true if the key is deprecated and
false otherwise.]]>
null if
no such property exists. If the key is deprecated, it returns the value of
the first key which replaces the deprecated key and is not null.
Values are processed for variable expansion
before being returned.
@param name the property name, will be trimmed before get value.
@return the value of the name or its replacing property,
or null if no such property exists.]]>
name exists without value]]>
String,
null if no such property exists.
If the key is deprecated, it returns the value of
the first key which replaces the deprecated key and is not null
Values are processed for variable expansion
before being returned.
@param name the property name.
@return the value of the name or its replacing property,
or null if no such property exists.]]>
String,
defaultValue if no such property exists.
See @{Configuration#getTrimmed} for more details.
@param name the property name.
@param defaultValue the property default value.
@return the value of the name or defaultValue
if it is not set.]]>
name property or
its replacing property and null if no such property exists.]]>
name property. If
name is deprecated or there is a deprecated name associated to it,
it sets the value to both names. Name will be trimmed before put into
configuration.
@param name property name.
@param value property value.]]>
name property. If
name is deprecated, it also sets the value to
the keys that replace the deprecated key. Name will be trimmed before put
into configuration.
@param name property name.
@param value property value.
@param source the place that this configuration value came from
(For debugging).
@throws IllegalArgumentException when the value or name is null.]]>
defaultValue is returned.
@param name property name, will be trimmed before get value.
@param defaultValue default value.
@return property value, or defaultValue if the property
doesn't exist.]]>
int.
If no such property exists, the provided default value is returned,
or if the specified value is not a valid int,
then an error is thrown.
@param name property name.
@param defaultValue default value.
@throws NumberFormatException when the value is invalid
@return property value as an int,
or defaultValue.]]>
int values.
If no such property exists, an empty array is returned.
@param name property name
@return property value interpreted as an array of comma-delimited
int values]]>
int.
@param name property name.
@param value int value of the property.]]>
long.
If no such property exists, the provided default value is returned,
or if the specified value is not a valid long,
then an error is thrown.
@param name property name.
@param defaultValue default value.
@throws NumberFormatException when the value is invalid
@return property value as a long,
or defaultValue.]]>
long or
human readable format. If no such property exists, the provided default
value is returned, or if the specified value is not a valid
long or human readable format, then an error is thrown. You
can use the following suffix (case insensitive): k(kilo), m(mega), g(giga),
t(tera), p(peta), e(exa)
@param name property name.
@param defaultValue default value.
@throws NumberFormatException when the value is invalid
@return property value as a long,
or defaultValue.]]>
long.
@param name property name.
@param value long value of the property.]]>
float.
If no such property exists, the provided default value is returned,
or if the specified value is not a valid float,
then an error is thrown.
@param name property name.
@param defaultValue default value.
@throws NumberFormatException when the value is invalid
@return property value as a float,
or defaultValue.]]>
float.
@param name property name.
@param value property value.]]>
double.
If no such property exists, the provided default value is returned,
or if the specified value is not a valid double,
then an error is thrown.
@param name property name.
@param defaultValue default value.
@throws NumberFormatException when the value is invalid
@return property value as a double,
or defaultValue.]]>
double.
@param name property name.
@param value property value.]]>
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.]]>
boolean.
@param name property name.
@param value boolean value of the property.]]>
set(<name>, value.toString()).
@param name property name
@param value new value]]>
set(<name>, value + <time suffix>).
@param name Property name
@param value Time duration
@param unit Unit of time]]>
Pattern.
If no such property is specified, or if the specified value is not a valid
Pattern, then DefaultValue is returned.
Note that the returned value is NOT trimmed by this method.
@param name property name
@param defaultValue default value
@return property value as a compiled Pattern, or defaultValue]]>
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.]]>
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.]]>
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.]]>
Strings, trimmed of the leading and trailing whitespace.
If no such property is specified then empty Collection is returned.
@param name property name.
@return property value as a collection of Strings, or empty Collection]]>
Strings, trimmed of the leading and trailing whitespace.
If no such property is specified then an empty array is returned.
@param name property name.
@return property value as an array of trimmed Strings,
or empty array.]]>
Strings, trimmed of the leading and trailing whitespace.
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 trimmed Strings,
or default value.]]>
InetSocketAddress. If hostProperty is
null, addressProperty will be used. This
is useful for cases where we want to differentiate between host
bind address and address clients should use to establish connection.
@param hostProperty bind host property name.
@param addressProperty address property name.
@param defaultAddressValue the default value
@param defaultPort the default port
@return InetSocketAddress]]>
InetSocketAddress.
@param name property name.
@param defaultAddress the default value
@param defaultPort the default port
@return InetSocketAddress]]>
host:port.]]>
host:port. The wildcard
address is replaced with the local host's address. If the host and address
properties are configured the host component of the address will be combined
with the port component of the addr to generate the address. This is to allow
optional control over which host name is used in multi-home bind-host
cases where a host can have multiple names
@param hostProperty the bind-host configuration name
@param addressProperty the service address configuration name
@param defaultAddressValue the service default address configuration value
@param addr InetSocketAddress of the service listener
@return InetSocketAddress for clients to connect]]>
host:port. The wildcard
address is replaced with the local host's address.
@param name property name.
@param addr InetSocketAddress of a listener to store in the given property
@return InetSocketAddress for clients to connect]]>
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.]]>
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.]]>
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.]]>
List
of objects implementing the interface specified by xface.
An exception is thrown if any of the classes does not exist, or if it does
not implement the named interface.
@param name the property name.
@param xface the interface implemented by the classes named by
name.
@return a List of objects implementing xface.]]>
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.]]>
@param out the writer to write to.]]>
{
"property": {
"key" : "key1",
"value" : "value1",
"isFinal" : "key1.isFinal",
"resource" : "key1.resource"
}
}
{ "properties" :
[ { key : "key1",
value : "value1",
isFinal : "key1.isFinal",
resource : "key1.resource" },
{ key : "key2",
value : "value2",
isFinal : "ke2.isFinal",
resource : "key2.resource" }
]
}
@param config the configuration @param propertyName property name @param out the Writer to write to @throws IOException @throws IllegalArgumentException when property name is not empty and the property is not found in configuration]]>
@param config the configuration @param out the Writer to write to @throws IOException]]>
false
to turn it off.]]>
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:
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.hosts.include</name>
<value>/etc/hadoop/conf/hosts.include</value>
<final>true</final>
</property>
Administrators typically define parameters as final in
core-site.xml for values that user applications may not alter.
Value strings are first processed for variable expansion. The available properties are:
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.
When conf.get("otherdir") is called, then ${env.BASE_DIR} will be resolved to the value of the ${BASE_DIR} environment variable. It supports ${env.NAME:-default} and ${env.NAME-default} notations. The former is resolved to "default" if ${NAME} environment variable is undefined or its value is empty. The latter behaves the same way only if ${NAME} is undefined.
By default, warnings will be given to any deprecated configuration parameters and these are suppressible by configuring log4j.logger.org.apache.hadoop.conf.Configuration.deprecation in log4j.properties file.]]>
KeyProvider implementations must be thread safe.]]>
uri is not supported.]]>
In the case of an exception, the state of the buffer (the contents of the buffer, the {@code buf.position()}, the {@code buf.limit()}, etc.) is undefined, and callers should be prepared to recover from this eventuality.
Callers should use {@link StreamCapabilities#hasCapability(String)} with {@link StreamCapabilities#PREADBYTEBUFFER} to check if the underlying stream supports this interface, otherwise they might get a {@link UnsupportedOperationException}.
Implementations should treat 0-length requests as legitimate, and must not signal an error upon their receipt. @param position position within file @param buf the ByteBuffer to receive the results of the read operation. @return the number of bytes read, possibly zero, or -1 if reached end-of-stream @throws IOException if there is some error performing the read]]>
EnumSet.of(CreateFlag.CREATE, CreateFlag.APPEND)
Use the CreateFlag as follows:
- CREATE - to create a file if it does not exist,
else throw FileAlreadyExists.
- APPEND - to append to a file if it exists,
else throw FileNotFoundException.
- OVERWRITE - to truncate a file if it exists,
else throw FileNotFoundException.
- CREATE|APPEND - to create a file if it does not exist,
else append to an existing file.
- CREATE|OVERWRITE - to create a file if it does not exist,
else overwrite an existing file.
- SYNC_BLOCK - to force closed blocks to the disk device.
In addition {@link Syncable#hsync()} should be called after each write,
if true synchronous behavior is required.
- LAZY_PERSIST - Create the block on transient storage (RAM) if
available.
- APPEND_NEWBLOCK - Append data to a new block instead of end of the last
partial block.
Following combinations are not valid and will result in
{@link HadoopIllegalArgumentException}:
- APPEND|OVERWRITE
- CREATE|APPEND|OVERWRITE
]]>
absOrFqPath could
not be instantiated.]]>
f is not valid]]>
f already exists
@throws FileNotFoundException If parent of f does not exist
and createParent is false
@throws ParentNotDirectoryException If parent of f is not a
directory.
