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This module contains implementations of InputFormat, OutputFormat, Mapper, Reducer, etc which
are needed for running MR jobs on tables, WALs, HFiles and other HBase specific constructs.
It also contains a bunch of tools: RowCounter, ImportTsv, Import, Export, CompactionTool,
ExportSnapshot, WALPlayer, etc
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.hbase.mapreduce;
import java.io.IOException;
import java.text.MessageFormat;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import org.apache.hadoop.hbase.HRegionInfo;
import org.apache.hadoop.hbase.HRegionLocation;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import org.apache.hadoop.hbase.client.RegionLocator;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.hbase.util.Pair;
import org.apache.hadoop.mapreduce.InputFormat;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.yetus.audience.InterfaceAudience;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* A base for {@link MultiTableInputFormat}s. Receives a list of {@link Scan} instances that define
* the input tables and filters etc. Subclasses may use other TableRecordReader implementations.
*/
@InterfaceAudience.Public
public abstract class MultiTableInputFormatBase
extends InputFormat {
private static final Logger LOG = LoggerFactory.getLogger(MultiTableInputFormatBase.class);
/** Holds the set of scans used to define the input. */
private List scans;
/** The reader scanning the table, can be a custom one. */
private TableRecordReader tableRecordReader = null;
/**
* Builds a TableRecordReader. If no TableRecordReader was provided, uses the default.
* @param split The split to work with.
* @param context The current context.
* @return The newly created record reader.
* @throws IOException When creating the reader fails.
* @throws InterruptedException when record reader initialization fails
* @see InputFormat#createRecordReader(InputSplit, TaskAttemptContext)
*/
@Override
public RecordReader createRecordReader(InputSplit split,
TaskAttemptContext context) throws IOException, InterruptedException {
TableSplit tSplit = (TableSplit) split;
LOG.info(MessageFormat.format("Input split length: {0} bytes.", tSplit.getLength()));
if (tSplit.getTable() == null) {
throw new IOException("Cannot create a record reader because of a"
+ " previous error. Please look at the previous logs lines from"
+ " the task's full log for more details.");
}
final Connection connection = ConnectionFactory.createConnection(context.getConfiguration());
Table table = connection.getTable(tSplit.getTable());
if (this.tableRecordReader == null) {
this.tableRecordReader = new TableRecordReader();
}
final TableRecordReader trr = this.tableRecordReader;
try {
Scan sc = tSplit.getScan();
sc.setStartRow(tSplit.getStartRow());
sc.setStopRow(tSplit.getEndRow());
trr.setScan(sc);
trr.setTable(table);
return new RecordReader() {
@Override
public void close() throws IOException {
trr.close();
connection.close();
}
@Override
public ImmutableBytesWritable getCurrentKey() throws IOException, InterruptedException {
return trr.getCurrentKey();
}
@Override
public Result getCurrentValue() throws IOException, InterruptedException {
return trr.getCurrentValue();
}
@Override
public float getProgress() throws IOException, InterruptedException {
return trr.getProgress();
}
@Override
public void initialize(InputSplit inputsplit, TaskAttemptContext context)
throws IOException, InterruptedException {
trr.initialize(inputsplit, context);
}
@Override
public boolean nextKeyValue() throws IOException, InterruptedException {
return trr.nextKeyValue();
}
};
} catch (IOException ioe) {
// If there is an exception make sure that all
// resources are closed and released.
trr.close();
connection.close();
throw ioe;
}
}
/**
* Calculates the splits that will serve as input for the map tasks. The number of splits matches
* the number of regions in a table.
* @param context The current job context.
* @return The list of input splits.
* @throws IOException When creating the list of splits fails.
