From 80d0e78a03bb8e1199d02fc4be45ab15243f98fd Mon Sep 17 00:00:00 2001 From: Christopher Douglas Date: Mon, 1 Mar 2010 19:43:49 +0000 Subject: [PATCH] JDiff output for release 0.20.2 git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/trunk@917671 13f79535-47bb-0310-9956-ffa450edef68 --- lib/jdiff/hadoop_0.20.2.xml | 53959 ++++++++++++++++++++++++++++++++++ 1 file changed, 53959 insertions(+) create mode 100644 lib/jdiff/hadoop_0.20.2.xml diff --git a/lib/jdiff/hadoop_0.20.2.xml b/lib/jdiff/hadoop_0.20.2.xml new file mode 100644 index 00000000000..36a2a4b158f --- /dev/null +++ b/lib/jdiff/hadoop_0.20.2.xml @@ -0,0 +1,53959 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + final. + + @param name resource to be added, the classpath is examined for a file + with that name.]]> + + + + + + final. + + @param url url of the resource to be added, the local filesystem is + examined directly to find the resource, without referring to + the classpath.]]> + + + + + + final. + + @param file file-path of resource to be added, the local filesystem is + examined directly to find the resource, without referring to + the classpath.]]> + + + + + + final. + + @param in InputStream to deserialize the object from.]]> + + + + + + + + + + + name property, null if + no such property exists. + + Values are processed for variable expansion + before being returned. + + @param name the property name. + @return the value of the name property, + or null if no such property exists.]]> + + + + + + name property, without doing + variable expansion. + + @param name the property name. + @return the value of the name property, + or null if no such property exists.]]> + + + + + + + value of the name property. + + @param name property name. + @param value property value.]]> + + + + + + + + + + + + + + name property. If no such property + exists, then defaultValue is returned. + + @param name property name. + @param defaultValue default value. + @return property value, or defaultValue if the property + doesn't exist.]]> + + + + + + + name property as an int. + + If no such property exists, or if the specified value is not a valid + int, then defaultValue is returned. + + @param name property name. + @param defaultValue default value. + @return property value as an int, + or defaultValue.]]> + + + + + + + name property to an int. + + @param name property name. + @param value int value of the property.]]> + + + + + + + name property as a long. + If no such property is specified, or if the specified value is not a valid + long, then defaultValue is returned. + + @param name property name. + @param defaultValue default value. + @return property value as a long, + or defaultValue.]]> + + + + + + + name property to a long. + + @param name property name. + @param value long value of the property.]]> + + + + + + + name property as a float. + If no such property is specified, or if the specified value is not a valid + float, then defaultValue is returned. + + @param name property name. + @param defaultValue default value. + @return property value as a float, + or defaultValue.]]> + + + + + + + name property to a float. + + @param name property name. + @param value property value.]]> + + + + + + + name property as a boolean. + If no such property is specified, or if the specified value is not a valid + boolean, then defaultValue is returned. + + @param name property name. + @param defaultValue default value. + @return property value as a boolean, + or defaultValue.]]> + + + + + + + name property to a boolean. + + @param name property name. + @param value boolean value of the property.]]> + + + + + + + + + + + + + + + + + + + + name property as + a collection of Strings. + If no such property is specified then empty collection is returned. +

+ This is an optimized version of {@link #getStrings(String)} + + @param name property name. + @return property value as a collection of Strings.]]> + + + + + + name property as + an array of Strings. + If no such property is specified then null is returned. + + @param name property name. + @return property value as an array of Strings, + or null.]]> + + + + + + + name property as + an array of Strings. + If no such property is specified then default value is returned. + + @param name property name. + @param defaultValue The default value + @return property value as an array of Strings, + or default value.]]> + + + + + + + name property as + as comma delimited values. + + @param name property name. + @param values The values]]> + + + + + + + + + + + + + + name property + as an array of Class. + The value of the property specifies a list of comma separated class names. + If no such property is specified, then defaultValue is + returned. + + @param name the property name. + @param defaultValue default value. + @return property value as a Class[], + or defaultValue.]]> + + + + + + + name property as a Class. + If no such property is specified, then defaultValue is + returned. + + @param name the class name. + @param defaultValue default value. + @return property value as a Class, + or defaultValue.]]> + + + + + + + + name property as a Class + implementing the interface specified by xface. + + If no such property is specified, then defaultValue is + returned. + + An exception is thrown if the returned class does not implement the named + interface. + + @param name the class name. + @param defaultValue default value. + @param xface the interface implemented by the named class. + @return property value as a Class, + or defaultValue.]]> + + + + + + + + name property to the name of a + theClass implementing the given interface xface. + + An exception is thrown if theClass does not implement the + interface xface. + + @param name property name. + @param theClass property value. + @param xface the interface implemented by the named class.]]> + + + + + + + + dirsProp with + the given path. If dirsProp contains multiple directories, + then one is chosen based on path's hash code. If the selected + directory does not exist, an attempt is made to create it. + + @param dirsProp directory in which to locate the file. + @param path file-path. + @return local file under the directory with the given path.]]> + + + + + + + + dirsProp with + the given path. If dirsProp contains multiple directories, + then one is chosen based on path's hash code. If the selected + directory does not exist, an attempt is made to create it. + + @param dirsProp directory in which to locate the file. + @param path file-path. + @return local file under the directory with the given path.]]> + + + + + + + + + + + + name. + + @param name configuration resource name. + @return an input stream attached to the resource.]]> + + + + + + name. + + @param name configuration resource name. + @return a reader attached to the resource.]]> + + + + + + + + + + + + + + + String + key-value pairs in the configuration. + + @return an iterator over the entries.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + true to set quiet-mode on, false + to turn it off.]]> + + + + + + + + + + + + + + + + + + + Resources + +

Configurations are specified by resources. A resource contains a set of + name/value pairs as XML data. Each resource is named by either a + String or by a {@link Path}. If named by a String, + then the classpath is examined for a file with that name. If named by a + Path, then the local filesystem is examined directly, without + referring to the classpath. + +

Unless explicitly turned off, Hadoop by default specifies two + resources, loaded in-order from the classpath:

    +
  1. core-default.xml + : Read-only defaults for hadoop.
    2. +
  2. core-site.xml: Site-specific configuration for a given hadoop + installation.
    3. +
+ Applications may add additional resources, which are loaded + subsequent to these resources in the order they are added. + +

Final Parameters

+ +

Configuration parameters may be declared final. + Once a resource declares a value final, no subsequently-loaded + resource can alter that value. + For example, one might define a final parameter with: + 

+  <property>
+    <name>dfs.client.buffer.dir</name>
+    <value>/tmp/hadoop/dfs/client</value>
+    <final>true</final>
+  </property>
+ + Administrators typically define parameters as final in + core-site.xml for values that user applications may not alter. + +

Variable Expansion

+ +

Value strings are first processed for variable expansion. The + available properties are:

    +
  1. Other properties defined in this Configuration; and, if a name is + undefined here,
    2. +
  2. Properties in {@link System#getProperties()}.
    3. +
+ +

For example, if a configuration resource contains the following property + definitions: + 

+  <property>
+    <name>basedir</name>
+    <value>/user/${user.name}</value>
+  </property>
+  
+  <property>
+    <name>tempdir</name>
+    <value>${basedir}/tmp</value>
+  </property>
+ + When conf.get("tempdir") is called, then ${basedir} + will be resolved to another property in this Configuration, while + ${user.name} would then ordinarily be resolved to the value + of the System property with that name.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + DistributedCache is a facility provided by the Map-Reduce + framework to cache files (text, archives, jars etc.) needed by applications. +

+ +

Applications specify the files, via urls (hdfs:// or http://) to be cached + via the {@link org.apache.hadoop.mapred.JobConf}. + The DistributedCache assumes that the + files specified via hdfs:// urls are already present on the + {@link FileSystem} at the path specified by the url.

+ +

The framework will copy the necessary files on to the slave node before + any tasks for the job are executed on that node. Its efficiency stems from + the fact that the files are only copied once per job and the ability to + cache archives which are un-archived on the slaves.

+ +

DistributedCache can be used to distribute simple, read-only + data/text files and/or more complex types such as archives, jars etc. + Archives (zip, tar and tgz/tar.gz files) are un-archived at the slave nodes. + Jars may be optionally added to the classpath of the tasks, a rudimentary + software distribution mechanism. Files have execution permissions. + Optionally users can also direct it to symlink the distributed cache file(s) + into the working directory of the task.

+ +

DistributedCache tracks modification timestamps of the cache + files. Clearly the cache files should not be modified by the application + or externally while the job is executing.

+ +

Here is an illustrative example on how to use the + DistributedCache:

+ 

+     // Setting up the cache for the application
+     
+     1. Copy the requisite files to the FileSystem:
+     
+     $ bin/hadoop fs -copyFromLocal lookup.dat /myapp/lookup.dat  
+     $ bin/hadoop fs -copyFromLocal map.zip /myapp/map.zip  
+     $ bin/hadoop fs -copyFromLocal mylib.jar /myapp/mylib.jar
+     $ bin/hadoop fs -copyFromLocal mytar.tar /myapp/mytar.tar
+     $ bin/hadoop fs -copyFromLocal mytgz.tgz /myapp/mytgz.tgz
+     $ bin/hadoop fs -copyFromLocal mytargz.tar.gz /myapp/mytargz.tar.gz
+     
+     2. Setup the application's JobConf:
+     
+     JobConf job = new JobConf();
+     DistributedCache.addCacheFile(new URI("/myapp/lookup.dat#lookup.dat"), 
+                                   job);
+     DistributedCache.addCacheArchive(new URI("/myapp/map.zip", job);
+     DistributedCache.addFileToClassPath(new Path("/myapp/mylib.jar"), job);
+     DistributedCache.addCacheArchive(new URI("/myapp/mytar.tar", job);
+     DistributedCache.addCacheArchive(new URI("/myapp/mytgz.tgz", job);
+     DistributedCache.addCacheArchive(new URI("/myapp/mytargz.tar.gz", job);
+     
+     3. Use the cached files in the {@link org.apache.hadoop.mapred.Mapper}
+     or {@link org.apache.hadoop.mapred.Reducer}:
+     
+     public static class MapClass extends MapReduceBase  
+     implements Mapper<K, V, K, V> {
+     
+       private Path[] localArchives;
+       private Path[] localFiles;
+       
+       public void configure(JobConf job) {
+         // Get the cached archives/files
+         localArchives = DistributedCache.getLocalCacheArchives(job);
+         localFiles = DistributedCache.getLocalCacheFiles(job);
+       }
+       
+       public void map(K key, V value, 
+                       OutputCollector<K, V> output, Reporter reporter) 
+       throws IOException {
+         // Use data from the cached archives/files here
+         // ...
+         // ...
+         output.collect(k, v);
+       }
+     }
+     
+

+ + @see org.apache.hadoop.mapred.JobConf + @see org.apache.hadoop.mapred.JobClient]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + BufferedFSInputStream + with the specified buffer size, + and saves its argument, the input stream + in, for later use. An internal + buffer array of length size + is created and stored in buf. + + @param in the underlying input stream. + @param size the buffer size. + @exception IllegalArgumentException if size <= 0.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + setReplication of FileSystem + @param src file name + @param replication new replication + @throws IOException + @return true if successful; + false if file does not exist or is a directory]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + fs.scheme.class whose value names the FileSystem class. + The entire URI is passed to the FileSystem instance's initialize method.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Return all the files that match filePattern and are not checksum + files. Results are sorted by their names. + +

+ A filename pattern is composed of regular characters and + special pattern matching characters, which are: + +

+
+
+

+

? +
Matches any single character. + +

+

* +
Matches zero or more characters. + +

+

[abc] +
Matches a single character from character set + {a,b,c}. + +

+

[a-b] +
Matches a single character from the character range + {a...b}. Note that character a must be + lexicographically less than or equal to character b. + +

+

[^a] +
Matches a single character that is not from character set or range + {a}. Note that the ^ character must occur + immediately to the right of the opening bracket. + +

+

\c +
Removes (escapes) any special meaning of character c. + +

+

{ab,cd} +
Matches a string from the string set {ab, cd} + +

+

{ab,c{de,fh}} +
Matches a string from the string set {ab, cde, cfh} + +
+
+
+ + @param pathPattern a regular expression specifying a pth pattern + + @return an array of paths that match the path pattern + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + All user code that may potentially use the Hadoop Distributed + File System should be written to use a FileSystem object. The + Hadoop DFS is a multi-machine system that appears as a single + disk. It's useful because of its fault tolerance and potentially + very large capacity. + +

+ The local implementation is {@link LocalFileSystem} and distributed + implementation is DistributedFileSystem.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + FilterFileSystem contains + some other file system, which it uses as + its basic file system, possibly transforming + the data along the way or providing additional + functionality. The class FilterFileSystem + itself simply overrides all methods of + FileSystem with versions that + pass all requests to the contained file + system. Subclasses of FilterFileSystem + may further override some of these methods + and may also provide additional methods + and fields.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + buf at offset + and checksum into checksum. + The method is used for implementing read, therefore, it should be optimized + for sequential reading + @param pos chunkPos + @param buf desitination buffer + @param offset offset in buf at which to store data + @param len maximun number of bytes to read + @return number of bytes read]]> + + + + + + + + + + + + + + + + + -1 if the end of the + stream is reached. + @exception IOException if an I/O error occurs.]]> + + + + + + + + + This method implements the general contract of the corresponding + {@link InputStream#read(byte[], int, int) read} method of + the {@link InputStream} class. As an additional + convenience, it attempts to read as many bytes as possible by repeatedly + invoking the read method of the underlying stream. This + iterated read continues until one of the following + conditions becomes true:

    + +
  • The specified number of bytes have been read, + +
  • The read method of the underlying stream returns + -1, indicating end-of-file. + +
If the first read on the underlying stream returns + -1 to indicate end-of-file then this method returns + -1. Otherwise this method returns the number of bytes + actually read. + + @param b destination buffer. + @param off offset at which to start storing bytes. + @param len maximum number of bytes to read. + @return the number of bytes read, or -1 if the end of + the stream has been reached. + @exception IOException if an I/O error occurs. + ChecksumException if any checksum error occurs]]> + + + + + + + + + + + + + + + + + + + n bytes of data from the + input stream. + +

This method may skip more bytes than are remaining in the backing + file. This produces no exception and the number of bytes skipped + may include some number of bytes that were beyond the EOF of the + backing file. Attempting to read from the stream after skipping past + the end will result in -1 indicating the end of the file. + +

If n is negative, no bytes are skipped. + + @param n the number of bytes to be skipped. + @return the actual number of bytes skipped. + @exception IOException if an I/O error occurs. + ChecksumException if the chunk to skip to is corrupted]]> + + + + + + + This method may seek past the end of the file. + This produces no exception and an attempt to read from + the stream will result in -1 indicating the end of the file. + + @param pos the postion to seek to. + @exception IOException if an I/O error occurs. + ChecksumException if the chunk to seek to is corrupted]]> + + + + + + + + + + len bytes from + stm + + @param stm an input stream + @param buf destiniation buffer + @param offset offset at which to store data + @param len number of bytes to read + @return actual number of bytes read + @throws IOException if there is any IO error]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + len bytes from the specified byte array + starting at offset off and generate a checksum for + each data chunk. + +

This method stores bytes from the given array into this + stream's buffer before it gets checksumed. The buffer gets checksumed + and flushed to the underlying output stream when all data + in a checksum chunk are in the buffer. If the buffer is empty and + requested length is at least as large as the size of next checksum chunk + size, this method will checksum and write the chunk directly + to the underlying output stream. Thus it avoids uneccessary data copy. + + @param b the data. + @param off the start offset in the data. + @param len the number of bytes to write. + @exception IOException if an I/O error occurs.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if and only if pathname + should be included]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + trash feature. Files are moved to a user's trash + directory, a subdirectory of their home directory named ".Trash". Files are + initially moved to a current sub-directory of the trash directory. + Within that sub-directory their original path is preserved. Periodically + one may checkpoint the current trash and remove older checkpoints. (This + design permits trash management without enumeration of the full trash + content, without date support in the filesystem, and without clock + synchronization.)]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A {@link FileSystem} backed by an FTP client provided by Apache Commons Net. +

]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + (cause==null ? null : cause.toString()) (which + typically contains the class and detail message of cause). + @param cause the cause (which is saved for later retrieval by the + {@link #getCause()} method). (A null value is + permitted, and indicates that the cause is nonexistent or + unknown.)]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This class is a tool for migrating data from an older to a newer version + of an S3 filesystem. +

+

+ All files in the filesystem are migrated by re-writing the block metadata + - no datafiles are touched. +

]]> + + + + + + + + + + + + + + + + + + + + + Extracts AWS credentials from the filesystem URI or configuration. +

]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A block-based {@link FileSystem} backed by + Amazon S3. +

+ @see NativeS3FileSystem]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + If f is a file, this method will make a single call to S3. + If f is a directory, this method will make a maximum of + (n / 1000) + 2 calls to S3, where n is the total number of + files and directories contained directly in f. +

]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A {@link FileSystem} for reading and writing files stored on + Amazon S3. + Unlike {@link org.apache.hadoop.fs.s3.S3FileSystem} this implementation + stores files on S3 in their + native form so they can be read by other S3 tools. +

+ @see org.apache.hadoop.fs.s3.S3FileSystem]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + . + @param name The name of the server + @param port The port to use on the server + @param findPort whether the server should start at the given port and + increment by 1 until it finds a free port. + @param conf Configuration]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + points to the log directory + "/static/" -> points to common static files (src/webapps/static) + "/" -> the jsp server code from (src/webapps/)]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + nth value.]]> + + + + + + + + + + + + + + + + + + + + + nth value in the file.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + public class IntArrayWritable extends ArrayWritable { + public IntArrayWritable() { + super(IntWritable.class); + } + } + ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a ByteWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This saves memory over creating a new DataInputStream and + ByteArrayInputStream each time data is read. + +

Typical usage is something like the following:

+
+ DataInputBuffer buffer = new DataInputBuffer();
+ while (... loop condition ...) {
+   byte[] data = ... get data ...;
+   int dataLength = ... get data length ...;
+   buffer.reset(data, dataLength);
+   ... read buffer using DataInput methods ...
+ }
+
]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This saves memory over creating a new DataOutputStream and + ByteArrayOutputStream each time data is written. + +

Typical usage is something like the following:

+
+ DataOutputBuffer buffer = new DataOutputBuffer();
+ while (... loop condition ...) {
+   buffer.reset();
+   ... write buffer using DataOutput methods ...
+   byte[] data = buffer.getData();
+   int dataLength = buffer.getLength();
+   ... write data to its ultimate destination ...
+ }
+
]]> + + + + + + + + + + + + + + + + + + + + + + + + + + the class of the item + @param conf the configuration to store + @param item the object to be stored + @param keyName the name of the key to use + @throws IOException : forwards Exceptions from the underlying + {@link Serialization} classes.]]> + + + + + + + + + the class of the item + @param conf the configuration to use + @param keyName the name of the key to use + @param itemClass the class of the item + @return restored object + @throws IOException : forwards Exceptions from the underlying + {@link Serialization} classes.]]> + + + + + + + + + the class of the item + @param conf the configuration to use + @param items the objects to be stored + @param keyName the name of the key to use + @throws IndexOutOfBoundsException if the items array is empty + @throws IOException : forwards Exceptions from the underlying + {@link Serialization} classes.]]> + + + + + + + + + the class of the item + @param conf the configuration to use + @param keyName the name of the key to use + @param itemClass the class of the item + @return restored object + @throws IOException : forwards Exceptions from the underlying + {@link Serialization} classes.]]> + + + + + DefaultStringifier offers convenience methods to store/load objects to/from + the configuration. + + @param the class of the objects to stringify]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a DoubleWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a FloatWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + When two sequence files, which have same Key type but different Value + types, are mapped out to reduce, multiple Value types is not allowed. + In this case, this class can help you wrap instances with different types. +

