Class MultiTableSnapshotInputFormat

java.lang.Object
org.apache.hadoop.hbase.mapred.TableSnapshotInputFormat
org.apache.hadoop.hbase.mapred.MultiTableSnapshotInputFormat
All Implemented Interfaces:
org.apache.hadoop.mapred.InputFormat<ImmutableBytesWritable,Result>

@Public public class MultiTableSnapshotInputFormat extends TableSnapshotInputFormat implements org.apache.hadoop.mapred.InputFormat<ImmutableBytesWritable,Result>
MultiTableSnapshotInputFormat generalizes TableSnapshotInputFormat allowing a MapReduce job to run over one or more table snapshots, with one or more scans configured for each. Internally, the input format delegates to TableSnapshotInputFormat and thus has the same performance advantages; see TableSnapshotInputFormat for more details. Usage is similar to TableSnapshotInputFormat, with the following exception: initMultiTableSnapshotMapperJob takes in a map from snapshot name to a collection of scans. For each snapshot in the map, each corresponding scan will be applied; the overall dataset for the job is defined by the concatenation of the regions and tables included in each snapshot/scan pair. TableMapReduceUtil.initMultiTableSnapshotMapperJob(Map, Class, Class, Class, JobConf, boolean, Path) can be used to configure the job.
 
 Job job = new Job(conf);
 Map<String, Collection<Scan>> snapshotScans = ImmutableMap.of(
    "snapshot1", ImmutableList.of(new Scan(Bytes.toBytes("a"), Bytes.toBytes("b"))),
    "snapshot2", ImmutableList.of(new Scan(Bytes.toBytes("1"), Bytes.toBytes("2")))
 );
 Path restoreDir = new Path("/tmp/snapshot_restore_dir")
 TableMapReduceUtil.initTableSnapshotMapperJob(
     snapshotScans, MyTableMapper.class, MyMapKeyOutput.class,
      MyMapOutputValueWritable.class, job, true, restoreDir);
 
 
Internally, this input format restores each snapshot into a subdirectory of the given tmp directory. Input splits and record readers are created as described in TableSnapshotInputFormat (one per region). See TableSnapshotInputFormat for more notes on permissioning; the same caveats apply here.
See Also: