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+/**
+Provides HBase MapReduce
+Input/OutputFormats, a table indexing MapReduce job, and utility
+
+ HBase, MapReduce and the CLASSPATH
+
+MapReduce jobs deployed to a MapReduce cluster do not by default have access
+to the HBase configuration under $HBASE_CONF_DIR nor to HBase classes.
+You could add hbase-site.xml to $HADOOP_HOME/conf and add
+hbase-X.X.X.jar
+to the $HADOOP_HOME/lib and copy these changes across your cluster but the
+cleanest means of adding hbase configuration and classes to the cluster
+CLASSPATH
+is by uncommenting HADOOP_CLASSPATH in $HADOOP_HOME/conf/hadoop-env.sh
+and adding the path to the hbase jar and $HBASE_CONF_DIR directory.
+Then copy the amended configuration around the cluster.
+You'll probably need to restart the MapReduce cluster if you want it to notice
+the new configuration (You may not have to).
+
+
+For example, here is how you would amend hadoop-env.sh adding
+the hbase jar, conf, and the PerformanceEvaluation class from hbase test
+classes to the hadoop CLASSPATH
+
+# Extra Java CLASSPATH elements. Optional.
+# export HADOOP_CLASSPATH=
+export HADOOP_CLASSPATH=$HBASE_HOME/build/test:$HBASE_HOME/build/hbase-X.X.X.jar:$HBASE_HOME/conf
+
+Expand $HBASE_HOME appropriately in the in accordance with your local environment.
+
+This is how you would run the PerformanceEvaluation MR job to put up 4 clients:
+
+
$HADOOP_HOME/bin/hadoop org.apache.hadoop.hbase.PerformanceEvaluation sequentialWrite 4
+
+The PerformanceEvaluation class wil be found on the CLASSPATH because you added $HBASE_HOME/build/test to HADOOP_CLASSPATH
+
+
+HBase as MapReduce job data source and sink
+
+HBase can be used as a data source, {@link org.apache.hadoop.hbase.mapred.TableInputFormat TableInputFormat},
+and data sink, {@link org.apache.hadoop.hbase.mapred.TableOutputFormat TableOutputFormat}, for MapReduce jobs.
+Writing MapReduce jobs that read or write HBase, you'll probably want to subclass
+{@link org.apache.hadoop.hbase.mapred.TableMap TableMap} and/or
+{@link org.apache.hadoop.hbase.mapred.TableReduce TableReduce}. See the do-nothing
+pass-through classes {@link org.apache.hadoop.hbase.mapred.IdentityTableMap IdentityTableMap} and
+{@link org.apache.hadoop.hbase.mapred.IdentityTableReduce IdentityTableReduce} for basic usage. For a more
+involved example, see {@link org.apache.hadoop.hbase.mapred.BuildTableIndex BuildTableIndex}
+or review the org.apache.hadoop.hbase.mapred.TestTableMapReduce unit test.
+
+
+Running mapreduce jobs that have hbase as source or sink, you'll need to
+specify source/sink table and column names in your configuration.
+
+Reading from hbase, the !TableInputFormat asks hbase for the list of
+regions and makes a map-per-region. Writing, its better to have lots of
+reducers so load is spread across the hbase cluster.
+
+
+ Sample MR Bulk Uploader
+Read the class comment below for specification of inputs, prerequisites, etc.
+
+package org.apache.hadoop.hbase.mapred;
+
+import java.io.IOException;
+import java.util.Iterator;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
+import org.apache.hadoop.io.LongWritable;
+import org.apache.hadoop.io.MapWritable;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.mapred.JobClient;
+import org.apache.hadoop.mapred.JobConf;
+import org.apache.hadoop.mapred.MapReduceBase;
+import org.apache.hadoop.mapred.Mapper;
+import org.apache.hadoop.mapred.OutputCollector;
+import org.apache.hadoop.mapred.Reporter;
+import org.apache.hadoop.util.Tool;
+import org.apache.hadoop.util.ToolRunner;
+
+/**
+ * Sample uploader.
+ *
+ * This is EXAMPLE code. You will need to change it to work for your context.