+ +

+ Compared with ObjectWritable, this class is much more effective, + because ObjectWritable will append the class declaration as a String + into the output file in every Key-Value pair. +

+ +

+ Generic Writable implements {@link Configurable} interface, so that it will be + configured by the framework. The configuration is passed to the wrapped objects + implementing {@link Configurable} interface before deserialization. +

+ + how to use it:
+ 1. Write your own class, such as GenericObject, which extends GenericWritable.
+ 2. Implements the abstract method getTypes(), defines + the classes which will be wrapped in GenericObject in application. + Attention: this classes defined in getTypes() method, must + implement Writable interface. +

+ + The code looks like this: + 
+ public class GenericObject extends GenericWritable {
+ 
+   private static Class[] CLASSES = {
+               ClassType1.class, 
+               ClassType2.class,
+               ClassType3.class,
+               };
+
+   protected Class[] getTypes() {
+       return CLASSES;
+   }
+
+ }
+
+ + @since Nov 8, 2006]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This saves memory over creating a new InputStream and + ByteArrayInputStream each time data is read. + +

Typical usage is something like the following:

+
+ InputBuffer buffer = new InputBuffer();
+ while (... loop condition ...) {
+   byte[] data = ... get data ...;
+   int dataLength = ... get data length ...;
+   buffer.reset(data, dataLength);
+   ... read buffer using InputStream methods ...
+ }
+
+ @see DataInputBuffer + @see DataOutput]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a IntWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + closes the input and output streams + at the end. + @param in InputStrem to read from + @param out OutputStream to write to + @param conf the Configuration object]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ignore any {@link IOException} or + null pointers. Must only be used for cleanup in exception handlers. + @param log the log to record problems to at debug level. Can be null. + @param closeables the objects to close]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a LongWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A map is a directory containing two files, the data file, + containing all keys and values in the map, and a smaller index + file, containing a fraction of the keys. The fraction is determined by + {@link Writer#getIndexInterval()}. + +

The index file is read entirely into memory. Thus key implementations + should try to keep themselves small. + +

Map files are created by adding entries in-order. To maintain a large + database, perform updates by copying the previous version of a database and + merging in a sorted change list, to create a new version of the database in + a new file. Sorting large change lists can be done with {@link + SequenceFile.Sorter}.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + key and + val. Returns true if such a pair exists and false when at + the end of the map]]> + + + + + + + + + + + + + + + + key or if it does not exist, at the first entry + after the named key. + +- * @param key - key that we're trying to find +- * @param val - data value if key is found +- * @return - the key that was the closest match or null if eof.]]> + + + + + + + + + key does not exist, return + the first entry that falls just before the key. Otherwise, + return the record that sorts just after. + @return - the key that was the closest match or null if eof.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is an MD5Hash whose digest contains the + same values.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This saves memory over creating a new OutputStream and + ByteArrayOutputStream each time data is written. + +

Typical usage is something like the following:

+
+ OutputBuffer buffer = new OutputBuffer();
+ while (... loop condition ...) {
+   buffer.reset();
+   ... write buffer using OutputStream methods ...
+   byte[] data = buffer.getData();
+   int dataLength = buffer.getLength();
+   ... write data to its ultimate destination ...
+ }
+
+ @see DataOutputBuffer + @see InputBuffer]]> + + + + + + + + + + + + + + + + + A {@link Comparator} that operates directly on byte representations of + objects. +

+ @param + @see DeserializerComparator]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + SequenceFiles are flat files consisting of binary key/value + pairs. + +

SequenceFile provides {@link Writer}, {@link Reader} and + {@link Sorter} classes for writing, reading and sorting respectively.

+ + There are three SequenceFile Writers based on the + {@link CompressionType} used to compress key/value pairs: +
    +
  1. + Writer : Uncompressed records. +
    2. +
  2. + RecordCompressWriter : Record-compressed files, only compress + values. +
    3. +
  3. + BlockCompressWriter : Block-compressed files, both keys & + values are collected in 'blocks' + separately and compressed. The size of + the 'block' is configurable. +
+ +

The actual compression algorithm used to compress key and/or values can be + specified by using the appropriate {@link CompressionCodec}.

+ +

The recommended way is to use the static createWriter methods + provided by the SequenceFile to chose the preferred format.

+ +

The {@link Reader} acts as the bridge and can read any of the above + SequenceFile formats.

+ +

SequenceFile Formats

+ +

Essentially there are 3 different formats for SequenceFiles + depending on the CompressionType specified. All of them share a + common header described below. + +

+
    +
  • + version - 3 bytes of magic header SEQ, followed by 1 byte of actual + version number (e.g. SEQ4 or SEQ6) +
    • +
  • + keyClassName -key class +
    • +
  • + valueClassName - value class +
    • +
  • + compression - A boolean which specifies if compression is turned on for + keys/values in this file. +
    • +
  • + blockCompression - A boolean which specifies if block-compression is + turned on for keys/values in this file. +
    • +
  • + compression codec - CompressionCodec class which is used for + compression of keys and/or values (if compression is + enabled). +
    • +
  • + metadata - {@link Metadata} for this file. +
    • +
  • + sync - A sync marker to denote end of the header. +
    • +
+ +
Uncompressed SequenceFile Format
+
    +
  • + Header +
    • +
  • + Record +
      +
    • Record length
      • +
    • Key length
      • +
    • Key
      • +
    • Value
      • +
    +
    • +
  • + A sync-marker every few 100 bytes or so. +
    • +
+ +
Record-Compressed SequenceFile Format
+
    +
  • + Header +
    • +
  • + Record +
      +
    • Record length
      • +
    • Key length
      • +
    • Key
      • +
    • Compressed Value
      • +
    +
    • +
  • + A sync-marker every few 100 bytes or so. +
    • +
+ +
Block-Compressed SequenceFile Format
+
    +
  • + Header +
    • +
  • + Record Block +
      +
    • Compressed key-lengths block-size
      • +
    • Compressed key-lengths block
      • +
    • Compressed keys block-size
      • +
    • Compressed keys block
      • +
    • Compressed value-lengths block-size
      • +
    • Compressed value-lengths block
      • +
    • Compressed values block-size
      • +
    • Compressed values block
      • +
    +
    • +
  • + A sync-marker every few 100 bytes or so. +
    • +
+ +

The compressed blocks of key lengths and value lengths consist of the + actual lengths of individual keys/values encoded in ZeroCompressedInteger + format.

+ + @see CompressionCodec]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + key, skipping its + value. True if another entry exists, and false at end of file.]]> + + + + + + + + key and + val. Returns true if such a pair exists and false when at + end of file]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The position passed must be a position returned by {@link + SequenceFile.Writer#getLength()} when writing this file. To seek to an arbitrary + position, use {@link SequenceFile.Reader#sync(long)}.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + SegmentDescriptor + @param segments the list of SegmentDescriptors + @param tmpDir the directory to write temporary files into + @return RawKeyValueIterator + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + For best performance, applications should make sure that the {@link + Writable#readFields(DataInput)} implementation of their keys is + very efficient. In particular, it should avoid allocating memory.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This always returns a synchronized position. In other words, + immediately after calling {@link SequenceFile.Reader#seek(long)} with a position + returned by this method, {@link SequenceFile.Reader#next(Writable)} may be called. However + the key may be earlier in the file than key last written when this + method was called (e.g., with block-compression, it may be the first key + in the block that was being written when this method was called).]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + key. Returns + true if such a key exists and false when at the end of the set.]]> + + + + + + + key. + Returns key, or null if no match exists.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + the class of the objects to stringify]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + position. Note that this + method avoids using the converter or doing String instatiation + @return the Unicode scalar value at position or -1 + if the position is invalid or points to a + trailing byte]]> + + + + + + + + + + what in the backing + buffer, starting as position start. The starting + position is measured in bytes and the return value is in + terms of byte position in the buffer. The backing buffer is + not converted to a string for this operation. + @return byte position of the first occurence of the search + string in the UTF-8 buffer or -1 if not found]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a Text with the same contents.]]> + + + + + + + + + + + + + + + + + + + + + + + + + replace is true, then + malformed input is replaced with the + substitution character, which is U+FFFD. Otherwise the + method throws a MalformedInputException.]]> + + + + + + + + + + + + + + + replace is true, then + malformed input is replaced with the + substitution character, which is U+FFFD. Otherwise the + method throws a MalformedInputException. + @return ByteBuffer: bytes stores at ByteBuffer.array() + and length is ByteBuffer.limit()]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + In + addition, it provides methods for string traversal without converting the + byte array to a string.

Also includes utilities for + serializing/deserialing a string, coding/decoding a string, checking if a + byte array contains valid UTF8 code, calculating the length of an encoded + string.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a UTF8 with the same contents.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + Also includes utilities for efficiently reading and writing UTF-8. + + @deprecated replaced by Text]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This is useful when a class may evolve, so that instances written by the + old version of the class may still be processed by the new version. To + handle this situation, {@link #readFields(DataInput)} + implementations should catch {@link VersionMismatchException}.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a VIntWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + o is a VLongWritable with the same value.]]> + + + + + + + + + + + + + + + + + + + + + + + + out. + + @param out DataOuput to serialize this object into. + @throws IOException]]> + + + + + + + in. + +

For efficiency, implementations should attempt to re-use storage in the + existing object where possible.

+ + @param in DataInput to deseriablize this object from. + @throws IOException]]> + + + + Any key or value type in the Hadoop Map-Reduce + framework implements this interface.

+ +

Implementations typically implement a static read(DataInput) + method which constructs a new instance, calls {@link #readFields(DataInput)} + and returns the instance.

+ +

Example:

+ 

+     public class MyWritable implements Writable {
+       // Some data     
+       private int counter;
+       private long timestamp;
+       
+       public void write(DataOutput out) throws IOException {
+         out.writeInt(counter);
+         out.writeLong(timestamp);
+       }
+       
+       public void readFields(DataInput in) throws IOException {
+         counter = in.readInt();
+         timestamp = in.readLong();
+       }
+       
+       public static MyWritable read(DataInput in) throws IOException {
+         MyWritable w = new MyWritable();
+         w.readFields(in);
+         return w;
+       }
+     }
+

]]> + + + + + + + + + WritableComparables can be compared to each other, typically + via Comparators. Any type which is to be used as a + key in the Hadoop Map-Reduce framework should implement this + interface.

+ +

Example:

+ 

+     public class MyWritableComparable implements WritableComparable {
+       // Some data
+       private int counter;
+       private long timestamp;
+       
+       public void write(DataOutput out) throws IOException {
+         out.writeInt(counter);
+         out.writeLong(timestamp);
+       }
+       
+       public void readFields(DataInput in) throws IOException {
+         counter = in.readInt();
+         timestamp = in.readLong();
+       }
+       
+       public int compareTo(MyWritableComparable w) {
+         int thisValue = this.value;
+         int thatValue = ((IntWritable)o).value;
+         return (thisValue < thatValue ? -1 : (thisValue==thatValue ? 0 : 1));
+       }
+     }
+

]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The default implementation reads the data into two {@link + WritableComparable}s (using {@link + Writable#readFields(DataInput)}, then calls {@link + #compare(WritableComparable,WritableComparable)}.]]> + + + + + + + The default implementation uses the natural ordering, calling {@link + Comparable#compareTo(Object)}.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This base implemenation uses the natural ordering. To define alternate + orderings, override {@link #compare(WritableComparable,WritableComparable)}. + +

One may optimize compare-intensive operations by overriding + {@link #compare(byte[],int,int,byte[],int,int)}. Static utility methods are + provided to assist in optimized implementations of this method.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Enum type + @param in DataInput to read from + @param enumType Class type of Enum + @return Enum represented by String read from DataInput + @throws IOException]]> + + + + + + + + + + + + + + + + len number of bytes in input streamin + @param in input stream + @param len number of bytes to skip + @throws IOException when skipped less number of bytes]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CompressionCodec for which to get the + Compressor + @return Compressor for the given + CompressionCodec from the pool or a new one]]> + + + + + + CompressionCodec for which to get the + Decompressor + @return Decompressor for the given + CompressionCodec the pool or a new one]]> + + + + + + Compressor to be returned to the pool]]> + + + + + + Decompressor to be returned to the + pool]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Implementations are assumed to be buffered. This permits clients to + reposition the underlying input stream then call {@link #resetState()}, + without having to also synchronize client buffers.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true indicating that more input data is required. + + @param b Input data + @param off Start offset + @param len Length]]> + + + + + true if the input data buffer is empty and + #setInput() should be called in order to provide more input.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if the end of the compressed + data output stream has been reached.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true indicating that more input data is required. + + @param b Input data + @param off Start offset + @param len Length]]> + + + + + true if the input data buffer is empty and + #setInput() should be called in order to provide more input.]]> + + + + + + + + + + + + + true if a preset dictionary is needed for decompression. + @return true if a preset dictionary is needed for decompression]]> + + + + + true if the end of the compressed + data output stream has been reached.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + FIXME: This array should be in a private or package private location, + since it could be modified by malicious code. +

]]> + + + + + This interface is public for historical purposes. You should have no need to + use it. +

]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Although BZip2 headers are marked with the magic "Bz" this + constructor expects the next byte in the stream to be the first one after + the magic. Thus callers have to skip the first two bytes. Otherwise this + constructor will throw an exception. +

+ + @throws IOException + if the stream content is malformed or an I/O error occurs. + @throws NullPointerException + if in == null]]> + + + + + + + + + + + + + + + + + The decompression requires large amounts of memory. Thus you should call the + {@link #close() close()} method as soon as possible, to force + CBZip2InputStream to release the allocated memory. See + {@link CBZip2OutputStream CBZip2OutputStream} for information about memory + usage. +

+ +

+ CBZip2InputStream reads bytes from the compressed source stream via + the single byte {@link java.io.InputStream#read() read()} method exclusively. + Thus you should consider to use a buffered source stream. +

+ +

+ Instances of this class are not threadsafe. +

]]> + + + + + + + + + + CBZip2OutputStream with a blocksize of 900k. + +

+ Attention: The caller is resonsible to write the two BZip2 magic + bytes "BZ" to the specified stream prior to calling this + constructor. +

+ + @param out * + the destination stream. + + @throws IOException + if an I/O error occurs in the specified stream. + @throws NullPointerException + if out == null.]]> + + + + + + CBZip2OutputStream with specified blocksize. + +

+ Attention: The caller is resonsible to write the two BZip2 magic + bytes "BZ" to the specified stream prior to calling this + constructor. +

+ + + @param out + the destination stream. + @param blockSize + the blockSize as 100k units. + + @throws IOException + if an I/O error occurs in the specified stream. + @throws IllegalArgumentException + if (blockSize < 1) || (blockSize > 9). + @throws NullPointerException + if out == null. + + @see #MIN_BLOCKSIZE + @see #MAX_BLOCKSIZE]]> + + + + + + + + + + + + + + + inputLength this method returns MAX_BLOCKSIZE + always. + + @param inputLength + The length of the data which will be compressed by + CBZip2OutputStream.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + == 1.]]> + + + + + == 9.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + If you are ever unlucky/improbable enough to get a stack overflow whilst + sorting, increase the following constant and try again. In practice I + have never seen the stack go above 27 elems, so the following limit seems + very generous. +

]]> + + + + + The compression requires large amounts of memory. Thus you should call the + {@link #close() close()} method as soon as possible, to force + CBZip2OutputStream to release the allocated memory. +

+ +

+ You can shrink the amount of allocated memory and maybe raise the compression + speed by choosing a lower blocksize, which in turn may cause a lower + compression ratio. You can avoid unnecessary memory allocation by avoiding + using a blocksize which is bigger than the size of the input. +

+ +

+ You can compute the memory usage for compressing by the following formula: +

+ + 
+ <code>400k + (9 * blocksize)</code>.
+
+ +

+ To get the memory required for decompression by {@link CBZip2InputStream + CBZip2InputStream} use +

+ + 
+ <code>65k + (5 * blocksize)</code>.
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Memory usage by blocksize
Blocksize Compression
+ memory usage		 Decompression
+ memory usage
100k1300k565k
200k2200k1065k
300k3100k1565k
400k4000k2065k
500k4900k2565k
600k5800k3065k
700k6700k3565k
800k7600k4065k
900k8500k4565k
+ +

+ For decompression CBZip2InputStream allocates less memory if the + bzipped input is smaller than one block. +

+ +

+ Instances of this class are not threadsafe. +

+ +

+ TODO: Update to BZip2 1.0.1 +

]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @return the total (non-negative) number of uncompressed bytes input so far]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @return the total (non-negative) number of uncompressed bytes input so far]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if native-zlib is loaded & initialized + and can be loaded for this job, else false]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
  • "none" - No compression. +
  • "lzo" - LZO compression. +
  • "gz" - GZIP compression. + ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
  • Block Compression. +
  • Named meta data blocks. +
  • Sorted or unsorted keys. +
  • Seek by key or by file offset. + + The memory footprint of a TFile includes the following: +
      +
    • Some constant overhead of reading or writing a compressed block. +
        +
      • Each compressed block requires one compression/decompression codec for + I/O. +
      • Temporary space to buffer the key. +
      • Temporary space to buffer the value (for TFile.Writer only). Values are + chunk encoded, so that we buffer at most one chunk of user data. By default, + the chunk buffer is 1MB. Reading chunked value does not require additional + memory. +
      +
    • TFile index, which is proportional to the total number of Data Blocks. + The total amount of memory needed to hold the index can be estimated as + (56+AvgKeySize)*NumBlocks. +
    • MetaBlock index, which is proportional to the total number of Meta + Blocks.The total amount of memory needed to hold the index for Meta Blocks + can be estimated as (40+AvgMetaBlockName)*NumMetaBlock. +
    +

    + The behavior of TFile can be customized by the following variables through + Configuration: +

      +
    • tfile.io.chunk.size: Value chunk size. Integer (in bytes). Default + to 1MB. Values of the length less than the chunk size is guaranteed to have + known value length in read time (See + {@link TFile.Reader.Scanner.Entry#isValueLengthKnown()}). +
    • tfile.fs.output.buffer.size: Buffer size used for + FSDataOutputStream. Integer (in bytes). Default to 256KB. +
    • tfile.fs.input.buffer.size: Buffer size used for + FSDataInputStream. Integer (in bytes). Default to 256KB. +
    +