@throws UnsupportedFileSystemException If file system for f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server
RuntimeExceptions:
@throws InvalidPathException If path f is not valid]]>
dir does not exist
and createParent is false
@throws ParentNotDirectoryException If parent of dir is not a
directory
@throws UnsupportedFileSystemException If file system for dir
is not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server
RuntimeExceptions:
@throws InvalidPathException If path dir is not valid]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server
RuntimeExceptions:
@throws InvalidPathException If path f is invalid]]>
f
is not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
true if the file has been truncated to the desired
newLength and is immediately available to be reused for
write operations such as append, or
false if a background process of adjusting the length of
the last block has been started, and clients should wait for it to
complete before proceeding with further file updates.
@throws AccessControlException If access is denied
@throws FileNotFoundException If file f does not exist
@throws UnsupportedFileSystemException If file system for f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
If OVERWRITE option is not passed as an argument, rename fails if the dst already exists.
If OVERWRITE option is passed as an argument, rename overwrites the dst if it is a file or an empty directory. Rename fails if dst is a non-empty directory.
Note that atomicity of rename is dependent on the file system implementation. Please refer to the file system documentation for details
@param src path to be renamed
@param dst new path after rename
@throws AccessControlException If access is denied
@throws FileAlreadyExistsException If dst already exists and
options has {@link Options.Rename#OVERWRITE}
option false.
@throws FileNotFoundException If src does not exist
@throws ParentNotDirectoryException If parent of dst is not a
directory
@throws UnsupportedFileSystemException If file system for src
and dst is not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f
is not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server
RuntimeExceptions:
@throws HadoopIllegalArgumentException If username or
groupname is invalid.]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f is
not supported
@throws IOException If an I/O error occurred]]>
f is
not supported
@throws IOException If the given path does not refer to a symlink
or an I/O error occurred]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
linkcode> already exists
@throws FileNotFoundException If target does not exist
@throws ParentNotDirectoryException If parent of link is not a
directory.
@throws UnsupportedFileSystemException If file system for
target or link is not supported
@throws IOException If an I/O error occurred]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
f is
not supported
@throws IOException If an I/O error occurred
Exceptions applicable to file systems accessed over RPC:
@throws RpcClientException If an exception occurred in the RPC client
@throws RpcServerException If an exception occurred in the RPC server
@throws UnexpectedServerException If server implementation throws
undeclared exception to RPC server]]>
The Hadoop file system supports a URI name space and URI names. It offers a forest of file systems that can be referenced using fully qualified URIs. Two common Hadoop file systems implementations are
To facilitate this, Hadoop supports a notion of a default file system. The user can set his default file system, although this is typically set up for you in your environment via your default config. A default file system implies a default scheme and authority; slash-relative names (such as /for/bar) are resolved relative to that default FS. Similarly a user can also have working-directory-relative names (i.e. names not starting with a slash). While the working directory is generally in the same default FS, the wd can be in a different FS.
Hence Hadoop path names can be one of:
****The Role of the FileContext and configuration defaults****
The FileContext provides file namespace context for resolving file names; it also contains the umask for permissions, In that sense it is like the per-process file-related state in Unix system. These two properties
The file system related SS defaults are
*** Usage Model for the FileContext class ***
Example 1: use the default config read from the $HADOOP_CONFIG/core.xml. Unspecified values come from core-defaults.xml in the release jar.
UnsupportedOperationException.
@return the protocol scheme for this FileSystem.
@throws UnsupportedOperationException if the operation is unsupported
(default).]]>
BlockLocation( { "localhost:50010" }, { "localhost" }, 0, file.getLen())
>
@param file FilesStatus to get data from
@param start offset into the given file
@param len length for which to get locations for
@throws IOException IO failure]]>
If OVERWRITE option is not passed as an argument, rename fails if the dst already exists.
If OVERWRITE option is passed as an argument, rename overwrites the dst if it is a file or an empty directory. Rename fails if dst is a non-empty directory.
Note that atomicity of rename is dependent on the file system implementation. Please refer to the file system documentation for details. This default implementation is non atomic.
This method is deprecated since it is a temporary method added to support the transition from FileSystem to FileContext for user applications. @param src path to be renamed @param dst new path after rename @throws FileNotFoundException src path does not exist, or the parent path of dst does not exist. @throws FileAlreadyExistsException dest path exists and is a file @throws ParentNotDirectoryException if the parent path of dest is not a directory @throws IOException on failure]]>
true if the file has been truncated to the desired
newLength and is immediately available to be reused for
write operations such as append, or
false if a background process of adjusting the length of
the last block has been started, and clients should wait for it to
complete before proceeding with further file updates.