+ *
+ * Uses TableReduce to put the data into hbase. Change the InputFormat to suit
+ * your data. Use the map to massage the input so it fits hbase. Currently its
+ * just a pass-through map. In the reduce, you need to output a row and a
+ * map of columns to cells. Change map and reduce to suit your input.
+ *
+ * <p>The below is wired up to handle an input whose format is a text file
+ * which has a line format as follow:
+ * <pre>
+ * row columnname columndata
+ * </pre>
+ *
+ * <p>The table and columnfamily we're to insert into must preexist.
+ *
+ * <p> To run, edit your hadoop-env.sh and add hbase classes and conf to your
+ * HADOOP_CLASSPATH. For example:
+ * <pre>
+ * export HADOOP_CLASSPATH=/Users/stack/Documents/checkouts/hbase/branches/0.1/build/classes:/Users/stack/Documents/checkouts/hbase/branches/0.1/conf
+ * </pre>
+ * <p>Restart your MR cluster after making the following change (You need to
+ * be running in pseudo-distributed mode at a minimum for the hadoop to see
+ * the above additions to your CLASSPATH).
+ *
+ * <p>Start up your hbase cluster.
+ *
+ * <p>Next do the following to start the MR job:
+ * <pre>
+ * ./bin/hadoop org.apache.hadoop.hbase.mapred.SampleUploader /tmp/input.txt TABLE_NAME
+ * </pre>
+ *
+ * <p>This code was written against hbase 0.1 branch.
+ *'
+public class SampleUploader extends MapReduceBase
+implements Mapper, Tool {
+ private static final String NAME = "SampleUploader";
+ private Configuration conf;
+
+ public JobConf createSubmittableJob(String[] args) {
+ JobConf c = new JobConf(getConf(), SampleUploader.class);
+ c.setJobName(NAME);
+ c.setInputPath(new Path(args[0]));
+ c.setMapperClass(this.getClass());
+ c.setMapOutputKeyClass(Text.class);
+ c.setMapOutputValueClass(MapWritable.class);
+ c.setReducerClass(TableUploader.class);
+ TableReduce.initJob(args[1], TableUploader.class, c);
+ return c;
+ }
+
+ public void map(LongWritable k, Text v,
+ OutputCollector output, Reporter r)
+ throws IOException {
+ // Lines are space-delimited; first item is row, next the columnname and
+ // then the third the cell value.
+ String tmp = v.toString();
+ if (tmp.length() == 0) {
+ return;
+ }
+ String [] splits = v.toString().split(" ");
+ MapWritable mw = new MapWritable();
+ mw.put(new Text(splits[1]),
+ new ImmutableBytesWritable(splits[2].getBytes()));
+ String row = splits[0];
+ r.setStatus("Map emitting " + row + " for record " + k.toString());
+ output.collect(new Text(row), mw);
+ }
+
+ public static class TableUploader
+ extends TableReduce<Text, MapWritable> {
+ @Override
+ public void reduce(Text k, Iterator v,
+ OutputCollector output, Reporter r)
+ throws IOException {
+ while (v.hasNext()) {
+ r.setStatus("Reducer committing " + k);
+ output.collect(k, v.next());
+ }
+ }
+ }
+
+ static int printUsage() {
+ System.out.println(NAME + "<input> <table_name>");
+ return -1;
+ }
+
+ public int run(@SuppressWarnings("unused") String[] args) throws Exception {
+ // Make sure there are exactly 2 parameters left.
+ if (args.length != 2) {
+ System.out.println("ERROR: Wrong number of parameters: " +
+ args.length + " instead of 2.");
+ return printUsage();
+ }
+ JobClient.runJob(createSubmittableJob(args));
+ return 0;
+ }
+
+ public Configuration getConf() {
+ return this.conf;
+ }
+
+ public void setConf(final Configuration c) {
+ this.conf = c;
+ }
+
+ public static void main(String[] args) throws Exception {
+ int errCode = ToolRunner.run(new Configuration(), new SampleUploader(),
+ args);
+ System.exit(errCode);
+ }
+}
+
+*/
+package org.apache.hadoop.hbase.mapred;