    + Suggestions on performance optimization. +

      +
    • Minimum block size. We recommend a setting of minimum block size between + 256KB to 1MB for general usage. Larger block size is preferred if files are + primarily for sequential access. However, it would lead to inefficient random + access (because there are more data to decompress). Smaller blocks are good + for random access, but require more memory to hold the block index, and may + be slower to create (because we must flush the compressor stream at the + conclusion of each data block, which leads to an FS I/O flush). Further, due + to the internal caching in Compression codec, the smallest possible block + size would be around 20KB-30KB. +
    • The current implementation does not offer true multi-threading for + reading. The implementation uses FSDataInputStream seek()+read(), which is + shown to be much faster than positioned-read call in single thread mode. + However, it also means that if multiple threads attempt to access the same + TFile (using multiple scanners) simultaneously, the actual I/O is carried out + sequentially even if they access different DFS blocks. +
    • Compression codec. Use "none" if the data is not very compressable (by + compressable, I mean a compression ratio at least 2:1). Generally, use "lzo" + as the starting point for experimenting. "gz" overs slightly better + compression ratio over "lzo" but requires 4x CPU to compress and 2x CPU to + decompress, comparing to "lzo". +
    • File system buffering, if the underlying FSDataInputStream and + FSDataOutputStream is already adequately buffered; or if applications + reads/writes keys and values in large buffers, we can reduce the sizes of + input/output buffering in TFile layer by setting the configuration parameters + "tfile.fs.input.buffer.size" and "tfile.fs.output.buffer.size". +
    + + Some design rationale behind TFile can be found at Hadoop-3315.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + entry of the TFile. + @param endKey + End key of the scan. If null, scan up to the last entry + of the TFile. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Use {@link Scanner#atEnd()} to test whether the cursor is at the end + location of the scanner. +

    + Use {@link Scanner#advance()} to move the cursor to the next key-value + pair (or end if none exists). Use seekTo methods ( + {@link Scanner#seekTo(byte[])} or + {@link Scanner#seekTo(byte[], int, int)}) to seek to any arbitrary + location in the covered range (including backward seeking). Use + {@link Scanner#rewind()} to seek back to the beginning of the scanner. + Use {@link Scanner#seekToEnd()} to seek to the end of the scanner. +

    + Actual keys and values may be obtained through {@link Scanner.Entry} + object, which is obtained through {@link Scanner#entry()}.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  • Algorithmic comparator: binary comparators that is language + independent. Currently, only "memcmp" is supported. +
  • Language-specific comparator: binary comparators that can + only be constructed in specific language. For Java, the syntax + is "jclass:", followed by the class name of the RawComparator. + Currently, we only support RawComparators that can be + constructed through the default constructor (with no + parameters). Parameterized RawComparators such as + {@link WritableComparator} or + {@link JavaSerializationComparator} may not be directly used. + One should write a wrapper class that inherits from such classes + and use its default constructor to perform proper + initialization. + + @param conf + The configuration object. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + If an exception is thrown, the TFile will be in an inconsistent + state. The only legitimate call after that would be close]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Utils#writeVLong(out, n). + + @param out + output stream + @param n + The integer to be encoded + @throws IOException + @see Utils#writeVLong(DataOutput, long)]]> + + + + + + + + +
  • if n in [-32, 127): encode in one byte with the actual value. + Otherwise, +
  • if n in [-20*2^8, 20*2^8): encode in two bytes: byte[0] = n/256 - 52; + byte[1]=n&0xff. Otherwise, +
  • if n IN [-16*2^16, 16*2^16): encode in three bytes: byte[0]=n/2^16 - + 88; byte[1]=(n>>8)&0xff; byte[2]=n&0xff. Otherwise, +
  • if n in [-8*2^24, 8*2^24): encode in four bytes: byte[0]=n/2^24 - 112; + byte[1] = (n>>16)&0xff; byte[2] = (n>>8)&0xff; byte[3]=n&0xff. Otherwise: +
  • if n in [-2^31, 2^31): encode in five bytes: byte[0]=-125; byte[1] = + (n>>24)&0xff; byte[2]=(n>>16)&0xff; byte[3]=(n>>8)&0xff; byte[4]=n&0xff; +
  • if n in [-2^39, 2^39): encode in six bytes: byte[0]=-124; byte[1] = + (n>>32)&0xff; byte[2]=(n>>24)&0xff; byte[3]=(n>>16)&0xff; + byte[4]=(n>>8)&0xff; byte[5]=n&0xff +
  • if n in [-2^47, 2^47): encode in seven bytes: byte[0]=-123; byte[1] = + (n>>40)&0xff; byte[2]=(n>>32)&0xff; byte[3]=(n>>24)&0xff; + byte[4]=(n>>16)&0xff; byte[5]=(n>>8)&0xff; byte[6]=n&0xff; +
  • if n in [-2^55, 2^55): encode in eight bytes: byte[0]=-122; byte[1] = + (n>>48)&0xff; byte[2] = (n>>40)&0xff; byte[3]=(n>>32)&0xff; + byte[4]=(n>>24)&0xff; byte[5]=(n>>16)&0xff; byte[6]=(n>>8)&0xff; + byte[7]=n&0xff; +
  • if n in [-2^63, 2^63): encode in nine bytes: byte[0]=-121; byte[1] = + (n>>54)&0xff; byte[2] = (n>>48)&0xff; byte[3] = (n>>40)&0xff; + byte[4]=(n>>32)&0xff; byte[5]=(n>>24)&0xff; byte[6]=(n>>16)&0xff; + byte[7]=(n>>8)&0xff; byte[8]=n&0xff; + + + @param out + output stream + @param n + the integer number + @throws IOException]]> + + + + + + + (int)Utils#readVLong(in). + + @param in + input stream + @return the decoded integer + @throws IOException + + @see Utils#readVLong(DataInput)]]> + + + + + + + +
  • if (FB >= -32), return (long)FB; +
  • if (FB in [-72, -33]), return (FB+52)<<8 + NB[0]&0xff; +
  • if (FB in [-104, -73]), return (FB+88)<<16 + (NB[0]&0xff)<<8 + + NB[1]&0xff; +
  • if (FB in [-120, -105]), return (FB+112)<<24 + (NB[0]&0xff)<<16 + + (NB[1]&0xff)<<8 + NB[2]&0xff; +
  • if (FB in [-128, -121]), return interpret NB[FB+129] as a signed + big-endian integer. + + @param in + input stream + @return the decoded long integer. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + Type of the input key. + @param list + The list + @param key + The input key. + @param cmp + Comparator for the key. + @return The index to the desired element if it exists; or list.size() + otherwise.]]> + + + + + + + + + Type of the input key. + @param list + The list + @param key + The input key. + @param cmp + Comparator for the key. + @return The index to the desired element if it exists; or list.size() + otherwise.]]> + + + + + + + + Type of the input key. + @param list + The list + @param key + The input key. + @return The index to the desired element if it exists; or list.size() + otherwise.]]> + + + + + + + + Type of the input key. + @param list + The list + @param key + The input key. + @return The index to the desired element if it exists; or list.size() + otherwise.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Keep trying a limited number of times, waiting a fixed time between attempts, + and then fail by re-throwing the exception. +

    ]]> +     +     + + + + + + + Keep trying for a maximum time, waiting a fixed time between attempts, + and then fail by re-throwing the exception. +

    ]]> +     +     + + + + + + + Keep trying a limited number of times, waiting a growing amount of time between attempts, + and then fail by re-throwing the exception. + The time between attempts is sleepTime mutliplied by the number of tries so far. +

    ]]> +     +     + + + + + + + Keep trying a limited number of times, waiting a growing amount of time between attempts, + and then fail by re-throwing the exception. + The time between attempts is sleepTime mutliplied by a random + number in the range of [0, 2 to the number of retries) +

    ]]> +     +     + + + + + + Set a default policy with some explicit handlers for specific exceptions. +

    ]]> +     +     + + + + + + A retry policy for RemoteException + Set a default policy with some explicit handlers for specific exceptions. +

    ]]> +     +     + + + + Try once, and fail by re-throwing the exception. + This corresponds to having no retry mechanism in place. +

    ]]> +     +     + + + + Try once, and fail silently for void methods, or by + re-throwing the exception for non-void methods. +

    ]]> +     +     + + + + Keep trying forever. +

    ]]> +     +     + + + A collection of useful implementations of {@link RetryPolicy}. +

    ]]> +     +     + + + + + + + + + + Determines whether the framework should retry a + method for the given exception, and the number + of retries that have been made for that operation + so far. +

    + @param e The exception that caused the method to fail. + @param retries The number of times the method has been retried. + @return true if the method should be retried, + false if the method should not be retried + but shouldn't fail with an exception (only for void methods). + @throws Exception The re-thrown exception e indicating + that the method failed and should not be retried further.]]> +     +     + + + Specifies a policy for retrying method failures. + Implementations of this interface should be immutable. +

    ]]> +     +     + + + + + + + + + + + + Create a proxy for an interface of an implementation class + using the same retry policy for each method in the interface. +

    + @param iface the interface that the retry will implement + @param implementation the instance whose methods should be retried + @param retryPolicy the policy for retirying method call failures + @return the retry proxy]]> +     +     + + + + + + + Create a proxy for an interface of an implementation class + using the a set of retry policies specified by method name. + If no retry policy is defined for a method then a default of + {@link RetryPolicies#TRY_ONCE_THEN_FAIL} is used. +

    + @param iface the interface that the retry will implement + @param implementation the instance whose methods should be retried + @param methodNameToPolicyMap a map of method names to retry policies + @return the retry proxy]]> +     +     + + + A factory for creating retry proxies. +

    ]]> +     +     + +     + + + + + + + + Prepare the deserializer for reading.

    ]]> +     +     + + + + + + Deserialize the next object from the underlying input stream. + If the object t is non-null then this deserializer + may set its internal state to the next object read from the input + stream. Otherwise, if the object t is null a new + deserialized object will be created. +

    + @return the deserialized object]]> +     +     + + + + Close the underlying input stream and clear up any resources.

    ]]> +     +     + + + Provides a facility for deserializing objects of type from an + {@link InputStream}. +

    + +

    + Deserializers are stateful, but must not buffer the input since + other producers may read from the input between calls to + {@link #deserialize(Object)}. +

    + @param ]]> +     +     + + + + + + + + + + + + + + + + + + A {@link RawComparator} that uses a {@link Deserializer} to deserialize + the objects to be compared so that the standard {@link Comparator} can + be used to compare them. +

    +

    + One may optimize compare-intensive operations by using a custom + implementation of {@link RawComparator} that operates directly + on byte representations. +

    + @param ]]> +     +     + + + + + + + + + + + + + + + + + + An experimental {@link Serialization} for Java {@link Serializable} classes. +

    + @see JavaSerializationComparator]]> +     +     + + + + + + + + + + + + + A {@link RawComparator} that uses a {@link JavaSerialization} + {@link Deserializer} to deserialize objects that are then compared via + their {@link Comparable} interfaces. +

    + @param + @see JavaSerialization]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + Encapsulates a {@link Serializer}/{@link Deserializer} pair. +

    + @param ]]> +     +     + + + + + + + Serializations are found by reading the io.serializations + property from conf, which is a comma-delimited list of + classnames. +

    ]]> +     +     + + + + + + + + + + + + A factory for {@link Serialization}s. +

    ]]> +     +     + + + + + + + + Prepare the serializer for writing.

    ]]> +     +     + + + + + Serialize t to the underlying output stream.

    ]]> +     +     + + + + Close the underlying output stream and clear up any resources.

    ]]> +     +     + + + Provides a facility for serializing objects of type to an + {@link OutputStream}. +

    + +

    + Serializers are stateful, but must not buffer the output since + other producers may write to the output between calls to + {@link #serialize(Object)}. +

    + @param ]]> +     +     + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + param, to the IPC server running at + address, returning the value. Throws exceptions if there are + network problems or if the remote code threw an exception. + @deprecated Use {@link #call(Writable, InetSocketAddress, Class, UserGroupInformation)} instead]]> + + + + + + + + + + param, to the IPC server running at + address with the ticket credentials, returning + the value. + Throws exceptions if there are network problems or if the remote code + threw an exception. + @deprecated Use {@link #call(Writable, InetSocketAddress, Class, UserGroupInformation)} instead]]> + + + + + + + + + + + param, to the IPC server running at + address which is servicing the protocol protocol, + with the ticket credentials, returning the value. + Throws exceptions if there are network problems or if the remote code + threw an exception.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Unwraps any IOException. + + @param lookupTypes the desired exception class. + @return IOException, which is either the lookupClass exception or this.]]> + + + + + This unwraps any Throwable that has a constructor taking + a String as a parameter. + Otherwise it returns this. + + @return Throwable]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + protocol is a Java interface. All parameters and return types must + be one of: + +
    • a primitive type, boolean, byte, + char, short, int, long, + float, double, or void; or
      • + +
    • a {@link String}; or
      • + +
    • a {@link Writable}; or
      • + +
    • an array of the above types
    + + All methods in the protocol should throw only IOException. No field data of + the protocol instance is transmitted.]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + handlerCount determines + the number of handler threads that will be used to process calls.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + ,name=RpcActivityForPort" + + Many of the activity metrics are sampled and averaged on an interval + which can be specified in the metrics config file. +

    + For the metrics that are sampled and averaged, one must specify + a metrics context that does periodic update calls. Most metrics contexts do. + The default Null metrics context however does NOT. So if you aren't + using any other metrics context then you can turn on the viewing and averaging + of sampled metrics by specifying the following two lines + in the hadoop-meterics.properties file: + 

    +        rpc.class=org.apache.hadoop.metrics.spi.NullContextWithUpdateThread
+        rpc.period=10
+
    +

    + Note that the metrics are collected regardless of the context used. + The context with the update thread is used to average the data periodically + + + + Impl details: We use a dynamic mbean that gets the list of the metrics + from the metrics registry passed as an argument to the constructor]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This class has a number of metrics variables that are publicly accessible; + these variables (objects) have methods to update their values; + for example: +

    {@link #rpcQueueTime}.inc(time)]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + For the statistics that are sampled and averaged, one must specify + a metrics context that does periodic update calls. Most do. + The default Null metrics context however does NOT. So if you aren't + using any other metrics context then you can turn on the viewing and averaging + of sampled metrics by specifying the following two lines + in the hadoop-meterics.properties file: + 

    +        rpc.class=org.apache.hadoop.metrics.spi.NullContextWithUpdateThread
+        rpc.period=10
+
    +

    + Note that the metrics are collected regardless of the context used. + The context with the update thread is used to average the data periodically]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + When constructing the instance, if the factory property + contextName.class exists, + its value is taken to be the name of the class to instantiate. Otherwise, + the default is to create an instance of + org.apache.hadoop.metrics.spi.NullContext, which is a + dummy "no-op" context which will cause all metric data to be discarded. + + @param contextName the name of the context + @return the named MetricsContext]]> + + + + + + + + + + + + + + + + + + + + + When the instance is constructed, this method checks if the file + hadoop-metrics.properties exists on the class path. If it + exists, it must be in the format defined by java.util.Properties, and all + the properties in the file are set as attributes on the newly created + ContextFactory instance. + + @return the singleton ContextFactory instance]]> + + + + getFactory() method.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + startMonitoring() again after calling + this. + @see #close()]]> + + + + + + + + + + + + + + + + recordName. + Throws an exception if the metrics implementation is configured with a fixed + set of record names and recordName is not in that set. + + @param recordName the name of the record + @throws MetricsException if recordName conflicts with configuration data]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A record name identifies the kind of data to be reported. For example, a + program reporting statistics relating to the disks on a computer might use + a record name "diskStats".

    + + A record has zero or more tags. A tag has a name and a value. To + continue the example, the "diskStats" record might use a tag named + "diskName" to identify a particular disk. Sometimes it is useful to have + more than one tag, so there might also be a "diskType" with value "ide" or + "scsi" or whatever.

    + + A record also has zero or more metrics. These are the named + values that are to be reported to the metrics system. In the "diskStats" + example, possible metric names would be "diskPercentFull", "diskPercentBusy", + "kbReadPerSecond", etc.

    + + The general procedure for using a MetricsRecord is to fill in its tag and + metric values, and then call update() to pass the record to the + client library. + Metric data is not immediately sent to the metrics system + each time that update() is called. + An internal table is maintained, identified by the record name. This + table has columns + corresponding to the tag and the metric names, and rows + corresponding to each unique set of tag values. An update + either modifies an existing row in the table, or adds a new row with a set of + tag values that are different from all the other rows. Note that if there + are no tags, then there can be at most one row in the table.

    + + Once a row is added to the table, its data will be sent to the metrics system + on every timer period, whether or not it has been updated since the previous + timer period. If this is inappropriate, for example if metrics were being + reported by some transient object in an application, the remove() + method can be used to remove the row and thus stop the data from being + sent.

    + + Note that the update() method is atomic. This means that it is + safe for different threads to be updating the same metric. More precisely, + it is OK for different threads to call update() on MetricsRecord instances + with the same set of tag names and tag values. Different threads should + not use the same MetricsRecord instance at the same time.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + MetricsContext.registerUpdater().]]> + + + + + + + + + + + + + + + + + + + + + + + + + fileName attribute, + if specified. Otherwise the data will be written to standard + output.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + This class is configured by setting ContextFactory attributes which in turn + are usually configured through a properties file. All the attributes are + prefixed by the contextName. For example, the properties file might contain: + 

    + myContextName.fileName=/tmp/metrics.log
+ myContextName.period=5
+
    ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + contextName.tableName. The returned map consists of + those attributes with the contextName and tableName stripped off.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + recordName. + Throws an exception if the metrics implementation is configured with a fixed + set of record names and recordName is not in that set. + + @param recordName the name of the record + @throws MetricsException if recordName conflicts with configuration data]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This class implements the internal table of metric data, and the timer + on which data is to be sent to the metrics system. Subclasses must + override the abstract emitRecord method in order to transmit + the data.

    ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + update + and remove().]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + hostname or hostname:port. If + the specs string is null, defaults to localhost:defaultPort. + + @return a list of InetSocketAddress objects.]]> + + + + + + + + + + + + + + + + + + + ,name=" + Where the and are the supplied parameters + + @param serviceName + @param nameName + @param theMbean - the MBean to register + @return the named used to register the MBean]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + hadoop.rpc.socket.factory.class.<ClassName>. When no + such parameter exists then fall back on the default socket factory as + configured by hadoop.rpc.socket.factory.class.default. If + this default socket factory is not configured, then fall back on the JVM + default socket factory. + + @param conf the configuration + @param clazz the class (usually a {@link VersionedProtocol}) + @return a socket factory]]> + + + + + + hadoop.rpc.socket.factory.default + + @param conf the configuration + @return the default socket factory as specified in the configuration or + the JVM default socket factory if the configuration does not + contain a default socket factory property.]]> + + + + + + + + + + + + + : + ://:/]]> + + + + + + + + : + ://:/]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    + + From documentation for {@link #getInputStream(Socket, long)}:
    + Returns InputStream for the socket. If the socket has an associated + SocketChannel then it returns a + {@link SocketInputStream} with the given timeout. If the socket does not + have a channel, {@link Socket#getInputStream()} is returned. In the later + case, the timeout argument is ignored and the timeout set with + {@link Socket#setSoTimeout(int)} applies for reads.

    + + Any socket created using socket factories returned by {@link #NetUtils}, + must use this interface instead of {@link Socket#getInputStream()}. + + @see #getInputStream(Socket, long) + + @param socket + @return InputStream for reading from the socket. + @throws IOException]]> +     +     + + + + + +
    + + Any socket created using socket factories returned by {@link #NetUtils}, + must use this interface instead of {@link Socket#getInputStream()}. + + @see Socket#getChannel() + + @param socket + @param timeout timeout in milliseconds. This may not always apply. zero + for waiting as long as necessary. + @return InputStream for reading from the socket. + @throws IOException]]> +     +     + + + + +
    + + From documentation for {@link #getOutputStream(Socket, long)} :
    + Returns OutputStream for the socket. If the socket has an associated + SocketChannel then it returns a + {@link SocketOutputStream} with the given timeout. If the socket does not + have a channel, {@link Socket#getOutputStream()} is returned. In the later + case, the timeout argument is ignored and the write will wait until + data is available.