@throws IOException IO failure
@throws UnsupportedOperationException if the operation is unsupported
(default).]]>
A filename pattern is composed of regular characters and special pattern matching characters, which are:
The local implementation is {@link LocalFileSystem} and distributed implementation is DistributedFileSystem. There are other implementations for object stores and (outside the Apache Hadoop codebase), third party filesystems.
Notes
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.]]>
file]]>
pathname
should be included]]>
ftp]]>
viewfs]]>
To use viewfs one would typically set the default file system in the config (i.e. fs.defaultFS < = viewfs:///) along with the mount table config variables as described below.
** Config variables to specify the mount table entries **
The file system is initialized from the standard Hadoop config through config variables. See {@link FsConstants} for URI and Scheme constants; See {@link Constants} for config var constants; see {@link ConfigUtil} for convenient lib.
All the mount table config entries for view fs are prefixed by fs.viewfs.mounttable. For example the above example can be specified with the following config variables:
**** Merge Mounts **** (NOTE: merge mounts are not implemented yet.)
One can also use "MergeMounts" to merge several directories (this is sometimes called union-mounts or junction-mounts in the literature. For example of the home directories are stored on say two file systems (because they do not fit on one) then one could specify a mount entry such as following merges two dirs:
Fencing is configured by the operator as an ordered list of methods to attempt. Each method will be tried in turn, and the next in the list will only be attempted if the previous one fails. See {@link NodeFencer} for more information.
If an implementation also implements {@link Configurable} then its
setConf method will be called upon instantiation.]]>
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:getTypes(), defines
the classes which will be wrapped in GenericObject in application.
Attention: this classes defined in getTypes() method, must
implement Writable interface.
public class GenericObject extends GenericWritable {
private static Class[] CLASSES = {
ClassType1.class,
ClassType2.class,
ClassType3.class,
};
protected Class[] getTypes() {
return CLASSES;
}
}
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}.]]>
SequenceFile provides {@link SequenceFile.Writer},
{@link SequenceFile.Reader} and {@link Sorter} classes for writing,
reading and sorting respectively.
SequenceFile Writers based on the
{@link CompressionType} used to compress key/value pairs:
Writer : Uncompressed records.
RecordCompressWriter : Record-compressed files, only compress
values.
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 SequenceFile.Reader} acts as the bridge and can read any of the
above SequenceFile formats.
Essentially there are 3 different formats for SequenceFiles
depending on the CompressionType specified. All of them share a
common header described below.
CompressionCodec class which is used for
compression of keys and/or values (if compression is
enabled).
100 bytes or so.
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]]>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]]>
new byte[0]).]]>
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.]]>
DataOuput to serialize this object into.
@throws IOException]]>
For efficiency, implementations should attempt to re-use storage in the existing object where possible.
@param inDataInput to deseriablize this object from.
@throws IOException]]>
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.
Note that hashCode() is frequently used in Hadoop to partition
keys. It's important that your implementation of hashCode() returns the same
result across different instances of the JVM. Note also that the default
hashCode() implementation in Object does not
satisfy this property.
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 o) {
int thisValue = this.value;
int thatValue = o.value;
return (thisValue < thatValue ? -1 : (thisValue==thatValue ? 0 : 1));
}
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + counter;
result = prime * result + (int) (timestamp ^ (timestamp >>> 32));
return result
}
}
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.]]>
Compressor
@param conf the Configuration object which contains confs for creating or reinit the compressor
@return Compressor for the given
CompressionCodec from the pool or a new one]]>
Decompressor
@return Decompressor for the given
CompressionCodec the pool or a new one]]>
b[] remain unmodified until
the caller is explicitly notified--via {@link #needsInput()}--that the
buffer may be safely modified. With this requirement, an extra
buffer-copy can be avoided.)
@param b Input data
@param off Start offset
@param len Length]]>
true if the input data buffer is empty and
{@link #setInput(byte[], int, int)} should be called in
order to provide more input.]]>
true if a preset dictionary is needed for decompression]]>
true and {@link #getRemaining()}
returns a positive value. finished() will be reset with the
{@link #reset()} method.
@return true if the end of the decompressed
data output stream has been reached.]]>
true and getRemaining() returns
a zero value, indicates that the end of data stream has been reached and
is not a concatenated data stream.