* @see InputFormat#getSplits(org.apache.hadoop.mapreduce.JobContext)
*/
@Override
public List getSplits(JobContext context) throws IOException {
if (scans.isEmpty()) {
throw new IOException("No scans were provided.");
}
Map> tableMaps = new HashMap<>();
for (Scan scan : scans) {
byte[] tableNameBytes = scan.getAttribute(Scan.SCAN_ATTRIBUTES_TABLE_NAME);
if (tableNameBytes == null) throw new IOException("A scan object did not have a table name");
TableName tableName = TableName.valueOf(tableNameBytes);
List scanList = tableMaps.get(tableName);
if (scanList == null) {
scanList = new ArrayList<>();
tableMaps.put(tableName, scanList);
}
scanList.add(scan);
}
List splits = new ArrayList<>();
Iterator iter = tableMaps.entrySet().iterator();
// Make a single Connection to the Cluster and use it across all tables.
try (Connection conn = ConnectionFactory.createConnection(context.getConfiguration())) {
while (iter.hasNext()) {
Map.Entry> entry = (Map.Entry>) iter.next();
TableName tableName = entry.getKey();
List scanList = entry.getValue();
try (Table table = conn.getTable(tableName);
RegionLocator regionLocator = conn.getRegionLocator(tableName)) {
RegionSizeCalculator sizeCalculator =
new RegionSizeCalculator(regionLocator, conn.getAdmin());
Pair keys = regionLocator.getStartEndKeys();
for (Scan scan : scanList) {
if (keys == null || keys.getFirst() == null || keys.getFirst().length == 0) {
throw new IOException(
"Expecting at least one region for table : " + tableName.getNameAsString());
}
int count = 0;
byte[] startRow = scan.getStartRow();
byte[] stopRow = scan.getStopRow();
for (int i = 0; i < keys.getFirst().length; i++) {
if (!includeRegionInSplit(keys.getFirst()[i], keys.getSecond()[i])) {
continue;
}
if (
(startRow.length == 0 || keys.getSecond()[i].length == 0
|| Bytes.compareTo(startRow, keys.getSecond()[i]) < 0)
&& (stopRow.length == 0 || Bytes.compareTo(stopRow, keys.getFirst()[i]) > 0)
) {
byte[] splitStart =
startRow.length == 0 || Bytes.compareTo(keys.getFirst()[i], startRow) >= 0
? keys.getFirst()[i]
: startRow;
byte[] splitStop =
(stopRow.length == 0 || Bytes.compareTo(keys.getSecond()[i], stopRow) <= 0)
&& keys.getSecond()[i].length > 0 ? keys.getSecond()[i] : stopRow;
HRegionLocation hregionLocation =
regionLocator.getRegionLocation(keys.getFirst()[i], false);
String regionHostname = hregionLocation.getHostname();
HRegionInfo regionInfo = hregionLocation.getRegionInfo();
String encodedRegionName = regionInfo.getEncodedName();
long regionSize = sizeCalculator.getRegionSize(regionInfo.getRegionName());
TableSplit split = new TableSplit(table.getName(), scan, splitStart, splitStop,
regionHostname, encodedRegionName, regionSize);
splits.add(split);
if (LOG.isDebugEnabled()) {
LOG.debug("getSplits: split -> " + (count++) + " -> " + split);
}
}
}
}
}
}
}
return splits;
}
/**
* Test if the given region is to be included in the InputSplit while splitting the regions of a
* table.
*
* This optimization is effective when there is a specific reasoning to exclude an entire region
* from the M-R job, (and hence, not contributing to the InputSplit), given the start and end keys
* of the same.
* Useful when we need to remember the last-processed top record and revisit the [last, current)
* interval for M-R processing, continuously. In addition to reducing InputSplits, reduces the
* load on the region server as well, due to the ordering of the keys.
*
* Note: It is possible that endKey.length() == 0 , for the last (recent) region.
*
* Override this method, if you want to bulk exclude regions altogether from M-R. By default, no
* region is excluded( i.e. all regions are included).
* @param startKey Start key of the region
* @param endKey End key of the region
* @return true, if this region needs to be included as part of the input (default).
*/
protected boolean includeRegionInSplit(final byte[] startKey, final byte[] endKey) {
return true;
}
/**
* Allows subclasses to get the list of {@link Scan} objects.
*/
protected List getScans() {
return this.scans;
}
/**
* Allows subclasses to set the list of {@link Scan} objects.
* @param scans The list of {@link Scan} used to define the input
*/
protected void setScans(List scans) {
this.scans = scans;
}
/**
* Allows subclasses to set the {@link TableRecordReader}.
* @param tableRecordReader A different {@link TableRecordReader} implementation.
*/
protected void setTableRecordReader(TableRecordReader tableRecordReader) {
this.tableRecordReader = tableRecordReader;
}
}