    + + Any socket created using socket factories returned by {@link #NetUtils}, + must use this interface instead of {@link Socket#getOutputStream()}. + + @see #getOutputStream(Socket, long) + + @param socket + @return OutputStream for writing to the socket. + @throws IOException]]> +     +     + + + + + +
    + + Any socket created using socket factories returned by {@link #NetUtils}, + must use this interface instead of {@link Socket#getOutputStream()}. + + @see Socket#getChannel() + + @param socket + @param timeout timeout in milliseconds. This may not always apply. zero + for waiting as long as necessary. + @return OutputStream for writing to the socket. + @throws IOException]]> +     +     + + + + + + + socket.connect(endpoint, timeout). If + socket.getChannel() returns a non-null channel, + connect is implemented using Hadoop's selectors. This is done mainly + to avoid Sun's connect implementation from creating thread-local + selectors, since Hadoop does not have control on when these are closed + and could end up taking all the available file descriptors. + + @see java.net.Socket#connect(java.net.SocketAddress, int) + + @param socket + @param endpoint + @param timeout - timeout in milliseconds]]> + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + node + + @param node + a node + @return true if node is already in the tree; false otherwise]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + scope + if scope starts with ~, choose one from the all nodes except for the + ones in scope; otherwise, choose one from scope + @param scope range of nodes from which a node will be choosen + @return the choosen node]]> + + + + + + + scope but not in excludedNodes + if scope starts with ~, return the number of nodes that are not + in scope and excludedNodes; + @param scope a path string that may start with ~ + @param excludedNodes a list of nodes + @return number of available nodes]]> + + + + + + + + + + + + reader + It linearly scans the array, if a local node is found, swap it with + the first element of the array. + If a local rack node is found, swap it with the first element following + the local node. + If neither local node or local rack node is found, put a random replica + location at postion 0. + It leaves the rest nodes untouched.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    + + Create a new input stream with the given timeout. If the timeout + is zero, it will be treated as infinite timeout. The socket's + channel will be configured to be non-blocking. + + @see SocketInputStream#SocketInputStream(ReadableByteChannel, long) + + @param socket should have a channel associated with it. + @param timeout timeout timeout in milliseconds. must not be negative. + @throws IOException]]> +     +     + + + +
    + + Create a new input stream with the given timeout. If the timeout + is zero, it will be treated as infinite timeout. The socket's + channel will be configured to be non-blocking. + @see SocketInputStream#SocketInputStream(ReadableByteChannel, long) + + @param socket should have a channel associated with it. + @throws IOException]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + +
    + + Create a new ouput stream with the given timeout. If the timeout + is zero, it will be treated as infinite timeout. The socket's + channel will be configured to be non-blocking. + + @see SocketOutputStream#SocketOutputStream(WritableByteChannel, long) + + @param socket should have a channel associated with it. + @param timeout timeout timeout in milliseconds. must not be negative. + @throws IOException]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + = getCount(). + @param newCapacity The new capacity in bytes.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Index idx = startVector(...); + while (!idx.done()) { + .... // read element of a vector + idx.incr(); + } + ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This task takes the given record definition files and compiles them into + java or c++ + files. It is then up to the user to compile the generated files. + +

    The task requires the file or the nested fileset element to be + specified. Optional attributes are language (set the output + language, default is "java"), + destdir (name of the destination directory for generated java/c++ + code, default is ".") and failonerror (specifies error handling + behavior. default is true). +

    Usage

    + 
    + <recordcc
+       destdir="${basedir}/gensrc"
+       language="java">
+   <fileset include="**\/*.jr" />
+ </recordcc>
+
    ]]> +     +     + +     + + + + + + ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + (cause==null ? null : cause.toString()) (which + typically contains the class and detail message of cause). + @param cause the cause (which is saved for later retrieval by the + {@link #getCause()} method). (A null value is + permitted, and indicates that the cause is nonexistent or + unknown.)]]> + + + + + + + + + + + + + Group with the given groupname. + @param group group name]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ugi. + @param ugi user + @return the {@link Subject} for the user identified by ugi]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ugi as a comma separated string in + conf as a property attr + + The String starts with the user name followed by the default group names, + and other group names. + + @param conf configuration + @param attr property name + @param ugi a UnixUserGroupInformation]]> + + + + + + + + conf + + The object is expected to store with the property name attr + as a comma separated string that starts + with the user name followed by group names. + If the property name is not defined, return null. + It's assumed that there is only one UGI per user. If this user already + has a UGI in the ugi map, return the ugi in the map. + Otherwise, construct a UGI from the configuration, store it in the + ugi map and return it. + + @param conf configuration + @param attr property name + @return a UnixUGI + @throws LoginException if the stored string is ill-formatted.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + User with the given username. + @param user user name]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + (cause==null ? null : cause.toString()) (which + typically contains the class and detail message of cause). + @param cause the cause (which is saved for later retrieval by the + {@link #getCause()} method). (A null value is + permitted, and indicates that the cause is nonexistent or + unknown.)]]> + + + + + + + + + + + + + + does not provide the stack trace for security purposes.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + service as related to + Service Level Authorization for Hadoop. + + Each service defines it's configuration key and also the necessary + {@link Permission} required to access the service.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + in]]> + + + + + + + out.]]> + + + + + + + + + + reset is true, then resets the checksum. + @return number of bytes written. Will be equal to getChecksumSize();]]> + + + + + + + + + reset is true, then resets the checksum. + @return number of bytes written. Will be equal to getChecksumSize();]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + GenericOptionsParser to parse only the generic Hadoop + arguments. + + The array of string arguments other than the generic arguments can be + obtained by {@link #getRemainingArgs()}. + + @param conf the Configuration to modify. + @param args command-line arguments.]]> + + + + + GenericOptionsParser to parse given options as well + as generic Hadoop options. + + The resulting CommandLine object can be obtained by + {@link #getCommandLine()}. + + @param conf the configuration to modify + @param options options built by the caller + @param args User-specified arguments]]> + + + + + Strings containing the un-parsed arguments + or empty array if commandLine was not defined.]]> + + + + + + + + + + CommandLine object + to process the parsed arguments. + + Note: If the object is created with + {@link #GenericOptionsParser(Configuration, String[])}, then returned + object will only contain parsed generic options. + + @return CommandLine representing list of arguments + parsed against Options descriptor.]]> + + + + + + + + + + + + + + + + + GenericOptionsParser is a utility to parse command line + arguments generic to the Hadoop framework. + + GenericOptionsParser recognizes several standarad command + line arguments, enabling applications to easily specify a namenode, a + jobtracker, additional configuration resources etc. + +

    Generic Options

    + +

    The supported generic options are:

    + 

    +     -conf <configuration file>     specify a configuration file
+     -D <property=value>            use value for given property
+     -fs <local|namenode:port>      specify a namenode
+     -jt <local|jobtracker:port>    specify a job tracker
+     -files <comma separated list of files>    specify comma separated
+                            files to be copied to the map reduce cluster
+     -libjars <comma separated list of jars>   specify comma separated
+                            jar files to include in the classpath.
+     -archives <comma separated list of archives>    specify comma
+             separated archives to be unarchived on the compute machines.
+
+

    + +

    The general command line syntax is:

    + 

    + bin/hadoop command [genericOptions] [commandOptions]
+

    + +

    Generic command line arguments might modify + Configuration objects, given to constructors.

    + +

    The functionality is implemented using Commons CLI.

    + +

    Examples:

    + 

    + $ bin/hadoop dfs -fs darwin:8020 -ls /data
+ list /data directory in dfs with namenode darwin:8020
+ 
+ $ bin/hadoop dfs -D fs.default.name=darwin:8020 -ls /data
+ list /data directory in dfs with namenode darwin:8020
+     
+ $ bin/hadoop dfs -conf hadoop-site.xml -ls /data
+ list /data directory in dfs with conf specified in hadoop-site.xml
+     
+ $ bin/hadoop job -D mapred.job.tracker=darwin:50020 -submit job.xml
+ submit a job to job tracker darwin:50020
+     
+ $ bin/hadoop job -jt darwin:50020 -submit job.xml
+ submit a job to job tracker darwin:50020
+     
+ $ bin/hadoop job -jt local -submit job.xml
+ submit a job to local runner
+ 
+ $ bin/hadoop jar -libjars testlib.jar 
+ -archives test.tgz -files file.txt inputjar args
+ job submission with libjars, files and archives
+

    + + @see Tool + @see ToolRunner]]> +     +     + + + + + + + + + Class<T>) of the + argument of type T. + @param The type of the argument + @param t the object to get it class + @return Class<T>]]> + + + + + + + List<T> to a an array of + T[]. + @param c the Class object of the items in the list + @param list the list to convert]]> + + + + + + List<T> to a an array of + T[]. + @param list the list to convert + @throws ArrayIndexOutOfBoundsException if the list is empty. + Use {@link #toArray(Class, List)} if the list may be empty.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + io.file.buffer.size specified in the given + Configuration. + @param in input stream + @param conf configuration + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if native-hadoop is loaded, + else false]]> + + + + + + true if native hadoop libraries, if present, can be + used for this job; false otherwise.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + { pq.top().change(); pq.adjustTop(); } + instead of 
    +  { o = pq.pop(); o.change(); pq.push(o); }
+
    ]]> +     +     + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clients and/or applications can use the provided Progressable + to explicitly report progress to the Hadoop framework. This is especially + important for operations which take an insignificant amount of time since, + in-lieu of the reported progress, the framework has to assume that an error + has occured and time-out the operation.

    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Class is to be obtained + @return the correctly typed Class of the given object.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Hadoop Pipes + or Hadoop Streaming. + + It also checks to ensure that we are running on a *nix platform else + (e.g. in Cygwin/Windows) it returns null. + @param conf configuration + @return a String[] with the ulimit command arguments or + null if we are running on a non *nix platform or + if the limit is unspecified.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Shell interface. + @param cmd shell command to execute. + @return the output of the executed command.]]> + + + + + + + + Shell interface. + @param env the map of environment key=value + @param cmd shell command to execute. + @return the output of the executed command.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + Shell can be used to run unix commands like du or + df. It also offers facilities to gate commands by + time-intervals.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ShellCommandExecutorshould be used in cases where the output + of the command needs no explicit parsing and where the command, working + directory and the environment remains unchanged. The output of the command + is stored as-is and is expected to be small.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ArrayList of string values]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + charToEscape in the string + with the escape char escapeChar + + @param str string + @param escapeChar escape char + @param charToEscape the char to be escaped + @return an escaped string]]> + + + + + + + + + + + + + + + + + + + + + + charToEscape in the string + with the escape char escapeChar + + @param str string + @param escapeChar escape char + @param charToEscape the escaped char + @return an unescaped string]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Tool, is the standard for any Map-Reduce tool/application. + The tool/application should delegate the handling of + + standard command-line options to {@link ToolRunner#run(Tool, String[])} + and only handle its custom arguments.

    + +

    Here is how a typical Tool is implemented:

    + 

    +     public class MyApp extends Configured implements Tool {
+     
+       public int run(String[] args) throws Exception {
+         // Configuration processed by ToolRunner
+         Configuration conf = getConf();
+         
+         // Create a JobConf using the processed conf
+         JobConf job = new JobConf(conf, MyApp.class);
+         
+         // Process custom command-line options
+         Path in = new Path(args[1]);
+         Path out = new Path(args[2]);
+         
+         // Specify various job-specific parameters     
+         job.setJobName("my-app");
+         job.setInputPath(in);
+         job.setOutputPath(out);
+         job.setMapperClass(MyApp.MyMapper.class);
+         job.setReducerClass(MyApp.MyReducer.class);
+
+         // Submit the job, then poll for progress until the job is complete
+         JobClient.runJob(job);
+       }
+       
+       public static void main(String[] args) throws Exception {
+         // Let ToolRunner handle generic command-line options 
+         int res = ToolRunner.run(new Configuration(), new Sort(), args);
+         
+         System.exit(res);
+       }
+     }
+

    + + @see GenericOptionsParser + @see ToolRunner]]> +     +     + + + + + + + + + + + + Tool by {@link Tool#run(String[])}, after + parsing with the given generic arguments. Uses the given + Configuration, or builds one if null. + + Sets the Tool's configuration with the possibly modified + version of the conf. + + @param conf Configuration for the Tool. + @param tool Tool to run. + @param args command-line arguments to the tool. + @return exit code of the {@link Tool#run(String[])} method.]]> + + + + + + + + Tool with its Configuration. + + Equivalent to run(tool.getConf(), tool, args). + + @param tool Tool to run. + @param args command-line arguments to the tool. + @return exit code of the {@link Tool#run(String[])} method.]]> + + + + + + + + + + ToolRunner can be used to run classes implementing + Tool interface. It works in conjunction with + {@link GenericOptionsParser} to parse the + + generic hadoop command line arguments and modifies the + Configuration of the Tool. The + application-specific options are passed along without being modified. +

    + + @see Tool + @see GenericOptionsParser]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + this filter. + @param nbHash The number of hash function to consider. + @param hashType type of the hashing function (see + {@link org.apache.hadoop.util.hash.Hash}).]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Bloom filter, as defined by Bloom in 1970. +

    + The Bloom filter is a data structure that was introduced in 1970 and that has been adopted by + the networking research community in the past decade thanks to the bandwidth efficiencies that it + offers for the transmission of set membership information between networked hosts. A sender encodes + the information into a bit vector, the Bloom filter, that is more compact than a conventional + representation. Computation and space costs for construction are linear in the number of elements. + The receiver uses the filter to test whether various elements are members of the set. Though the + filter will occasionally return a false positive, it will never return a false negative. When creating + the filter, the sender can choose its desired point in a trade-off between the false positive rate and the size. + +

    + Originally created by + European Commission One-Lab Project 034819. + + @see Filter The general behavior of a filter + + @see Space/Time Trade-Offs in Hash Coding with Allowable Errors]]> + + + + + + + + + + + + + this filter. + @param nbHash The number of hash function to consider. + @param hashType type of the hashing function (see + {@link org.apache.hadoop.util.hash.Hash}).]]> + + + + + + + + + this counting Bloom filter. +

    + Invariant: nothing happens if the specified key does not belong to this counter Bloom filter. + @param key The key to remove.]]> + + + + + + + + + + + + key -> count map. +

    NOTE: due to the bucket size of this filter, inserting the same + key more than 15 times will cause an overflow at all filter positions + associated with this key, and it will significantly increase the error + rate for this and other keys. For this reason the filter can only be + used to store small count values 0 <= N << 15. + @param key key to be tested + @return 0 if the key is not present. Otherwise, a positive value v will + be returned such that v == count with probability equal to the + error rate of this filter, and v > count otherwise. + Additionally, if the filter experienced an underflow as a result of + {@link #delete(Key)} operation, the return value may be lower than the + count with the probability of the false negative rate of such + filter.]]> + + + + + + + + + + + + + + + + + + + + + + counting Bloom filter, as defined by Fan et al. in a ToN + 2000 paper. +

    + A counting Bloom filter is an improvement to standard a Bloom filter as it + allows dynamic additions and deletions of set membership information. This + is achieved through the use of a counting vector instead of a bit vector. +

    + Originally created by + European Commission One-Lab Project 034819. + + @see Filter The general behavior of a filter + + @see Summary cache: a scalable wide-area web cache sharing protocol]]> + + + + + + + + + + + + + + Builds an empty Dynamic Bloom filter. + @param vectorSize The number of bits in the vector. + @param nbHash The number of hash function to consider. + @param hashType type of the hashing function (see + {@link org.apache.hadoop.util.hash.Hash}). + @param nr The threshold for the maximum number of keys to record in a + dynamic Bloom filter row.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + dynamic Bloom filter, as defined in the INFOCOM 2006 paper. +

    + A dynamic Bloom filter (DBF) makes use of a s * m bit matrix but + each of the s rows is a standard Bloom filter. The creation + process of a DBF is iterative. At the start, the DBF is a 1 * m + bit matrix, i.e., it is composed of a single standard Bloom filter. + It assumes that nr elements are recorded in the + initial bit vector, where nr <= n (n is + the cardinality of the set A to record in the filter). +

    + As the size of A grows during the execution of the application, + several keys must be inserted in the DBF. When inserting a key into the DBF, + one must first get an active Bloom filter in the matrix. A Bloom filter is + active when the number of recorded keys, nr, is + strictly less than the current cardinality of A, n. + If an active Bloom filter is found, the key is inserted and + nr is incremented by one. On the other hand, if there + is no active Bloom filter, a new one is created (i.e., a new row is added to + the matrix) according to the current size of A and the element + is added in this new Bloom filter and the nr value of + this new Bloom filter is set to one. A given key is said to belong to the + DBF if the k positions are set to one in one of the matrix rows. +

    + Originally created by + European Commission One-Lab Project 034819. + + @see Filter The general behavior of a filter + @see BloomFilter A Bloom filter + + @see Theory and Network Applications of Dynamic Bloom Filters]]> + + + + + + + + + + + this filter. + @param nbHash The number of hash functions to consider. + @param hashType type of the hashing function (see {@link Hash}).]]> + + + + + + this filter. + @param key The key to add.]]> + + + + + + this filter. + @param key The key to test. + @return boolean True if the specified key belongs to this filter. + False otherwise.]]> + + + + + + this filter and a specified filter. +

    + Invariant: The result is assigned to this filter. + @param filter The filter to AND with.]]> + + + + + + this filter and a specified filter. +

    + Invariant: The result is assigned to this filter. + @param filter The filter to OR with.]]> + + + + + + this filter and a specified filter. +

    + Invariant: The result is assigned to this filter. + @param filter The filter to XOR with.]]> + + + + + this filter. +

    + The result is assigned to this filter.]]> + + + + + + this filter. + @param keys The list of keys.]]> + + + + + + this filter. + @param keys The collection of keys.]]> + + + + + + this filter. + @param keys The array of keys.]]> + + + + + + + + + + + + + this filter.]]> + + + + + + + + + + + + + + + + + + + + A filter is a data structure which aims at offering a lossy summary of a set A. The + key idea is to map entries of A (also called keys) into several positions + in a vector through the use of several hash functions. +

    + Typically, a filter will be implemented as a Bloom filter (or a Bloom filter extension). +

    + It must be extended in order to define the real behavior. + + @see Key The general behavior of a key + @see HashFunction A hash function]]> + + + + + + + + + Builds a hash function that must obey to a given maximum number of returned values and a highest value. + @param maxValue The maximum highest returned value. + @param nbHash The number of resulting hashed values. + @param hashType type of the hashing function (see {@link Hash}).]]> + + + + + this hash function. A NOOP]]> + + + + + + + + + + + + + + + + + + + + + + + + + Builds a key with a default weight. + @param value The byte value of this key.]]> + + + + + + Builds a key with a specified weight. + @param value The value of this key. + @param weight The weight associated to this key.]]> + + + + + + + + + + + + this key.]]> + + + + + this key.]]> + + + + + + this key with a specified value. + @param weight The increment.]]> + + + + + this key by one.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The idea is to randomly select a bit to reset.]]> + + + + + + The idea is to select the bit to reset that will generate the minimum + number of false negative.]]> + + + + + + The idea is to select the bit to reset that will remove the maximum number + of false positive.]]> + + + + + + The idea is to select the bit to reset that will, at the same time, remove + the maximum number of false positve while minimizing the amount of false + negative generated.]]> + + + + + Originally created by + European Commission One-Lab Project 034819.]]> + + + + + + + + + + + + + + this filter. + @param nbHash The number of hash function to consider. + @param hashType type of the hashing function (see + {@link org.apache.hadoop.util.hash.Hash}).]]> + + + + + + + + + this retouched Bloom filter. +

    + Invariant: if the false positive is null, nothing happens. + @param key The false positive key to add.]]> + + + + + + this retouched Bloom filter. + @param coll The collection of false positive.]]> + + + + + + this retouched Bloom filter. + @param keys The list of false positive.]]> + + + + + + this retouched Bloom filter. + @param keys The array of false positive.]]> + + + + + + + this retouched Bloom filter. + @param scheme The selective clearing scheme to apply.]]> + + + + + + + + + + + + retouched Bloom filter, as defined in the CoNEXT 2006 paper. +

    + It allows the removal of selected false positives at the cost of introducing + random false negatives, and with the benefit of eliminating some random false + positives at the same time. + +

    + Originally created by + European Commission One-Lab Project 034819. + + @see Filter The general behavior of a filter + @see BloomFilter A Bloom filter + @see RemoveScheme The different selective clearing algorithms + + @see Retouched Bloom Filters: Allowing Networked Applications to Trade Off Selected False Positives Against False Negatives]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + length, and + the provided seed value + @param bytes input bytes + @param length length of the valid bytes to consider + @param initval seed value + @return hash value]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The best hash table sizes are powers of 2. There is no need to do mod + a prime (mod is sooo slow!). If you need less than 32 bits, use a bitmask. + For example, if you need only 10 bits, do + h = (h & hashmask(10)); + In which case, the hash table should have hashsize(10) elements. + +

    If you are hashing n strings byte[][] k, do it like this: + for (int i = 0, h = 0; i < n; ++i) h = hash( k[i], h); + +

    By Bob Jenkins, 2006. bob_jenkins@burtleburtle.net. You may use this + code any way you wish, private, educational, or commercial. It's free. + +

    Use for hash table lookup, or anything where one collision in 2^^32 is + acceptable. Do NOT use for cryptographic purposes.]]> + + + + + + + + + + + lookup3.c, by Bob Jenkins, May 2006, Public Domain. + + You can use this free for any purpose. It's in the public domain. + It has no warranty. + + + @see lookup3.c + @see Hash Functions (and how this + function compares to others such as CRC, MD?, etc + @see Has update on the + Dr. Dobbs Article]]> + + + + + + + + + + + + + + + + The C version of MurmurHash 2.0 found at that site was ported + to Java by Andrzej Bialecki (ab at getopt org).