@return The number of bytes remaining in the compressed data buffer.]]>
false when reset() is called.]]>
The behavior of TFile can be customized by the following variables through Configuration:
Suggestions on performance optimization.
To add a new serialization framework write an implementation of {@link org.apache.hadoop.io.serializer.Serialization} and add its name to the "io.serializations" property.
]]>Use {@link org.apache.hadoop.io.serializer.avro.AvroSpecificSerialization} for serialization of classes generated by Avro's 'specific' compiler.
Use {@link org.apache.hadoop.io.serializer.avro.AvroReflectSerialization} for other classes. {@link org.apache.hadoop.io.serializer.avro.AvroReflectSerialization} work for any class which is either in the package list configured via {@link org.apache.hadoop.io.serializer.avro.AvroReflectSerialization#AVRO_REFLECT_PACKAGES} or implement {@link org.apache.hadoop.io.serializer.avro.AvroReflectSerializable} interface.
]]>org.apache.hadoop.metrics.spiorg.apache.hadoop.metrics.fileorg.apache.hadoop.metrics.ganglia
private ContextFactory contextFactory = ContextFactory.getFactory();
void reportMyMetric(float myMetric) {
MetricsContext myContext = contextFactory.getContext("myContext");
MetricsRecord myRecord = myContext.getRecord("myRecord");
myRecord.setMetric("myMetric", myMetric);
myRecord.update();
}
In this example there are three names:
private MetricsRecord diskStats =
contextFactory.getContext("myContext").getRecord("diskStats");
void reportDiskMetrics(String diskName, float diskBusy, float diskUsed) {
diskStats.setTag("diskName", diskName);
diskStats.setMetric("diskBusy", diskBusy);
diskStats.setMetric("diskUsed", diskUsed);
diskStats.update();
}
MetricsRecord.update() is called. Instead it is stored in an
internal table, and the contents of the table are sent periodically.
This can be important for two reasons:
registerUpdater() method. The benefit of this
versus using java.util.Timer is that the callbacks will be done
immediately before sending the data, making the data as current as possible.
ContextFactory factory = ContextFactory.getFactory();
... examine and/or modify factory attributes ...
MetricsContext context = factory.getContext("myContext");
The factory attributes can be examined and modified using the following
ContextFactorymethods:
Object getAttribute(String attributeName)String[] getAttributeNames()void setAttribute(String name, Object value)void removeAttribute(attributeName)ContextFactory.getFactory() initializes the factory attributes by
reading the properties file hadoop-metrics.properties if it exists
on the class path.
A factory attribute named:
contextName.classshould have as its value the fully qualified name of the class to be instantiated by a call of the
CodeFactory method
getContext(contextName). If this factory attribute is not
specified, the default is to instantiate
org.apache.hadoop.metrics.file.FileContext.
Other factory attributes are specific to a particular implementation of this
API and are documented elsewhere. For example, configuration attributes for
the file and Ganglia implementations can be found in the javadoc for
their respective packages.]]>
recordName is not in that set.
@param recordName the name of the record
@throws MetricsException if recordName conflicts with configuration data]]>
emitRecord method in order to transmit
the data.
@deprecated Use org.apache.hadoop.metrics2 package instead.]]>
remove().
@deprecated Use {@link org.apache.hadoop.metrics2.impl.MetricsRecordImpl}
instead.]]>
org.apache.hadoop.metrics.ganglia.
Plugging in an implementation involves writing a concrete subclass of
AbstractMetricsContext. The subclass should get its
configuration information using the getAttribute(attributeName)
method.]]>
basepath property. All metrics will be logged to a file in the
current interval's directory in a file named <hostname>.log, where
<hostname> is the name of the host on which the metrics logging
process is running. The base path is set by the
<prefix>.sink.<instance>.basepath property. The
time zone used to create the current interval's directory name is GMT. If
the basepath property isn't specified, it will default to
"/tmp", which is the temp directory on whatever default file
system is configured for the cluster.
The <prefix>.sink.<instance>.ignore-error
property controls whether an exception is thrown when an error is encountered
writing a log file. The default value is true. When set to
false, file errors are quietly swallowed.
The roll-interval property sets the amount of time before
rolling the directory. The default value is 1 hour. The roll interval may
not be less than 1 minute. The property's value should be given as
number unit, where number is an integer value, and
unit is a valid unit. Valid units are minute, hour,
and day. The units are case insensitive and may be abbreviated or
plural. If no units are specified, hours are assumed. For example,
"2", "2h", "2 hour", and
"2 hours" are all valid ways to specify two hours.
