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Apache Accumulo MapReduce bindings.
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/*
* 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
*
* https://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.accumulo.hadoop.mapreduce;
import java.io.IOException;
import java.util.List;
import java.util.Map.Entry;
import org.apache.accumulo.core.client.RowIterator;
import org.apache.accumulo.core.data.Key;
import org.apache.accumulo.core.data.Value;
import org.apache.accumulo.core.util.PeekingIterator;
import org.apache.accumulo.hadoopImpl.mapreduce.AccumuloRecordReader;
import org.apache.accumulo.hadoopImpl.mapreduce.InputFormatBuilderImpl;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.InputFormat;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
/**
* This class allows MapReduce jobs to use Accumulo as the source of data. This {@link InputFormat}
* provides row names as {@link Text} as keys, and a corresponding {@link PeekingIterator} as a
* value, which in turn makes the {@link Key}/{@link Value} pairs for that row available to the Map
* function. Configure the job using the {@link #configure()} method, which provides a fluent API.
* For Example:
*
*
* AccumuloRowInputFormat.configure().clientProperties(props).table(name) // required
* .auths(auths).addIterator(iter1).ranges(ranges).fetchColumns(columns).executionHints(hints)
* .samplerConfiguration(sampleConf).autoAdjustRanges(false) // enabled by default
* .scanIsolation(true) // not available with batchScan()
* .offlineScan(true) // not available with batchScan()
* .store(job);
*
*
* For descriptions of all options see
* {@link org.apache.accumulo.hadoop.mapreduce.InputFormatBuilder.InputFormatOptions}
*
* @since 2.0
*/
public class AccumuloRowInputFormat extends InputFormat>> {
private static final Class CLASS = AccumuloRowInputFormat.class;
@Override
public RecordReader>> createRecordReader(InputSplit split,
TaskAttemptContext context) {
return new AccumuloRecordReader<>(CLASS) {
RowIterator rowIterator;
@Override
public void initialize(InputSplit inSplit, TaskAttemptContext attempt) throws IOException {
super.initialize(inSplit, attempt);
rowIterator = new RowIterator(scannerIterator);
currentK = new Text();
currentV = null;
}
@Override
public boolean nextKeyValue() {
if (!rowIterator.hasNext()) {
return false;
}
currentV = new PeekingIterator<>(rowIterator.next());
numKeysRead = rowIterator.getKVCount();
currentKey = currentV.peek().getKey();
currentK = new Text(currentKey.getRow());
return true;
}
};
}
/**
* Gets the splits of the tables that have been set on the job by reading the metadata table for
* the specified ranges.
*
* @return the splits from the tables based on the ranges.
* @throws java.io.IOException if a table set on the job doesn't exist or an error occurs
* initializing the tablet locator
*/
@Override
public List getSplits(JobContext context) throws IOException {
return AccumuloRecordReader.getSplits(context, CLASS);
}
/**
* Sets all the information required for this map reduce job.
*/
public static InputFormatBuilder.ClientParams configure() {
return new InputFormatBuilderImpl<>(CLASS);
}
}