    ]]> +     +     + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + JobTracker, + as {@link JobTracker.State} + + @return the current state of the JobTracker.]]> + + + + + JobTracker + + @return the size of heap memory used by the JobTracker]]> + + + + + JobTracker + + @return the configured size of max heap memory that can be used by the JobTracker]]> + + + + + + + + + + + + ClusterStatus provides clients with information such as: +
      +
    1. + Size of the cluster. +
      2. +
    2. + Name of the trackers. +
      3. +
    3. + Task capacity of the cluster. +
      4. +
    4. + The number of currently running map & reduce tasks. +
      5. +
    5. + State of the JobTracker. +
      6. +

    + +

    Clients can query for the latest ClusterStatus, via + {@link JobClient#getClusterStatus()}.

    + + @see JobClient]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Counters represent global counters, defined either by the + Map-Reduce framework or applications. Each Counter can be of + any {@link Enum} type.

    + +

    Counters are bunched into {@link Group}s, each comprising of + counters from a particular Enum class. + @deprecated Use {@link org.apache.hadoop.mapreduce.Counters} instead.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Group of counters, comprising of counters from a particular + counter {@link Enum} class. + +

    Grouphandles localization of the class name and the + counter names.

    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + FileInputFormat implementations can override this and return + false to ensure that individual input files are never split-up + so that {@link Mapper}s process entire files. + + @param fs the file system that the file is on + @param filename the file name to check + @return is this file splitable?]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + FileInputFormat is the base class for all file-based + InputFormats. This provides a generic implementation of + {@link #getSplits(JobConf, int)}. + Subclasses of FileInputFormat can also override the + {@link #isSplitable(FileSystem, Path)} method to ensure input-files are + not split-up and are processed as a whole by {@link Mapper}s. + @deprecated Use {@link org.apache.hadoop.mapreduce.lib.input.FileInputFormat} + instead.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if the job output should be compressed, + false otherwise]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Tasks' Side-Effect Files + +

    Note: The following is valid only if the {@link OutputCommitter} + is {@link FileOutputCommitter}. If OutputCommitter is not + a FileOutputCommitter, the task's temporary output + directory is same as {@link #getOutputPath(JobConf)} i.e. + ${mapred.output.dir}$

    + +

    Some applications need to create/write-to side-files, which differ from + the actual job-outputs. + +

    In such cases there could be issues with 2 instances of the same TIP + (running simultaneously e.g. speculative tasks) trying to open/write-to the + same file (path) on HDFS. Hence the application-writer will have to pick + unique names per task-attempt (e.g. using the attemptid, say + attempt_200709221812_0001_m_000000_0), not just per TIP.

    + +

    To get around this the Map-Reduce framework helps the application-writer + out by maintaining a special + ${mapred.output.dir}/_temporary/_${taskid} + sub-directory for each task-attempt on HDFS where the output of the + task-attempt goes. On successful completion of the task-attempt the files + in the ${mapred.output.dir}/_temporary/_${taskid} (only) + are promoted to ${mapred.output.dir}. Of course, the + framework discards the sub-directory of unsuccessful task-attempts. This + is completely transparent to the application.

    + +

    The application-writer can take advantage of this by creating any + side-files required in ${mapred.work.output.dir} during execution + of his reduce-task i.e. via {@link #getWorkOutputPath(JobConf)}, and the + framework will move them out similarly - thus she doesn't have to pick + unique paths per task-attempt.

    + +

    Note: the value of ${mapred.work.output.dir} during + execution of a particular task-attempt is actually + ${mapred.output.dir}/_temporary/_{$taskid}, and this value is + set by the map-reduce framework. So, just create any side-files in the + path returned by {@link #getWorkOutputPath(JobConf)} from map/reduce + task to take advantage of this feature.

    + +

    The entire discussion holds true for maps of jobs with + reducer=NONE (i.e. 0 reduces) since output of the map, in that case, + goes directly to HDFS.

    + + @return the {@link Path} to the task's temporary output directory + for the map-reduce job.]]> +     +     + + + + + + + + + + + + + The generated name can be used to create custom files from within the + different tasks for the job, the names for different tasks will not collide + with each other.

    + +

    The given name is postfixed with the task type, 'm' for maps, 'r' for + reduces and the task partition number. For example, give a name 'test' + running on the first map o the job the generated name will be + 'test-m-00000'.

    + + @param conf the configuration for the job. + @param name the name to make unique. + @return a unique name accross all tasks of the job.]]> +     +     + + + + + The path can be used to create custom files from within the map and + reduce tasks. The path name will be unique for each task. The path parent + will be the job output directory.

    ls + +

    This method uses the {@link #getUniqueName} method to make the file name + unique for the task.

    + + @param conf the configuration for the job. + @param name the name for the file. + @return a unique path accross all tasks of the job.]]> +     +     + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Each {@link InputSplit} is then assigned to an individual {@link Mapper} + for processing.

    + +

    Note: The split is a logical split of the inputs and the + input files are not physically split into chunks. For e.g. a split could + be <input-file-path, start, offset> tuple. + + @param job job configuration. + @param numSplits the desired number of splits, a hint. + @return an array of {@link InputSplit}s for the job.]]> + + + + + + + + + It is the responsibility of the RecordReader to respect + record boundaries while processing the logical split to present a + record-oriented view to the individual task.

    + + @param split the {@link InputSplit} + @param job the job that this split belongs to + @return a {@link RecordReader}]]> +     +     + + InputFormat describes the input-specification for a + Map-Reduce job. + +

    The Map-Reduce framework relies on the InputFormat of the + job to:

    +

      +
    1. + Validate the input-specification of the job. +
    2. + Split-up the input file(s) into logical {@link InputSplit}s, each of + which is then assigned to an individual {@link Mapper}. +
      3. +
    3. + Provide the {@link RecordReader} implementation to be used to glean + input records from the logical InputSplit for processing by + the {@link Mapper}. +
      4. +
    + +

    The default behavior of file-based {@link InputFormat}s, typically + sub-classes of {@link FileInputFormat}, is to split the + input into logical {@link InputSplit}s based on the total size, in + bytes, of the input files. However, the {@link FileSystem} blocksize of + the input files is treated as an upper bound for input splits. A lower bound + on the split size can be set via + + mapred.min.split.size.

    + +

    Clearly, logical splits based on input-size is insufficient for many + applications since record boundaries are to respected. In such cases, the + application has to also implement a {@link RecordReader} on whom lies the + responsibilty to respect record-boundaries and present a record-oriented + view of the logical InputSplit to the individual task. + + @see InputSplit + @see RecordReader + @see JobClient + @see FileInputFormat + @deprecated Use {@link org.apache.hadoop.mapreduce.InputFormat} instead.]]> + + + + + + + + + + InputSplit. + + @return the number of bytes in the input split. + @throws IOException]]> + + + + + + InputSplit is + located as an array of Strings. + @throws IOException]]> + + + + InputSplit represents the data to be processed by an + individual {@link Mapper}. + +

    Typically, it presents a byte-oriented view on the input and is the + responsibility of {@link RecordReader} of the job to process this and present + a record-oriented view. + + @see InputFormat + @see RecordReader + @deprecated Use {@link org.apache.hadoop.mapreduce.InputSplit} instead.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + JobClient.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + jobid doesn't correspond to any known job. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + JobClient is the primary interface for the user-job to interact + with the {@link JobTracker}. + + JobClient provides facilities to submit jobs, track their + progress, access component-tasks' reports/logs, get the Map-Reduce cluster + status information etc. + +

    The job submission process involves: +

      +
    1. + Checking the input and output specifications of the job. +
      2. +
    2. + Computing the {@link InputSplit}s for the job. +
      3. +
    3. + Setup the requisite accounting information for the {@link DistributedCache} + of the job, if necessary. +
      4. +
    4. + Copying the job's jar and configuration to the map-reduce system directory + on the distributed file-system. +
      5. +
    5. + Submitting the job to the JobTracker and optionally monitoring + it's status. +
      6. +

    + + Normally the user creates the application, describes various facets of the + job via {@link JobConf} and then uses the JobClient to submit + the job and monitor its progress. + +

    Here is an example on how to use JobClient:

    + 

    +     // Create a new JobConf
+     JobConf job = new JobConf(new Configuration(), MyJob.class);
+     
+     // Specify various job-specific parameters     
+     job.setJobName("myjob");
+     
+     job.setInputPath(new Path("in"));
+     job.setOutputPath(new Path("out"));
+     
+     job.setMapperClass(MyJob.MyMapper.class);
+     job.setReducerClass(MyJob.MyReducer.class);
+
+     // Submit the job, then poll for progress until the job is complete
+     JobClient.runJob(job);
+

    + +

    Job Control

    + +

    At times clients would chain map-reduce jobs to accomplish complex tasks + which cannot be done via a single map-reduce job. This is fairly easy since + the output of the job, typically, goes to distributed file-system and that + can be used as the input for the next job.

    + +

    However, this also means that the onus on ensuring jobs are complete + (success/failure) lies squarely on the clients. In such situations the + various job-control options are: +

      +
    1. + {@link #runJob(JobConf)} : submits the job and returns only after + the job has completed. +
      2. +
    2. + {@link #submitJob(JobConf)} : only submits the job, then poll the + returned handle to the {@link RunningJob} to query status and make + scheduling decisions. +
      3. +
    3. + {@link JobConf#setJobEndNotificationURI(String)} : setup a notification + on job-completion, thus avoiding polling. +
      4. +

    + + @see JobConf + @see ClusterStatus + @see Tool + @see DistributedCache]]> +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + If the parameter {@code loadDefaults} is false, the new instance + will not load resources from the default files. + + @param loadDefaults specifies whether to load from the default files]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if framework should keep the intermediate files + for failed tasks, false otherwise.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if the outputs of the maps are to be compressed, + false otherwise.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This comparator should be provided if the equivalence rules for keys + for sorting the intermediates are different from those for grouping keys + before each call to + {@link Reducer#reduce(Object, java.util.Iterator, OutputCollector, Reporter)}.

    + +

    For key-value pairs (K1,V1) and (K2,V2), the values (V1, V2) are passed + in a single call to the reduce function if K1 and K2 compare as equal.

    + +

    Since {@link #setOutputKeyComparatorClass(Class)} can be used to control + how keys are sorted, this can be used in conjunction to simulate + secondary sort on values.

    + +

    Note: This is not a guarantee of the reduce sort being + stable in any sense. (In any case, with the order of available + map-outputs to the reduce being non-deterministic, it wouldn't make + that much sense.)

    + + @param theClass the comparator class to be used for grouping keys. + It should implement RawComparator. + @see #setOutputKeyComparatorClass(Class)]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + combiner class used to combine map-outputs + before being sent to the reducers. Typically the combiner is same as the + the {@link Reducer} for the job i.e. {@link #getReducerClass()}. + + @return the user-defined combiner class used to combine map-outputs.]]> + + + + + + combiner class used to combine map-outputs + before being sent to the reducers. + +

    The combiner is an application-specified aggregation operation, which + can help cut down the amount of data transferred between the + {@link Mapper} and the {@link Reducer}, leading to better performance.

    + +

    The framework may invoke the combiner 0, 1, or multiple times, in both + the mapper and reducer tasks. In general, the combiner is called as the + sort/merge result is written to disk. The combiner must: +

      +
    • be side-effect free
      • +
    • have the same input and output key types and the same input and + output value types
      • +

    + +

    Typically the combiner is same as the Reducer for the + job i.e. {@link #setReducerClass(Class)}.

    + + @param theClass the user-defined combiner class used to combine + map-outputs.]]> +     +     + + + true. + + @return true if speculative execution be used for this job, + false otherwise.]]> + + + + + + true if speculative execution + should be turned on, else false.]]> + + + + + true. + + @return true if speculative execution be + used for this job for map tasks, + false otherwise.]]> + + + + + + true if speculative execution + should be turned on for map tasks, + else false.]]> + + + + + true. + + @return true if speculative execution be used + for reduce tasks for this job, + false otherwise.]]> + + + + + + true if speculative execution + should be turned on for reduce tasks, + else false.]]> + + + + + 1. + + @return the number of reduce tasks for this job.]]> + + + + + + Note: This is only a hint to the framework. The actual + number of spawned map tasks depends on the number of {@link InputSplit}s + generated by the job's {@link InputFormat#getSplits(JobConf, int)}. + + A custom {@link InputFormat} is typically used to accurately control + the number of map tasks for the job.

    + +

    How many maps?

    + +

    The number of maps is usually driven by the total size of the inputs + i.e. total number of blocks of the input files.

    + +

    The right level of parallelism for maps seems to be around 10-100 maps + per-node, although it has been set up to 300 or so for very cpu-light map + tasks. Task setup takes awhile, so it is best if the maps take at least a + minute to execute.

    + +

    The default behavior of file-based {@link InputFormat}s is to split the + input into logical {@link InputSplit}s based on the total size, in + bytes, of input files. However, the {@link FileSystem} blocksize of the + input files is treated as an upper bound for input splits. A lower bound + on the split size can be set via + + mapred.min.split.size.

    + +

    Thus, if you expect 10TB of input data and have a blocksize of 128MB, + you'll end up with 82,000 maps, unless {@link #setNumMapTasks(int)} is + used to set it even higher.

    + + @param n the number of map tasks for this job. + @see InputFormat#getSplits(JobConf, int) + @see FileInputFormat + @see FileSystem#getDefaultBlockSize() + @see FileStatus#getBlockSize()]]> +     +     + + + 1. + + @return the number of reduce tasks for this job.]]> + + + + + + How many reduces? + +

    The right number of reduces seems to be 0.95 or + 1.75 multiplied by (<no. of nodes> * + + mapred.tasktracker.reduce.tasks.maximum). +

    + +

    With 0.95 all of the reduces can launch immediately and + start transfering map outputs as the maps finish. With 1.75 + the faster nodes will finish their first round of reduces and launch a + second wave of reduces doing a much better job of load balancing.

    + +

    Increasing the number of reduces increases the framework overhead, but + increases load balancing and lowers the cost of failures.

    + +

    The scaling factors above are slightly less than whole numbers to + reserve a few reduce slots in the framework for speculative-tasks, failures + etc.

    + +

    Reducer NONE

    + +

    It is legal to set the number of reduce-tasks to zero.

    + +

    In this case the output of the map-tasks directly go to distributed + file-system, to the path set by + {@link FileOutputFormat#setOutputPath(JobConf, Path)}. Also, the + framework doesn't sort the map-outputs before writing it out to HDFS.

    + + @param n the number of reduce tasks for this job.]]> +     +     + + + mapred.map.max.attempts + property. If this property is not already set, the default is 4 attempts. + + @return the max number of attempts per map task.]]> + + + + + + + + + + + mapred.reduce.max.attempts + property. If this property is not already set, the default is 4 attempts. + + @return the max number of attempts per reduce task.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + noFailures, the + tasktracker is blacklisted for this job. + + @param noFailures maximum no. of failures of a given job per tasktracker.]]> + + + + + blacklisted for this job. + + @return the maximum no. of failures of a given job per tasktracker.]]> + + + + + failed. + + Defaults to zero, i.e. any failed map-task results in + the job being declared as {@link JobStatus#FAILED}. + + @return the maximum percentage of map tasks that can fail without + the job being aborted.]]> + + + + + + failed. + + @param percent the maximum percentage of map tasks that can fail without + the job being aborted.]]> + + + + + failed. + + Defaults to zero, i.e. any failed reduce-task results + in the job being declared as {@link JobStatus#FAILED}. + + @return the maximum percentage of reduce tasks that can fail without + the job being aborted.]]> + + + + + + failed. + + @param percent the maximum percentage of reduce tasks that can fail without + the job being aborted.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The debug script can aid debugging of failed map tasks. The script is + given task's stdout, stderr, syslog, jobconf files as arguments.

    + +

    The debug command, run on the node where the map failed, is:

    + 

     
+ $script $stdout $stderr $syslog $jobconf.
+

    + +

    The script file is distributed through {@link DistributedCache} + APIs. The script needs to be symlinked.

    + +

    Here is an example on how to submit a script + 

    + job.setMapDebugScript("./myscript");
+ DistributedCache.createSymlink(job);
+ DistributedCache.addCacheFile("/debug/scripts/myscript#myscript");
+

    + + @param mDbgScript the script name]]> +     +     + + + + + + + + + The debug script can aid debugging of failed reduce tasks. The script + is given task's stdout, stderr, syslog, jobconf files as arguments.

    + +

    The debug command, run on the node where the map failed, is:

    + 

     
+ $script $stdout $stderr $syslog $jobconf.
+

    + +

    The script file is distributed through {@link DistributedCache} + APIs. The script file needs to be symlinked

    + +

    Here is an example on how to submit a script + 

    + job.setReduceDebugScript("./myscript");
+ DistributedCache.createSymlink(job);
+ DistributedCache.addCacheFile("/debug/scripts/myscript#myscript");
+

    + + @param rDbgScript the script name]]> +     +     + + + + + + + + null if it hasn't + been set. + @see #setJobEndNotificationURI(String)]]> + + + + + + The uri can contain 2 special parameters: $jobId and + $jobStatus. Those, if present, are replaced by the job's + identifier and completion-status respectively.