The roll-offset-interval-millis property sets the upper
bound on a random time interval (in milliseconds) that is used to delay
before the initial roll. All subsequent rolls will happen an integer
number of roll intervals after the initial roll, hence retaining the original
offset. The purpose of this property is to insert some variance in the roll
times so that large clusters using this sink on every node don't cause a
performance impact on HDFS by rolling simultaneously. The default value is
30000 (30s). When writing to HDFS, as a rule of thumb, the roll offset in
millis should be no less than the number of sink instances times 5.
The primary use of this class is for logging to HDFS. As it uses {@link org.apache.hadoop.fs.FileSystem} to access the target file system, however, it can be used to write to the local file system, Amazon S3, or any other supported file system. The base path for the sink will determine the file system used. An unqualified path will write to the default file system set by the configuration.
Not all file systems support the ability to append to files. In file
systems without the ability to append to files, only one writer can write to
a file at a time. To allow for concurrent writes from multiple daemons on a
single host, the source property is used to set unique headers
for the log files. The property should be set to the name of
the source daemon, e.g. namenode. The value of the
source property should typically be the same as the property's
prefix. If this property is not set, the source is taken to be
unknown.
Instead of appending to an existing file, by default the sink will create a new file with a suffix of ".<n>&quet;, where n is the next lowest integer that isn't already used in a file name, similar to the Hadoop daemon logs. NOTE: the file with the highest sequence number is the newest file, unlike the Hadoop daemon logs.
For file systems that allow append, the sink supports appending to the
existing file instead. If the allow-append property is set to
true, the sink will instead append to the existing file on file systems that
support appends. By default, the allow-append property is
false.
Note that when writing to HDFS with allow-append set to true,
there is a minimum acceptable number of data nodes. If the number of data
nodes drops below that minimum, the append will succeed, but reading the
data will fail with an IOException in the DataStreamer class. The minimum
number of data nodes required for a successful append is generally 2 or
3.
Note also that when writing to HDFS, the file size information is not updated until the file is closed (at the end of the interval) even though the data is being written successfully. This is a known HDFS limitation that exists because of the performance cost of updating the metadata. See HDFS-5478.
When using this sink in a secure (Kerberos) environment, two additional
properties must be set: keytab-key and
principal-key. keytab-key should contain the key by
which the keytab file can be found in the configuration, for example,
yarn.nodemanager.keytab. principal-key should
contain the key by which the principal can be found in the configuration,
for example, yarn.nodemanager.principal.]]>
*.sink.statsd.class=org.apache.hadoop.metrics2.sink.StatsDSink [prefix].sink.statsd.server.host= [prefix].sink.statsd.server.port= [prefix].sink.statsd.skip.hostname=true|false (optional) [prefix].sink.statsd.service.name=NameNode (name you want for service)]]>
Configured
base class, and should not be changed to do so, as it causes problems
for subclasses. The constructor of the Configured calls
the {@link #setConf(Configuration)} method, which will call into the
subclasses before they have been fully constructed.]]>
RawScriptBasedMapping that performs
the work: reading the configuration parameters, executing any defined
script, handling errors and such like. The outer
class extends {@link CachedDNSToSwitchMapping} to cache the delegated
queries.
This DNS mapper's {@link #isSingleSwitch()} predicate returns
true if and only if a script is defined.]]>
This class uses the configuration parameter {@code net.topology.table.file.name} to locate the mapping file.
Calls to {@link #resolve(List)} will look up the address as defined in the mapping file. If no entry corresponding to the address is found, the value {@code /default-rack} is returned.
]]>DEPRECATED: Replaced by Avro.
recfile = *include module *record
include = "include" path
path = (relative-path / absolute-path)
module = "module" module-name
module-name = name *("." name)
record := "class" name "{" 1*(field) "}"
field := type name ";"
name := ALPHA (ALPHA / DIGIT / "_" )*
type := (ptype / ctype)
ptype := ("byte" / "boolean" / "int" |
"long" / "float" / "double"
"ustring" / "buffer")
ctype := (("vector" "<" type ">") /
("map" "<" type "," type ">" ) ) / name)
module links {
class Link {
ustring URL;
boolean isRelative;
ustring anchorText;
};
}
include "links.jr"
module outlinks {
class OutLinks {
ustring baseURL;
vector outLinks;
};
}
$ rcc -l C++ ...
namespace hadoop {
enum RecFormat { kBinary, kXML, kCSV };
class InStream {
public:
virtual ssize_t read(void *buf, size_t n) = 0;
};
class OutStream {
public:
virtual ssize_t write(const void *buf, size_t n) = 0;
};
class IOError : public runtime_error {
public:
explicit IOError(const std::string& msg);
};
class IArchive;
class OArchive;
class RecordReader {
public:
RecordReader(InStream& in, RecFormat fmt);
virtual ~RecordReader(void);
virtual void read(Record& rec);
};
class RecordWriter {
public:
RecordWriter(OutStream& out, RecFormat fmt);
virtual ~RecordWriter(void);
virtual void write(Record& rec);
};
class Record {
public:
virtual std::string type(void) const = 0;
virtual std::string signature(void) const = 0;
protected:
virtual bool validate(void) const = 0;
virtual void
serialize(OArchive& oa, const std::string& tag) const = 0;
virtual void
deserialize(IArchive& ia, const std::string& tag) = 0;
};
}
namespace links {
class Link : public hadoop::Record {
// ....
};
};
...
private:
int32_t mMyField;
...
public:
int32_t getMyField(void) const {
return mMyField;
};
void setMyField(int32_t m) {
mMyField = m;
};
...
...
private:
std::string mMyBuf;
...
public:
std::string& getMyBuf() {
return mMyBuf;
};
const std::string& getMyBuf() const {
return mMyBuf;
};
...
module inclrec {
class RI {
int I32;
double D;
ustring S;
};
}
include "inclrec.jr"
module testrec {
class R {
vector VF;
RI Rec;
buffer Buf;
};
}
$ rcc -l c++ inclrec.jr testrec.jr
#ifndef _INCLREC_JR_HH_
#define _INCLREC_JR_HH_
#include "recordio.hh"
namespace inclrec {
class RI : public hadoop::Record {
private:
int32_t I32;
double D;
std::string S;
public:
RI(void);
virtual ~RI(void);
virtual bool operator==(const RI& peer) const;
virtual bool operator<(const RI& peer) const;
virtual int32_t getI32(void) const { return I32; }
virtual void setI32(int32_t v) { I32 = v; }
virtual double getD(void) const { return D; }
virtual void setD(double v) { D = v; }
virtual std::string& getS(void) const { return S; }
virtual const std::string& getS(void) const { return S; }
virtual std::string type(void) const;
virtual std::string signature(void) const;
protected:
virtual void serialize(hadoop::OArchive& a) const;
virtual void deserialize(hadoop::IArchive& a);
};
} // end namespace inclrec
#endif /* _INCLREC_JR_HH_ */
#ifndef _TESTREC_JR_HH_
#define _TESTREC_JR_HH_
#include "inclrec.jr.hh"
namespace testrec {
class R : public hadoop::Record {
private:
std::vector VF;
inclrec::RI Rec;
std::string Buf;
public:
R(void);
virtual ~R(void);
virtual bool operator==(const R& peer) const;
virtual bool operator<(const R& peer) const;
virtual std::vector& getVF(void) const;
virtual const std::vector& getVF(void) const;
virtual std::string& getBuf(void) const ;
virtual const std::string& getBuf(void) const;
virtual inclrec::RI& getRec(void) const;
virtual const inclrec::RI& getRec(void) const;
virtual bool serialize(hadoop::OutArchive& a) const;
virtual bool deserialize(hadoop::InArchive& a);
virtual std::string type(void) const;
virtual std::string signature(void) const;
};
}; // end namespace testrec
#endif /* _TESTREC_JR_HH_ */
DDL Type C++ Type Java Type
boolean bool boolean
byte int8_t byte
int int32_t int
long int64_t long
float float float
double double double
ustring std::string java.lang.String
buffer std::string org.apache.hadoop.record.Buffer
class type class type class type
vector std::vector java.util.ArrayList
map std::map java.util.TreeMap
record = primitive / struct / vector / map
primitive = boolean / int / long / float / double / ustring / buffer
boolean = "T" / "F"
int = ["-"] 1*DIGIT
long = ";" ["-"] 1*DIGIT
float = ["-"] 1*DIGIT "." 1*DIGIT ["E" / "e" ["-"] 1*DIGIT]
double = ";" ["-"] 1*DIGIT "." 1*DIGIT ["E" / "e" ["-"] 1*DIGIT]
ustring = "'" *(UTF8 char except NULL, LF, % and , / "%00" / "%0a" / "%25" / "%2c" )
buffer = "#" *(BYTE except NULL, LF, % and , / "%00" / "%0a" / "%25" / "%2c" )
struct = "s{" record *("," record) "}"
vector = "v{" [record *("," record)] "}"
map = "m{" [*(record "," record)] "}"
class {
int MY_INT; // value 5
vector MY_VEC; // values 0.1, -0.89, 2.45e4
buffer MY_BUF; // value '\00\n\tabc%'
}
<value>
<struct>
<member>
<name>MY_INT</name>
<value><i4>5</i4></value>
</member>
<member>
<name>MY_VEC</name>
<value>
<array>
<data>
<value><ex:float>0.1</ex:float></value>
<value><ex:float>-0.89</ex:float></value>
<value><ex:float>2.45e4</ex:float></value>
</data>
</array>
</value>
</member>
<member>
<name>MY_BUF</name>
<value><string>%00\n\tabc%25</string></value>
</member>
</struct>
</value>
DEPRECATED: Replaced by Avro.