    + +

    This is typically used by application-writers to implement chaining of + Map-Reduce jobs in an asynchronous manner.

    + + @param uri the job end notification uri + @see JobStatus + @see Job Completion and Chaining]]> +     +     + + + + When a job starts, a shared directory is created at location + + ${mapred.local.dir}/taskTracker/jobcache/$jobid/work/ . + This directory is exposed to the users through + job.local.dir . + So, the tasks can use this space + as scratch space and share files among them.

    + This value is available as System property also. + + @return The localized job specific shared directory]]> +     +     + + + + For backward compatibility, if the job configuration sets the + key {@link #MAPRED_TASK_MAXVMEM_PROPERTY} to a value different + from {@link #DISABLED_MEMORY_LIMIT}, that value will be used + after converting it from bytes to MB. + @return memory required to run a map task of the job, in MB, + or {@link #DISABLED_MEMORY_LIMIT} if unset.]]> + + + + + + + + + For backward compatibility, if the job configuration sets the + key {@link #MAPRED_TASK_MAXVMEM_PROPERTY} to a value different + from {@link #DISABLED_MEMORY_LIMIT}, that value will be used + after converting it from bytes to MB. + @return memory required to run a reduce task of the job, in MB, + or {@link #DISABLED_MEMORY_LIMIT} if unset.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + This method is deprecated. Now, different memory limits can be + set for map and reduce tasks of a job, in MB. +

    + For backward compatibility, if the job configuration sets the + key {@link #MAPRED_TASK_MAXVMEM_PROPERTY} to a value different + from {@link #DISABLED_MEMORY_LIMIT}, that value is returned. + Otherwise, this method will return the larger of the values returned by + {@link #getMemoryForMapTask()} and {@link #getMemoryForReduceTask()} + after converting them into bytes. + + @return Memory required to run a task of this job, in bytes, + or {@link #DISABLED_MEMORY_LIMIT}, if unset. + @see #setMaxVirtualMemoryForTask(long) + @deprecated Use {@link #getMemoryForMapTask()} and + {@link #getMemoryForReduceTask()}]]> + + + + + + + mapred.task.maxvmem is split into + mapred.job.map.memory.mb + and mapred.job.map.memory.mb,mapred + each of the new key are set + as mapred.task.maxvmem / 1024 + as new values are in MB + + @param vmem Maximum amount of virtual memory in bytes any task of this job + can use. + @see #getMaxVirtualMemoryForTask() + @deprecated + Use {@link #setMemoryForMapTask(long mem)} and + Use {@link #setMemoryForReduceTask(long mem)}]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + JobConf is the primary interface for a user to describe a + map-reduce job to the Hadoop framework for execution. The framework tries to + faithfully execute the job as-is described by JobConf, however: +

      +
    1. + Some configuration parameters might have been marked as + + final by administrators and hence cannot be altered. +
      2. +
    2. + While some job parameters are straight-forward to set + (e.g. {@link #setNumReduceTasks(int)}), some parameters interact subtly + rest of the framework and/or job-configuration and is relatively more + complex for the user to control finely (e.g. {@link #setNumMapTasks(int)}). +
      3. +

    + +

    JobConf typically specifies the {@link Mapper}, combiner + (if any), {@link Partitioner}, {@link Reducer}, {@link InputFormat} and + {@link OutputFormat} implementations to be used etc. + +

    Optionally JobConf is used to specify other advanced facets + of the job such as Comparators to be used, files to be put in + the {@link DistributedCache}, whether or not intermediate and/or job outputs + are to be compressed (and how), debugability via user-provided scripts + ( {@link #setMapDebugScript(String)}/{@link #setReduceDebugScript(String)}), + for doing post-processing on task logs, task's stdout, stderr, syslog. + and etc.

    + +

    Here is an example on how to configure a job via JobConf:

    + 

    +     // Create a new JobConf
+     JobConf job = new JobConf(new Configuration(), MyJob.class);
+     
+     // Specify various job-specific parameters     
+     job.setJobName("myjob");
+     
+     FileInputFormat.setInputPaths(job, new Path("in"));
+     FileOutputFormat.setOutputPath(job, new Path("out"));
+     
+     job.setMapperClass(MyJob.MyMapper.class);
+     job.setCombinerClass(MyJob.MyReducer.class);
+     job.setReducerClass(MyJob.MyReducer.class);
+     
+     job.setInputFormat(SequenceFileInputFormat.class);
+     job.setOutputFormat(SequenceFileOutputFormat.class);
+

    + + @see JobClient + @see ClusterStatus + @see Tool + @see DistributedCache + @deprecated Use {@link Configuration} instead]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + .]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + any job + run on the jobtracker started at 200707121733, we would use : + 
     
+ JobID.getTaskIDsPattern("200707121733", null);
+
    + which will return : + 
     "job_200707121733_[0-9]*"
    + @param jtIdentifier jobTracker identifier, or null + @param jobId job number, or null + @return a regex pattern matching JobIDs]]> +     +     + + + An example JobID is : + job_200707121733_0003 , which represents the third job + running at the jobtracker started at 200707121733. +

    + Applications should never construct or parse JobID strings, but rather + use appropriate constructors or {@link #forName(String)} method. + + @see TaskID + @see TaskAttemptID]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + "N/A" + + @return Scheduling information associated to particular Job Queue]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + zero. + + @param conf configuration for the JobTracker. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Output pairs need not be of the same types as input pairs. A given + input pair may map to zero or many output pairs. Output pairs are + collected with calls to + {@link OutputCollector#collect(Object,Object)}.

    + +

    Applications can use the {@link Reporter} provided to report progress + or just indicate that they are alive. In scenarios where the application + takes an insignificant amount of time to process individual key/value + pairs, this is crucial since the framework might assume that the task has + timed-out and kill that task. The other way of avoiding this is to set + + mapred.task.timeout to a high-enough value (or even zero for no + time-outs).

    + + @param key the input key. + @param value the input value. + @param output collects mapped keys and values. + @param reporter facility to report progress.]]> +     + + + Maps are the individual tasks which transform input records into a + intermediate records. The transformed intermediate records need not be of + the same type as the input records. A given input pair may map to zero or + many output pairs.

    + +

    The Hadoop Map-Reduce framework spawns one map task for each + {@link InputSplit} generated by the {@link InputFormat} for the job. + Mapper implementations can access the {@link JobConf} for the + job via the {@link JobConfigurable#configure(JobConf)} and initialize + themselves. Similarly they can use the {@link Closeable#close()} method for + de-initialization.

    + +

    The framework then calls + {@link #map(Object, Object, OutputCollector, Reporter)} + for each key/value pair in the InputSplit for that task.

    + +

    All intermediate values associated with a given output key are + subsequently grouped by the framework, and passed to a {@link Reducer} to + determine the final output. Users can control the grouping by specifying + a Comparator via + {@link JobConf#setOutputKeyComparatorClass(Class)}.

    + +

    The grouped Mapper outputs are partitioned per + Reducer. Users can control which keys (and hence records) go to + which Reducer by implementing a custom {@link Partitioner}. + +

    Users can optionally specify a combiner, via + {@link JobConf#setCombinerClass(Class)}, to perform local aggregation of the + intermediate outputs, which helps to cut down the amount of data transferred + from the Mapper to the Reducer. + +

    The intermediate, grouped outputs are always stored in + {@link SequenceFile}s. Applications can specify if and how the intermediate + outputs are to be compressed and which {@link CompressionCodec}s are to be + used via the JobConf.

    + +

    If the job has + zero + reduces then the output of the Mapper is directly written + to the {@link FileSystem} without grouping by keys.

    + +

    Example:

    + 

    +     public class MyMapper<K extends WritableComparable, V extends Writable> 
+     extends MapReduceBase implements Mapper<K, V, K, V> {
+     
+       static enum MyCounters { NUM_RECORDS }
+       
+       private String mapTaskId;
+       private String inputFile;
+       private int noRecords = 0;
+       
+       public void configure(JobConf job) {
+         mapTaskId = job.get("mapred.task.id");
+         inputFile = job.get("map.input.file");
+       }
+       
+       public void map(K key, V val,
+                       OutputCollector<K, V> output, Reporter reporter)
+       throws IOException {
+         // Process the <key, value> pair (assume this takes a while)
+         // ...
+         // ...
+         
+         // Let the framework know that we are alive, and kicking!
+         // reporter.progress();
+         
+         // Process some more
+         // ...
+         // ...
+         
+         // Increment the no. of <key, value> pairs processed
+         ++noRecords;
+
+         // Increment counters
+         reporter.incrCounter(NUM_RECORDS, 1);
+        
+         // Every 100 records update application-level status
+         if ((noRecords%100) == 0) {
+           reporter.setStatus(mapTaskId + " processed " + noRecords + 
+                              " from input-file: " + inputFile); 
+         }
+         
+         // Output the result
+         output.collect(key, val);
+       }
+     }
+

    + +

    Applications may write a custom {@link MapRunnable} to exert greater + control on map processing e.g. multi-threaded Mappers etc.

    + + @see JobConf + @see InputFormat + @see Partitioner + @see Reducer + @see MapReduceBase + @see MapRunnable + @see SequenceFile + @deprecated Use {@link org.apache.hadoop.mapreduce.Mapper} instead.]]> +     +     + + + + + + + + + + + + + + + + + + + + + Provides default no-op implementations for a few methods, most non-trivial + applications need to override some of them.

    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + <key, value> pairs. + +

    Mapping of input records to output records is complete when this method + returns.

    + + @param input the {@link RecordReader} to read the input records. + @param output the {@link OutputCollector} to collect the outputrecords. + @param reporter {@link Reporter} to report progress, status-updates etc. + @throws IOException]]> +     +     + + Custom implementations of MapRunnable can exert greater + control on map processing e.g. multi-threaded, asynchronous mappers etc.

    + + @see Mapper + @deprecated Use {@link org.apache.hadoop.mapreduce.Mapper} instead.]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + nearly + equal content length.
    + Subclasses implement {@link #getRecordReader(InputSplit, JobConf, Reporter)} + to construct RecordReader's for MultiFileSplit's. + @see MultiFileSplit + @deprecated Use {@link org.apache.hadoop.mapred.lib.CombineFileInputFormat} instead]]> +     +     + + + + + + + + + + + + + MultiFileSplit can be used to implement {@link RecordReader}'s, with + reading one record per file. + @see FileSplit + @see MultiFileInputFormat + @deprecated Use {@link org.apache.hadoop.mapred.lib.CombineFileSplit} instead]]> + + + + + + + + + + + + + + + <key, value> pairs output by {@link Mapper}s + and {@link Reducer}s. + +

    OutputCollector is the generalization of the facility + provided by the Map-Reduce framework to collect data output by either the + Mapper or the Reducer i.e. intermediate outputs + or the output of the job.

    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + OutputCommitter describes the commit of task output for a + Map-Reduce job. + +

    The Map-Reduce framework relies on the OutputCommitter of + the job to:

    +

      +
    1. + Setup the job during initialization. For example, create the temporary + output directory for the job during the initialization of the job. +
      2. +
    2. + Cleanup the job after the job completion. For example, remove the + temporary output directory after the job completion. +
      3. +
    3. + Setup the task temporary output. +
      4. +
    4. + Check whether a task needs a commit. This is to avoid the commit + procedure if a task does not need commit. +
      5. +
    5. + Commit of the task output. +
      6. +
    6. + Discard the task commit. +
      7. +
    + + @see FileOutputCommitter + @see JobContext + @see TaskAttemptContext + @deprecated Use {@link org.apache.hadoop.mapreduce.OutputCommitter} instead.]]> +     +     + + + + + + + + + + + + + + + + + + + This is to validate the output specification for the job when it is + a job is submitted. Typically checks that it does not already exist, + throwing an exception when it already exists, so that output is not + overwritten.

    + + @param ignored + @param job job configuration. + @throws IOException when output should not be attempted]]> +     +     + + OutputFormat describes the output-specification for a + Map-Reduce job. + +

    The Map-Reduce framework relies on the OutputFormat of the + job to:

    +

      +
    1. + Validate the output-specification of the job. For e.g. check that the + output directory doesn't already exist. +
    2. + Provide the {@link RecordWriter} implementation to be used to write out + the output files of the job. Output files are stored in a + {@link FileSystem}. +
      3. +
    + + @see RecordWriter + @see JobConf + @deprecated Use {@link org.apache.hadoop.mapreduce.OutputFormat} instead.]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + Typically a hash function on a all or a subset of the key.

    + + @param key the key to be paritioned. + @param value the entry value. + @param numPartitions the total number of partitions. + @return the partition number for the key.]]> +     +     + + Partitioner controls the partitioning of the keys of the + intermediate map-outputs. The key (or a subset of the key) is used to derive + the partition, typically by a hash function. The total number of partitions + is the same as the number of reduce tasks for the job. Hence this controls + which of the m reduce tasks the intermediate key (and hence the + record) is sent for reduction.

    + + @see Reducer + @deprecated Use {@link org.apache.hadoop.mapreduce.Partitioner} instead.]]> +     +     + + + + + + + + + + + + + + + + + + + true if there exists a key/value, + false otherwise. + @throws IOException]]> + + + + + + + + + + + + + + + RawKeyValueIterator is an iterator used to iterate over + the raw keys and values during sort/merge of intermediate data.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 0.0 to 1.0. + @throws IOException]]> + + + + RecordReader reads <key, value> pairs from an + {@link InputSplit}. + +

    RecordReader, typically, converts the byte-oriented view of + the input, provided by the InputSplit, and presents a + record-oriented view for the {@link Mapper} & {@link Reducer} tasks for + processing. It thus assumes the responsibility of processing record + boundaries and presenting the tasks with keys and values.

    + + @see InputSplit + @see InputFormat]]> +     +     + + + + + + + + + + + + + + + + RecordWriter to future operations. + + @param reporter facility to report progress. + @throws IOException]]> + + + + RecordWriter writes the output <key, value> pairs + to an output file. + +

    RecordWriter implementations write the job outputs to the + {@link FileSystem}. + + @see OutputFormat]]> + + + + + + + + + + + + + + + Reduces values for a given key. + +

    The framework calls this method for each + <key, (list of values)> pair in the grouped inputs. + Output values must be of the same type as input values. Input keys must + not be altered. The framework will reuse the key and value objects + that are passed into the reduce, therefore the application should clone + the objects they want to keep a copy of. In many cases, all values are + combined into zero or one value. +

    + +

    Output pairs are collected with calls to + {@link OutputCollector#collect(Object,Object)}.

    + +

    Applications can use the {@link Reporter} provided to report progress + or just indicate that they are alive. In scenarios where the application + takes an insignificant amount of time to process individual key/value + pairs, this is crucial since the framework might assume that the task has + timed-out and kill that task. The other way of avoiding this is to set + + mapred.task.timeout to a high-enough value (or even zero for no + time-outs).

    + + @param key the key. + @param values the list of values to reduce. + @param output to collect keys and combined values. + @param reporter facility to report progress.]]> +     + + + The number of Reducers for the job is set by the user via + {@link JobConf#setNumReduceTasks(int)}. Reducer implementations + can access the {@link JobConf} for the job via the + {@link JobConfigurable#configure(JobConf)} method and initialize themselves. + Similarly they can use the {@link Closeable#close()} method for + de-initialization.

    + +

    Reducer has 3 primary phases:

    +
      +
    1. + +

      Shuffle

      + +

      Reducer is input the grouped output of a {@link Mapper}. + In the phase the framework, for each Reducer, fetches the + relevant partition of the output of all the Mappers, via HTTP. +

      +
      2. + +
    2. +

      Sort

      + +

      The framework groups Reducer inputs by keys + (since different Mappers may have output the same key) in this + stage.

      + +

      The shuffle and sort phases occur simultaneously i.e. while outputs are + being fetched they are merged.

      + +
      SecondarySort
      + +

      If equivalence rules for keys while grouping the intermediates are + different from those for grouping keys before reduction, then one may + specify a Comparator via + {@link JobConf#setOutputValueGroupingComparator(Class)}.Since + {@link JobConf#setOutputKeyComparatorClass(Class)} can be used to + control how intermediate keys are grouped, these can be used in conjunction + to simulate secondary sort on values.

      + + + For example, say that you want to find duplicate web pages and tag them + all with the url of the "best" known example. You would set up the job + like: +
        +
      • Map Input Key: url
        • +
      • Map Input Value: document
        • +
      • Map Output Key: document checksum, url pagerank
        • +
      • Map Output Value: url
        • +
      • Partitioner: by checksum
        • +
      • OutputKeyComparator: by checksum and then decreasing pagerank
        • +
      • OutputValueGroupingComparator: by checksum
        • +
      +
      3. + +
    3. +

      Reduce

      + +

      In this phase the + {@link #reduce(Object, Iterator, OutputCollector, Reporter)} + method is called for each <key, (list of values)> pair in + the grouped inputs.

      +

      The output of the reduce task is typically written to the + {@link FileSystem} via + {@link OutputCollector#collect(Object, Object)}.

      +
      4. +
    + +

    The output of the Reducer is not re-sorted.

    + +

    Example:

    + 

    +     public class MyReducer<K extends WritableComparable, V extends Writable> 
+     extends MapReduceBase implements Reducer<K, V, K, V> {
+     
+       static enum MyCounters { NUM_RECORDS }
+        
+       private String reduceTaskId;
+       private int noKeys = 0;
+       
+       public void configure(JobConf job) {
+         reduceTaskId = job.get("mapred.task.id");
+       }
+       
+       public void reduce(K key, Iterator<V> values,
+                          OutputCollector<K, V> output, 
+                          Reporter reporter)
+       throws IOException {
+       
+         // Process
+         int noValues = 0;
+         while (values.hasNext()) {
+           V value = values.next();
+           
+           // Increment the no. of values for this key
+           ++noValues;
+           
+           // Process the <key, value> pair (assume this takes a while)
+           // ...
+           // ...
+           
+           // Let the framework know that we are alive, and kicking!
+           if ((noValues%10) == 0) {
+             reporter.progress();
+           }
+         
+           // Process some more
+           // ...
+           // ...
+           
+           // Output the <key, value> 
+           output.collect(key, value);
+         }
+         
+         // Increment the no. of <key, list of values> pairs processed
+         ++noKeys;
+         
+         // Increment counters
+         reporter.incrCounter(NUM_RECORDS, 1);
+         
+         // Every 100 keys update application-level status
+         if ((noKeys%100) == 0) {
+           reporter.setStatus(reduceTaskId + " processed " + noKeys);
+         }
+       }
+     }
+

    + + @see Mapper + @see Partitioner + @see Reporter + @see MapReduceBase + @deprecated Use {@link org.apache.hadoop.mapreduce.Reducer} instead.]]> +     +     + + + + + + + + + + + + + + Counter of the given group/name.]]> + + + + + + + Counter of the given group/name.]]> + + + + + + + Enum. + @param amount A non-negative amount by which the counter is to + be incremented.]]> + + + + + + + + + + + + + + InputSplit that the map is reading from. + @throws UnsupportedOperationException if called outside a mapper]]> + + + + + + + + + {@link Mapper} and {@link Reducer} can use the Reporter + provided to report progress or just indicate that they are alive. In + scenarios where the application takes an insignificant amount of time to + process individual key/value pairs, this is crucial since the framework + might assume that the task has timed-out and kill that task. + +

    Applications can also update {@link Counters} via the provided + Reporter .

    + + @see Progressable + @see Counters]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + progress of the job's map-tasks, as a float between 0.0 + and 1.0. When all map tasks have completed, the function returns 1.0. + + @return the progress of the job's map-tasks. + @throws IOException]]> + + + + + + progress of the job's reduce-tasks, as a float between 0.0 + and 1.0. When all reduce tasks have completed, the function returns 1.0. + + @return the progress of the job's reduce-tasks. + @throws IOException]]> + + + + + + progress of the job's cleanup-tasks, as a float between 0.0 + and 1.0. When all cleanup tasks have completed, the function returns 1.0. + + @return the progress of the job's cleanup-tasks. + @throws IOException]]> + + + + + + progress of the job's setup-tasks, as a float between 0.0 + and 1.0. When all setup tasks have completed, the function returns 1.0. + + @return the progress of the job's setup-tasks. + @throws IOException]]> + + + + + + true if the job is complete, else false. + @throws IOException]]> + + + + + + true if the job succeeded, else false. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + RunningJob is the user-interface to query for details on a + running Map-Reduce job. + +

    Clients can get hold of RunningJob via the {@link JobClient} + and then query the running-job for details such as name, configuration, + progress etc.

    + + @see JobClient]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This allows the user to specify the key class to be different + from the actual class ({@link BytesWritable}) used for writing

    + + @param conf the {@link JobConf} to modify + @param theClass the SequenceFile output key class.]]> +     +     + + + + + This allows the user to specify the value class to be different + from the actual class ({@link BytesWritable}) used for writing

    + + @param conf the {@link JobConf} to modify + @param theClass the SequenceFile output key class.]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + f. The filtering criteria is + MD5(key) % f == 0.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + f using + the criteria record# % f == 0. + For example, if the frequency is 10, one out of 10 records is returned.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if auto increment + {@link SkipBadRecords#COUNTER_MAP_PROCESSED_RECORDS}. + false otherwise.]]> + + + + + + + + + + + + + true if auto increment + {@link SkipBadRecords#COUNTER_REDUCE_PROCESSED_GROUPS}. + false otherwise.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Hadoop provides an optional mode of execution in which the bad records + are detected and skipped in further attempts. + +

    This feature can be used when map/reduce tasks crashes deterministically on + certain input. This happens due to bugs in the map/reduce function. The usual + course would be to fix these bugs. But sometimes this is not possible; + perhaps the bug is in third party libraries for which the source code is + not available. Due to this, the task never reaches to completion even with + multiple attempts and complete data for that task is lost.

    + +

    With this feature, only a small portion of data is lost surrounding + the bad record, which may be acceptable for some user applications. + see {@link SkipBadRecords#setMapperMaxSkipRecords(Configuration, long)}

    + +

    The skipping mode gets kicked off after certain no of failures + see {@link SkipBadRecords#setAttemptsToStartSkipping(Configuration, int)}

    + +

    In the skipping mode, the map/reduce task maintains the record range which + is getting processed at all times. Before giving the input to the + map/reduce function, it sends this record range to the Task tracker. + If task crashes, the Task tracker knows which one was the last reported + range. On further attempts that range get skipped.

    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + all task attempt IDs + of any jobtracker, in any job, of the first + map task, we would use : + 
     
+ TaskAttemptID.getTaskAttemptIDsPattern(null, null, true, 1, null);
+
    + which will return : + 
     "attempt_[^_]*_[0-9]*_m_000001_[0-9]*"
    + @param jtIdentifier jobTracker identifier, or null + @param jobId job number, or null + @param isMap whether the tip is a map, or null + @param taskId taskId number, or null + @param attemptId the task attempt number, or null + @return a regex pattern matching TaskAttemptIDs]]> +     +     + + + An example TaskAttemptID is : + attempt_200707121733_0003_m_000005_0 , which represents the + zeroth task attempt for the fifth map task in the third job + running at the jobtracker started at 200707121733. +

    + Applications should never construct or parse TaskAttemptID strings + , but rather use appropriate constructors or {@link #forName(String)} + method. + + @see JobID + @see TaskID]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + the first map task + of any jobtracker, of any job, we would use : + 

     
+ TaskID.getTaskIDsPattern(null, null, true, 1);
+
    + which will return : + 
     "task_[^_]*_[0-9]*_m_000001*"
    + @param jtIdentifier jobTracker identifier, or null + @param jobId job number, or null + @param isMap whether the tip is a map, or null + @param taskId taskId number, or null + @return a regex pattern matching TaskIDs]]> +     + + + + + + + + An example TaskID is : + task_200707121733_0003_m_000005 , which represents the + fifth map task in the third job running at the jobtracker + started at 200707121733. +

    + Applications should never construct or parse TaskID strings + , but rather use appropriate constructors or {@link #forName(String)} + method. + + @see JobID + @see TaskAttemptID]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + hadoop.log.dir.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if the Job was added.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ([,]*) + func ::= tbl(,"") + class ::= @see java.lang.Class#forName(java.lang.String) + path ::= @see org.apache.hadoop.fs.Path#Path(java.lang.String) + } + Reads expression from the mapred.join.expr property and + user-supplied join types from mapred.join.define.<ident> + types. Paths supplied to tbl are given as input paths to the + InputFormat class listed. + @see #compose(java.lang.String, java.lang.Class, java.lang.String...)]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ,

    ) }]]> + + + + + + + + (tbl(,),tbl(,),...,tbl(,)) }]]> + + + + + + + + (tbl(,),tbl(,),...,tbl(,)) }]]> + + + + mapred.join.define.<ident> to a classname. In the expression + mapred.join.expr, the identifier will be assumed to be a + ComposableRecordReader. + mapred.join.keycomparator can be a classname used to compare keys + in the join. + @see JoinRecordReader + @see MultiFilterRecordReader]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + ...... + }]]> + + + + + + + + + + + + + + + + + + + + + capacity children to position + id in the parent reader. + The id of a root CompositeRecordReader is -1 by convention, but relying + on this is not recommended.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + override(S1,S2,S3) will prefer values + from S3 over S2, and values from S2 over S1 for all keys + emitted from all sources.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + [,,...,]]]> + + + + + + + out. + TupleWritable format: + {@code + ...... + }]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + It has to be specified how key and values are passed from one element of + the chain to the next, by value or by reference. If a Mapper leverages the + assumed semantics that the key and values are not modified by the collector + 'by value' must be used. If the Mapper does not expect this semantics, as + an optimization to avoid serialization and deserialization 'by reference' + can be used. +

    + For the added Mapper the configuration given for it, + mapperConf, have precedence over the job's JobConf. This + precedence is in effect when the task is running. +

    + IMPORTANT: There is no need to specify the output key/value classes for the + ChainMapper, this is done by the addMapper for the last mapper in the chain +

    + + @param job job's JobConf to add the Mapper class. + @param klass the Mapper class to add. + @param inputKeyClass mapper input key class. + @param inputValueClass mapper input value class. + @param outputKeyClass mapper output key class. + @param outputValueClass mapper output value class. + @param byValue indicates if key/values should be passed by value + to the next Mapper in the chain, if any. + @param mapperConf a JobConf with the configuration for the Mapper + class. It is recommended to use a JobConf without default values using the + JobConf(boolean loadDefaults) constructor with FALSE.]]> + + + + + + + If this method is overriden super.configure(...) should be + invoked at the beginning of the overwriter method.]]> + + + + + + + + + + map(...) methods of the Mappers in the chain.]]> + + + + + + + If this method is overriden super.close() should be + invoked at the end of the overwriter method.]]> + + + + + The Mapper classes are invoked in a chained (or piped) fashion, the output of + the first becomes the input of the second, and so on until the last Mapper, + the output of the last Mapper will be written to the task's output. +

    + The key functionality of this feature is that the Mappers in the chain do not + need to be aware that they are executed in a chain. This enables having + reusable specialized Mappers that can be combined to perform composite + operations within a single task. +

    + Special care has to be taken when creating chains that the key/values output + by a Mapper are valid for the following Mapper in the chain. It is assumed + all Mappers and the Reduce in the chain use maching output and input key and + value classes as no conversion is done by the chaining code. +

    + Using the ChainMapper and the ChainReducer classes is possible to compose + Map/Reduce jobs that look like [MAP+ / REDUCE MAP*]. And + immediate benefit of this pattern is a dramatic reduction in disk IO. +

    + IMPORTANT: There is no need to specify the output key/value classes for the + ChainMapper, this is done by the addMapper for the last mapper in the chain. +

    + ChainMapper usage pattern: +

    + 

    + ...
+ conf.setJobName("chain");
+ conf.setInputFormat(TextInputFormat.class);
+ conf.setOutputFormat(TextOutputFormat.class);
+ 
    
+ JobConf mapAConf = new JobConf(false);
+ ...
+ ChainMapper.addMapper(conf, AMap.class, LongWritable.class, Text.class,
+   Text.class, Text.class, true, mapAConf);
+ 
    
+ JobConf mapBConf = new JobConf(false);
+ ...
+ ChainMapper.addMapper(conf, BMap.class, Text.class, Text.class,
+   LongWritable.class, Text.class, false, mapBConf);
+ 
    
+ JobConf reduceConf = new JobConf(false);
+ ...
+ ChainReducer.setReducer(conf, XReduce.class, LongWritable.class, Text.class,
+   Text.class, Text.class, true, reduceConf);
+ 
    
+ ChainReducer.addMapper(conf, CMap.class, Text.class, Text.class,
+   LongWritable.class, Text.class, false, null);
+ 
    
+ ChainReducer.addMapper(conf, DMap.class, LongWritable.class, Text.class,
+   LongWritable.class, LongWritable.class, true, null);
+ 
    
+ FileInputFormat.setInputPaths(conf, inDir);
+ FileOutputFormat.setOutputPath(conf, outDir);
+ ...
+ 
    
+ JobClient jc = new JobClient(conf);
+ RunningJob job = jc.submitJob(conf);
+ ...
+
    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + It has to be specified how key and values are passed from one element of + the chain to the next, by value or by reference. If a Reducer leverages the + assumed semantics that the key and values are not modified by the collector + 'by value' must be used. If the Reducer does not expect this semantics, as + an optimization to avoid serialization and deserialization 'by reference' + can be used. +

    + For the added Reducer the configuration given for it, + reducerConf, have precedence over the job's JobConf. This + precedence is in effect when the task is running. +

    + IMPORTANT: There is no need to specify the output key/value classes for the + ChainReducer, this is done by the setReducer or the addMapper for the last + element in the chain. + + @param job job's JobConf to add the Reducer class. + @param klass the Reducer class to add. + @param inputKeyClass reducer input key class. + @param inputValueClass reducer input value class. + @param outputKeyClass reducer output key class. + @param outputValueClass reducer output value class. + @param byValue indicates if key/values should be passed by value + to the next Mapper in the chain, if any. + @param reducerConf a JobConf with the configuration for the Reducer + class. It is recommended to use a JobConf without default values using the + JobConf(boolean loadDefaults) constructor with FALSE.]]> + + + + + + + + + + + + + + It has to be specified how key and values are passed from one element of + the chain to the next, by value or by reference. If a Mapper leverages the + assumed semantics that the key and values are not modified by the collector + 'by value' must be used. If the Mapper does not expect this semantics, as + an optimization to avoid serialization and deserialization 'by reference' + can be used. +

    + For the added Mapper the configuration given for it, + mapperConf, have precedence over the job's JobConf. This + precedence is in effect when the task is running. +

    + IMPORTANT: There is no need to specify the output key/value classes for the + ChainMapper, this is done by the addMapper for the last mapper in the chain + . + + @param job chain job's JobConf to add the Mapper class. + @param klass the Mapper class to add. + @param inputKeyClass mapper input key class. + @param inputValueClass mapper input value class. + @param outputKeyClass mapper output key class. + @param outputValueClass mapper output value class. + @param byValue indicates if key/values should be passed by value + to the next Mapper in the chain, if any. + @param mapperConf a JobConf with the configuration for the Mapper + class. It is recommended to use a JobConf without default values using the + JobConf(boolean loadDefaults) constructor with FALSE.]]> + + + + + + + If this method is overriden super.configure(...) should be + invoked at the beginning of the overwriter method.]]> + + + + + + + + + + reduce(...) method of the Reducer with the + map(...) methods of the Mappers in the chain.]]> + + + + + + + If this method is overriden super.close() should be + invoked at the end of the overwriter method.]]> + + + + + For each record output by the Reducer, the Mapper classes are invoked in a + chained (or piped) fashion, the output of the first becomes the input of the + second, and so on until the last Mapper, the output of the last Mapper will + be written to the task's output. +

    + The key functionality of this feature is that the Mappers in the chain do not + need to be aware that they are executed after the Reducer or in a chain. + This enables having reusable specialized Mappers that can be combined to + perform composite operations within a single task. +

    + Special care has to be taken when creating chains that the key/values output + by a Mapper are valid for the following Mapper in the chain. It is assumed + all Mappers and the Reduce in the chain use maching output and input key and + value classes as no conversion is done by the chaining code. +

    + Using the ChainMapper and the ChainReducer classes is possible to compose + Map/Reduce jobs that look like [MAP+ / REDUCE MAP*]. And + immediate benefit of this pattern is a dramatic reduction in disk IO. +

    + IMPORTANT: There is no need to specify the output key/value classes for the + ChainReducer, this is done by the setReducer or the addMapper for the last + element in the chain. +

    + ChainReducer usage pattern: +

    + 

    + ...
+ conf.setJobName("chain");
+ conf.setInputFormat(TextInputFormat.class);
+ conf.setOutputFormat(TextOutputFormat.class);
+ 
    
+ JobConf mapAConf = new JobConf(false);
+ ...
+ ChainMapper.addMapper(conf, AMap.class, LongWritable.class, Text.class,
+   Text.class, Text.class, true, mapAConf);
+ 
    
+ JobConf mapBConf = new JobConf(false);
+ ...
+ ChainMapper.addMapper(conf, BMap.class, Text.class, Text.class,
+   LongWritable.class, Text.class, false, mapBConf);
+ 
    
+ JobConf reduceConf = new JobConf(false);
+ ...
+ ChainReducer.setReducer(conf, XReduce.class, LongWritable.class, Text.class,
+   Text.class, Text.class, true, reduceConf);
+ 
    
+ ChainReducer.addMapper(conf, CMap.class, Text.class, Text.class,
+   LongWritable.class, Text.class, false, null);
+ 
    
+ ChainReducer.addMapper(conf, DMap.class, LongWritable.class, Text.class,
+   LongWritable.class, LongWritable.class, true, null);
+ 
    
+ FileInputFormat.setInputPaths(conf, inDir);
+ FileOutputFormat.setOutputPath(conf, outDir);
+ ...
+ 
    
+ JobClient jc = new JobClient(conf);
+ RunningJob job = jc.submitJob(conf);
+ ...
+
    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + RecordReader's for CombineFileSplit's. + @see CombineFileSplit]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + th Path]]> + + + + + + th Path]]> + + + + + + + + + + + th Path]]> + + + + + + + + + + + + + + + + + + + + + + + + + + CombineFileSplit can be used to implement {@link org.apache.hadoop.mapred.RecordReader}'s, + with reading one record per file. + @see org.apache.hadoop.mapred.FileSplit + @see CombineFileInputFormat]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + all splits. + @param freq The frequency with which records will be emitted.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + all splits. + This will read every split at the client, which is very expensive. + @param freq Probability with which a key will be chosen. + @param numSamples Total number of samples to obtain from all selected + splits.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + all splits. + Takes the first numSamples / numSplits records from each split. + @param numSamples Total number of samples to obtain from all selected + splits.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if the name output is multi, false + if it is single. If the name output is not defined it returns + false]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @param conf job conf to add the named output + @param namedOutput named output name, it has to be a word, letters + and numbers only, cannot be the word 'part' as + that is reserved for the + default output. + @param outputFormatClass OutputFormat class. + @param keyClass key class + @param valueClass value class]]> + + + + + + + + + + + + @param conf job conf to add the named output + @param namedOutput named output name, it has to be a word, letters + and numbers only, cannot be the word 'part' as + that is reserved for the + default output. + @param outputFormatClass OutputFormat class. + @param keyClass key class + @param valueClass value class]]> + + + + + + + + By default these counters are disabled. +

    + MultipleOutputs supports counters, by default the are disabled. + The counters group is the {@link MultipleOutputs} class name. +

    + The names of the counters are the same as the named outputs. For multi + named outputs the name of the counter is the concatenation of the named + output, and underscore '_' and the multiname. + + @param conf job conf to enableadd the named output. + @param enabled indicates if the counters will be enabled or not.]]> +     +     + + + + + By default these counters are disabled. +

    + MultipleOutputs supports counters, by default the are disabled. + The counters group is the {@link MultipleOutputs} class name. +

    + The names of the counters are the same as the named outputs. For multi + named outputs the name of the counter is the concatenation of the named + output, and underscore '_' and the multiname. + + + @param conf job conf to enableadd the named output. + @return TRUE if the counters are enabled, FALSE if they are disabled.]]> +     +     + + + + + + + + + + + + + @param namedOutput the named output name + @param reporter the reporter + @return the output collector for the given named output + @throws IOException thrown if output collector could not be created]]> + + + + + + + + + + + @param namedOutput the named output name + @param multiName the multi name part + @param reporter the reporter + @return the output collector for the given named output + @throws IOException thrown if output collector could not be created]]> + + + + + + + If overriden subclasses must invoke super.close() at the + end of their close() + + @throws java.io.IOException thrown if any of the MultipleOutput files + could not be closed properly.]]> + + + + OutputCollector passed to + the map() and reduce() methods of the + Mapper and Reducer implementations. +

    + Each additional output, or named output, may be configured with its own + OutputFormat, with its own key class and with its own value + class. +

    + A named output can be a single file or a multi file. The later is refered as + a multi named output. +

    + A multi named output is an unbound set of files all sharing the same + OutputFormat, key class and value class configuration. +

    + When named outputs are used within a Mapper implementation, + key/values written to a name output are not part of the reduce phase, only + key/values written to the job OutputCollector are part of the + reduce phase. +

    + MultipleOutputs supports counters, by default the are disabled. The counters + group is the {@link MultipleOutputs} class name. +

    + The names of the counters are the same as the named outputs. For multi + named outputs the name of the counter is the concatenation of the named + output, and underscore '_' and the multiname. +

    + Job configuration usage pattern is: + 

    +
+ JobConf conf = new JobConf();
+
+ conf.setInputPath(inDir);
+ FileOutputFormat.setOutputPath(conf, outDir);
+
+ conf.setMapperClass(MOMap.class);
+ conf.setReducerClass(MOReduce.class);
+ ...
+
+ // Defines additional single text based output 'text' for the job
+ MultipleOutputs.addNamedOutput(conf, "text", TextOutputFormat.class,
+ LongWritable.class, Text.class);
+
+ // Defines additional multi sequencefile based output 'sequence' for the
+ // job
+ MultipleOutputs.addMultiNamedOutput(conf, "seq",
+   SequenceFileOutputFormat.class,
+   LongWritable.class, Text.class);
+ ...
+
+ JobClient jc = new JobClient();
+ RunningJob job = jc.submitJob(conf);
+
+ ...
+
    +