]]> 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).
<recordcc
destdir="${basedir}/gensrc"
language="java">
<fileset include="**\/*.jr" />
</recordcc>
@deprecated Replaced by Avro.]]>
DEPRECATED: Replaced by Avro.
]]>null the default one will be used.]]>
null the default one will be used.
@param connConfigurator a connection configurator.]]>
TRUE if the token is transmitted in the
URL query string, FALSE if the delegation token is transmitted
using the {@link DelegationTokenAuthenticator#DELEGATION_TOKEN_HEADER} HTTP
header.]]>
FALSE if the delegation token is transmitted using the
{@link DelegationTokenAuthenticator#DELEGATION_TOKEN_HEADER} HTTP header.]]>
doAs parameter is not NULL,
the request will be done on behalf of the specified doAs user.
@param url the URL to connect to. Only HTTP/S URLs are supported.
@param token the authentication token being used for the user.
@param doAs user to do the the request on behalf of, if NULL the request is
as self.
@return an authenticated {@link HttpURLConnection}.
@throws IOException if an IO error occurred.
@throws AuthenticationException if an authentication exception occurred.]]>
AuthenticatedURL instances are not thread-safe.]]>
This permits implementations to change the configuration before the init operation. As the ServiceLauncher only creates an instance of the base {@link Configuration} class, it is recommended to instantiate any subclass (such as YarnConfiguration) that injects new resources.
@param config the initial configuration build up by the service launcher. @param args list of arguments passed to the command line after any launcher-specific commands have been stripped. @return the configuration to init the service with. Recommended: pass down the config parameter with any changes @throws Exception any problem]]>
If an exception is raised, the policy is:
Approximate HTTP equivalent: {@code 505: Version Not Supported}]]>
Many of the exit codes are designed to resemble HTTP error codes, squashed into a single byte. e.g 44 , "not found" is the equivalent of 404. The various 2XX HTTP error codes aren't followed; the Unix standard of "0" for success is used.
0-10: general command issues
30-39: equivalent to the 3XX responses, where those responses are
considered errors by the application.
40-49: client-side/CLI/config problems
50-59: service-side problems.
60+ : application specific error codes
]]>
If the last argument is a throwable, it becomes the cause of the exception. It will also be used as a parameter for the format. @param exitCode exit code @param format format for message to use in exception @param args list of arguments]]>
Progressable
to explicitly report progress to the Hadoop framework. This is especially
important for operations which take significant 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 of the given object.]]>
".sh" otherwise.
@param parent File parent directory
@param basename String script file basename
@return File referencing the script in the directory]]>
".sh" otherwise.
@param basename String script file basename
@return String script file name]]>
Shell
processes and destroys them one by one. This method is thread safe]]>
@deprecated use one of the exception-raising getter methods, specifically {@link #getWinUtilsPath()} or {@link #getWinUtilsFile()}]]>
du or
df. It also offers facilities to gate commands by
time-intervals.]]>
ShutdownHookManager singleton.]]>
TimeUnit]]>
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(MyMapper.class);
job.setReducerClass(MyReducer.class);
// Submit the job, then poll for progress until the job is complete
RunningJob runningJob = JobClient.runJob(job);
if (runningJob.isSuccessful()) {
return 0;
} else {
return 1;
}
}
public static void main(String[] args) throws Exception {
// Let ToolRunner handle generic command-line options
int res = ToolRunner.run(new Configuration(), new MyApp(), args);
System.exit(res);
}
}
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.]]>
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]]>
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]]>
Invariant: nothing happens if the specified key does not belong to this counter Bloom filter. @param key The key to remove.]]>
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.]]>
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]]>
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]]>
Invariant: if the false positive is null, nothing happens.
@param key The false positive key to add.]]>
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]]>