    + Job configuration usage pattern is: + 

    +
+ public class MOReduce implements
+   Reducer<WritableComparable, Writable> {
+ private MultipleOutputs mos;
+
+ public void configure(JobConf conf) {
+ ...
+ mos = new MultipleOutputs(conf);
+ }
+
+ public void reduce(WritableComparable key, Iterator<Writable> values,
+ OutputCollector output, Reporter reporter)
+ throws IOException {
+ ...
+ mos.getCollector("text", reporter).collect(key, new Text("Hello"));
+ mos.getCollector("seq", "A", reporter).collect(key, new Text("Bye"));
+ mos.getCollector("seq", "B", reporter).collect(key, new Text("Chau"));
+ ...
+ }
+
+ public void close() throws IOException {
+ mos.close();
+ ...
+ }
+
+ }
+
    ]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + It can be used instead of the default implementation, + @link org.apache.hadoop.mapred.MapRunner, when the Map operation is not CPU + bound in order to improve throughput. +

    + Map implementations using this MapRunnable must be thread-safe. +

    + The Map-Reduce job has to be configured to use this MapRunnable class (using + the JobConf.setMapRunnerClass method) and + the number of thread the thread-pool can use with the + mapred.map.multithreadedrunner.threads property, its default + value is 10 threads. +

    ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + pairs. Uses + {@link StringTokenizer} to break text into tokens. + @deprecated Use + {@link org.apache.hadoop.mapreduce.lib.map.TokenCounterMapper} instead.]]> + + + + + + + + + + + + total.order.partitioner.natural.order is not false, a trie + of the first total.order.partitioner.max.trie.depth(2) + 1 bytes + will be built. Otherwise, keys will be located using a binary search of + the partition keyset using the {@link org.apache.hadoop.io.RawComparator} + defined for this job. The input file must be sorted with the same + comparator and contain {@link + org.apache.hadoop.mapred.JobConf#getNumReduceTasks} - 1 keys.]]> + + + + + + + + + + + + R reduces, there are R-1 + keys in the SequenceFile.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + generateKeyValPairs(Object key, Object value); public void + configure(JobConfjob); } + + The package also provides a base class, ValueAggregatorBaseDescriptor, + implementing the above interface. The user can extend the base class and + implement generateKeyValPairs accordingly. + + The primary work of generateKeyValPairs is to emit one or more key/value + pairs based on the input key/value pair. The key in an output key/value pair + encode two pieces of information: aggregation type and aggregation id. The + value will be aggregated onto the aggregation id according the aggregation + type. + + This class offers a function to generate a map/reduce job using Aggregate + framework. The function takes the following parameters: input directory spec + input format (text or sequence file) output directory a file specifying the + user plugin class]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The job can be configured using the static methods in this class, + {@link DBInputFormat}, and {@link DBOutputFormat}. +

    + Alternatively, the properties can be set in the configuration with proper + values. + + @see DBConfiguration#configureDB(JobConf, String, String, String, String) + @see DBInputFormat#setInput(JobConf, Class, String, String) + @see DBInputFormat#setInput(JobConf, Class, String, String, String, String...) + @see DBOutputFormat#setOutput(JobConf, String, String...)]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 20070101 AND length > 0)' + @param orderBy the fieldNames in the orderBy clause. + @param fieldNames The field names in the table + @see #setInput(JobConf, Class, String, String)]]> + + + + + + + + + + + + + + DBInputFormat emits LongWritables containing the record number as + key and DBWritables as value. + + The SQL query, and input class can be using one of the two + setInput methods.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + {@link DBOutputFormat} accepts <key,value> pairs, where + key has a type extending DBWritable. Returned {@link RecordWriter} + writes only the key to the database with a batch SQL query.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + DBWritable. DBWritable, is similar to {@link Writable} + except that the {@link #write(PreparedStatement)} method takes a + {@link PreparedStatement}, and {@link #readFields(ResultSet)} + takes a {@link ResultSet}. +

    + Implementations are responsible for writing the fields of the object + to PreparedStatement, and reading the fields of the object from the + ResultSet. + +

    Example:

    + If we have the following table in the database : + 
    + CREATE TABLE MyTable (
+   counter        INTEGER NOT NULL,
+   timestamp      BIGINT  NOT NULL,
+ );
+
    + then we can read/write the tuples from/to the table with : + 

    + public class MyWritable implements Writable, DBWritable {
+   // Some data     
+   private int counter;
+   private long timestamp;
+       
+   //Writable#write() implementation
+   public void write(DataOutput out) throws IOException {
+     out.writeInt(counter);
+     out.writeLong(timestamp);
+   }
+       
+   //Writable#readFields() implementation
+   public void readFields(DataInput in) throws IOException {
+     counter = in.readInt();
+     timestamp = in.readLong();
+   }
+       
+   public void write(PreparedStatement statement) throws SQLException {
+     statement.setInt(1, counter);
+     statement.setLong(2, timestamp);
+   }
+       
+   public void readFields(ResultSet resultSet) throws SQLException {
+     counter = resultSet.getInt(1);
+     timestamp = resultSet.getLong(2);
+   } 
+ }
+

    ]]> +     + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Counters represent global counters, defined either by the + Map-Reduce framework or applications. Each Counter is named by + an {@link Enum} and has a long for the value.

    + +

    Counters are bunched into Groups, each comprising of + counters from a particular Enum class.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Each {@link InputSplit} is then assigned to an individual {@link Mapper} + for processing.

    + +

    Note: The split is a logical split of the inputs and the + input files are not physically split into chunks. For e.g. a split could + be <input-file-path, start, offset> tuple. The InputFormat + also creates the {@link RecordReader} to read the {@link InputSplit}. + + @param context job configuration. + @return an array of {@link InputSplit}s for the job.]]> + + + + + + + + + + + + + InputFormat describes the input-specification for a + Map-Reduce job. + +

    The Map-Reduce framework relies on the InputFormat of the + job to:

    +

      +
    1. + Validate the input-specification of the job. +
    2. + Split-up the input file(s) into logical {@link InputSplit}s, each of + which is then assigned to an individual {@link Mapper}. +
      3. +
    3. + Provide the {@link RecordReader} implementation to be used to glean + input records from the logical InputSplit for processing by + the {@link Mapper}. +
      4. +
    + +

    The default behavior of file-based {@link InputFormat}s, typically + sub-classes of {@link FileInputFormat}, is to split the + input into logical {@link InputSplit}s based on the total size, in + bytes, of the input files. However, the {@link FileSystem} blocksize of + the input files is treated as an upper bound for input splits. A lower bound + on the split size can be set via + + mapred.min.split.size.

    + +

    Clearly, logical splits based on input-size is insufficient for many + applications since record boundaries are to respected. In such cases, the + application has to also implement a {@link RecordReader} on whom lies the + responsibility to respect record-boundaries and present a record-oriented + view of the logical InputSplit to the individual task. + + @see InputSplit + @see RecordReader + @see FileInputFormat]]> + + + + + + + + + + + + + + + + + + + + + + + InputSplit represents the data to be processed by an + individual {@link Mapper}. + +

    Typically, it presents a byte-oriented view on the input and is the + responsibility of {@link RecordReader} of the job to process this and present + a record-oriented view. + + @see InputFormat + @see RecordReader]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + InputFormat to use + @throws IllegalStateException if the job is submitted]]> + + + + + + + OutputFormat to use + @throws IllegalStateException if the job is submitted]]> + + + + + + + Mapper to use + @throws IllegalStateException if the job is submitted]]> + + + + + + + + + + + + + + + + + + + + + + + + + Reducer to use + @throws IllegalStateException if the job is submitted]]> + + + + + + + Partitioner to use + @throws IllegalStateException if the job is submitted]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + progress of the job's map-tasks, as a float between 0.0 + and 1.0. When all map tasks have completed, the function returns 1.0. + + @return the progress of the job's map-tasks. + @throws IOException]]> + + + + + + progress of the job's reduce-tasks, as a float between 0.0 + and 1.0. When all reduce tasks have completed, the function returns 1.0. + + @return the progress of the job's reduce-tasks. + @throws IOException]]> + + + + + + true if the job is complete, else false. + @throws IOException]]> + + + + + + true if the job succeeded, else false. + @throws IOException]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + JobTracker is lost]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 1. + @return the number of reduce tasks for this job.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + An example JobID is : + job_200707121733_0003 , which represents the third job + running at the jobtracker started at 200707121733. +

    + Applications should never construct or parse JobID strings, but rather + use appropriate constructors or {@link #forName(String)} method. + + @see TaskID + @see TaskAttemptID + @see org.apache.hadoop.mapred.JobTracker#getNewJobId() + @see org.apache.hadoop.mapred.JobTracker#getStartTime()]]> + + + + + + + + + + + + + + + + + + + + + + + + + + the key input type to the Mapper + @param the value input type to the Mapper + @param the key output type from the Mapper + @param the value output type from the Mapper]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Maps are the individual tasks which transform input records into a + intermediate records. The transformed intermediate records need not be of + the same type as the input records. A given input pair may map to zero or + many output pairs.

    + +

    The Hadoop Map-Reduce framework spawns one map task for each + {@link InputSplit} generated by the {@link InputFormat} for the job. + Mapper implementations can access the {@link Configuration} for + the job via the {@link JobContext#getConfiguration()}. + +

    The framework first calls + {@link #setup(org.apache.hadoop.mapreduce.Mapper.Context)}, followed by + {@link #map(Object, Object, Context)} + for each key/value pair in the InputSplit. Finally + {@link #cleanup(Context)} is called.

    + +

    All intermediate values associated with a given output key are + subsequently grouped by the framework, and passed to a {@link Reducer} to + determine the final output. Users can control the sorting and grouping by + specifying two key {@link RawComparator} classes.

    + +

    The Mapper outputs are partitioned per + Reducer. Users can control which keys (and hence records) go to + which Reducer by implementing a custom {@link Partitioner}. + +

    Users can optionally specify a combiner, via + {@link Job#setCombinerClass(Class)}, to perform local aggregation of the + intermediate outputs, which helps to cut down the amount of data transferred + from the Mapper to the Reducer. + +

    Applications can specify if and how the intermediate + outputs are to be compressed and which {@link CompressionCodec}s are to be + used via the Configuration.

    + +

    If the job has zero + reduces then the output of the Mapper is directly written + to the {@link OutputFormat} without sorting by keys.

    + +

    Example:

    + 

    + public class TokenCounterMapper 
+     extends Mapper{
+    
+   private final static IntWritable one = new IntWritable(1);
+   private Text word = new Text();
+   
+   public void map(Object key, Text value, Context context) throws IOException {
+     StringTokenizer itr = new StringTokenizer(value.toString());
+     while (itr.hasMoreTokens()) {
+       word.set(itr.nextToken());
+       context.collect(word, one);
+     }
+   }
+ }
+

    + +

    Applications may override the {@link #run(Context)} method to exert + greater control on map processing e.g. multi-threaded Mappers + etc.

    + + @see InputFormat + @see JobContext + @see Partitioner + @see Reducer]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + OutputCommitter describes the commit of task output for a + Map-Reduce job. + +

    The Map-Reduce framework relies on the OutputCommitter of + the job to:

    +

      +
    1. + Setup the job during initialization. For example, create the temporary + output directory for the job during the initialization of the job. +
      2. +
    2. + Cleanup the job after the job completion. For example, remove the + temporary output directory after the job completion. +
      3. +
    3. + Setup the task temporary output. +
      4. +
    4. + Check whether a task needs a commit. This is to avoid the commit + procedure if a task does not need commit. +
      5. +
    5. + Commit of the task output. +
      6. +
    6. + Discard the task commit. +
      7. +
    + + @see org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter + @see JobContext + @see TaskAttemptContext]]> +     +     + + + + + + + + + + + + + + + + + + + This is to validate the output specification for the job when it is + a job is submitted. Typically checks that it does not already exist, + throwing an exception when it already exists, so that output is not + overwritten.

    + + @param context information about the job + @throws IOException when output should not be attempted]]> +     +     + + + + + + + + + + OutputFormat describes the output-specification for a + Map-Reduce job. + +

    The Map-Reduce framework relies on the OutputFormat of the + job to:

    +

      +
    1. + Validate the output-specification of the job. For e.g. check that the + output directory doesn't already exist. +
    2. + Provide the {@link RecordWriter} implementation to be used to write out + the output files of the job. Output files are stored in a + {@link FileSystem}. +
      3. +
    + + @see RecordWriter]]> +     +     + + + + + + + + + + + Typically a hash function on a all or a subset of the key.

    + + @param key the key to be partioned. + @param value the entry value. + @param numPartitions the total number of partitions. + @return the partition number for the key.]]> +     +     + + Partitioner controls the partitioning of the keys of the + intermediate map-outputs. The key (or a subset of the key) is used to derive + the partition, typically by a hash function. The total number of partitions + is the same as the number of reduce tasks for the job. Hence this controls + which of the m reduce tasks the intermediate key (and hence the + record) is sent for reduction.

    + + @see Reducer]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @param ]]> + + + + + + + + + + + + + + + + + + + + + + RecordWriter to future operations. + + @param context the context of the task + @throws IOException]]> + + + + RecordWriter writes the output <key, value> pairs + to an output file. + +

    RecordWriter implementations write the job outputs to the + {@link FileSystem}. + + @see OutputFormat]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + the class of the input keys + @param the class of the input values + @param the class of the output keys + @param the class of the output values]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Reducer implementations + can access the {@link Configuration} for the job via the + {@link JobContext#getConfiguration()} method.

    + +

    Reducer has 3 primary phases:

    +
      +
    1. + +

      Shuffle

      + +

      The Reducer copies the sorted output from each + {@link Mapper} using HTTP across the network.

      +
      2. + +
    2. +

      Sort

      + +

      The framework merge sorts Reducer inputs by + keys + (since different Mappers may have output the same key).

      + +

      The shuffle and sort phases occur simultaneously i.e. while outputs are + being fetched they are merged.

      + +
      SecondarySort
      + +

      To achieve a secondary sort on the values returned by the value + iterator, the application should extend the key with the secondary + key and define a grouping comparator. The keys will be sorted using the + entire key, but will be grouped using the grouping comparator to decide + which keys and values are sent in the same call to reduce.The grouping + comparator is specified via + {@link Job#setGroupingComparatorClass(Class)}. The sort order is + controlled by + {@link Job#setSortComparatorClass(Class)}.

      + + + For example, say that you want to find duplicate web pages and tag them + all with the url of the "best" known example. You would set up the job + like: +
        +
      • Map Input Key: url
        • +
      • Map Input Value: document
        • +
      • Map Output Key: document checksum, url pagerank
        • +
      • Map Output Value: url
        • +
      • Partitioner: by checksum
        • +
      • OutputKeyComparator: by checksum and then decreasing pagerank
        • +
      • OutputValueGroupingComparator: by checksum
        • +
      +
      3. + +
    3. +

      Reduce

      + +

      In this phase the + {@link #reduce(Object, Iterable, Context)} + method is called for each <key, (collection of values)> in + the sorted inputs.

      +

      The output of the reduce task is typically written to a + {@link RecordWriter} via + {@link Context#write(Object, Object)}.

      +
      4. +
    + +

    The output of the Reducer is not re-sorted.

    + +

    Example:

    + 

    + public class IntSumReducer extends Reducer {
+   private IntWritable result = new IntWritable();
+ 
+   public void reduce(Key key, Iterable values, 
+                      Context context) throws IOException {
+     int sum = 0;
+     for (IntWritable val : values) {
+       sum += val.get();
+     }
+     result.set(sum);
+     context.collect(key, result);
+   }
+ }
+

    + + @see Mapper + @see Partitioner]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + An example TaskAttemptID is : + attempt_200707121733_0003_m_000005_0 , which represents the + zeroth task attempt for the fifth map task in the third job + running at the jobtracker started at 200707121733. +

    + Applications should never construct or parse TaskAttemptID strings + , but rather use appropriate constructors or {@link #forName(String)} + method. + + @see JobID + @see TaskID]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + An example TaskID is : + task_200707121733_0003_m_000005 , which represents the + fifth map task in the third job running at the jobtracker + started at 200707121733. +

    + Applications should never construct or parse TaskID strings + , but rather use appropriate constructors or {@link #forName(String)} + method. + + @see JobID + @see TaskAttemptID]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + the input key type for the task + @param the input value type for the task + @param the output key type for the task + @param the output value type for the task]]> + + + + + + + + + + + + + + + + + + + FileInputFormat implementations can override this and return + false to ensure that individual input files are never split-up + so that {@link Mapper}s process entire files. + + @param context the job context + @param filename the file name to check + @return is this file splitable?]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + FileInputFormat is the base class for all file-based + InputFormats. This provides a generic implementation of + {@link #getSplits(JobContext)}. + Subclasses of FileInputFormat can also override the + {@link #isSplitable(JobContext, Path)} method to ensure input-files are + not split-up and are processed as a whole by {@link Mapper}s.]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + the map's input key type + @param the map's input value type + @param the map's output key type + @param the map's output value type + @param job the job + @return the mapper class to run]]> + + + + + + + the map input key type + @param the map input value type + @param the map output key type + @param the map output value type + @param job the job to modify + @param cls the class to use as the mapper]]> + + + + + + + + + + + + + It can be used instead of the default implementation, + @link org.apache.hadoop.mapred.MapRunner, when the Map operation is not CPU + bound in order to improve throughput. +

    + Mapper implementations using this MapRunnable must be thread-safe. +

    + The Map-Reduce job has to be configured with the mapper to use via + {@link #setMapperClass(Configuration, Class)} and + the number of thread the thread-pool can use with the + {@link #getNumberOfThreads(Configuration) method. The default + value is 10 threads. +

    ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + true if the job output should be compressed, + false otherwise]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Tasks' Side-Effect Files + +

    Some applications need to create/write-to side-files, which differ from + the actual job-outputs. + +

    In such cases there could be issues with 2 instances of the same TIP + (running simultaneously e.g. speculative tasks) trying to open/write-to the + same file (path) on HDFS. Hence the application-writer will have to pick + unique names per task-attempt (e.g. using the attemptid, say + attempt_200709221812_0001_m_000000_0), not just per TIP.

    + +

    To get around this the Map-Reduce framework helps the application-writer + out by maintaining a special + ${mapred.output.dir}/_temporary/_${taskid} + sub-directory for each task-attempt on HDFS where the output of the + task-attempt goes. On successful completion of the task-attempt the files + in the ${mapred.output.dir}/_temporary/_${taskid} (only) + are promoted to ${mapred.output.dir}. Of course, the + framework discards the sub-directory of unsuccessful task-attempts. This + is completely transparent to the application.

    + +

    The application-writer can take advantage of this by creating any + side-files required in a work directory during execution + of his task i.e. via + {@link #getWorkOutputPath(TaskInputOutputContext)}, and + the framework will move them out similarly - thus she doesn't have to pick + unique paths per task-attempt.

    + +

    The entire discussion holds true for maps of jobs with + reducer=NONE (i.e. 0 reduces) since output of the map, in that case, + goes directly to HDFS.

    + + @return the {@link Path} to the task's temporary output directory + for the map-reduce job.]]> +     + + + + + + + + + The path can be used to create custom files from within the map and + reduce tasks. The path name will be unique for each task. The path parent + will be the job output directory.

    ls + +

    This method uses the {@link #getUniqueFile} method to make the file name + unique for the task.

    + + @param context the context for the task. + @param name the name for the file. + @param extension the extension for the file + @return a unique path accross all tasks of the job.]]> +     +     + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +     + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + This tool supports archiving and anaylzing (sort/grep) of log-files. + It takes as input + a) Input uri which will serve uris of the logs to be archived. + b) Output directory (not mandatory). + b) Directory on dfs to archive the logs. + c) The sort/grep patterns for analyzing the files and separator for boundaries. + Usage: + Logalyzer -archive -archiveDir -analysis -logs -grep -sort -separator +

    ]]> + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +