com.tuplejump.calliope.hadoop.ColumnFamilyInputFormat.java Source code

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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
 *
 *     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 com.tuplejump.calliope.hadoop;

import org.apache.cassandra.db.Column;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.TaskAttemptID;

import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.SortedMap;

/**
 * Hadoop InputFormat allowing map/reduce against Cassandra rows within one ColumnFamily.
 * <p/>
 * At minimum, you need to set the CF and predicate (description of columns to extract from each row)
 * in your Hadoop job Configuration.  The ConfigHelper class is provided to make this
 * simple:
 * ConfigHelper.setInputColumnFamily
 * ConfigHelper.setInputSlicePredicate
 * <p/>
 * You can also configure the number of rows per InputSplit with
 * ConfigHelper.setInputSplitSize
 * This should be "as big as possible, but no bigger."  Each InputSplit is read from Cassandra
 * with multiple get_slice_range queries, and the per-call overhead of get_slice_range is high,
 * so larger split sizes are better -- but if it is too large, you will run out of memory.
 * <p/>
 * The default split size is 64k rows.
 */
public class ColumnFamilyInputFormat
        extends AbstractColumnFamilyInputFormat<ByteBuffer, SortedMap<ByteBuffer, Column>> {

    public RecordReader<ByteBuffer, SortedMap<ByteBuffer, Column>> createRecordReader(InputSplit inputSplit,
            TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException {
        return new ColumnFamilyRecordReader();
    }

    public org.apache.hadoop.mapred.RecordReader<ByteBuffer, SortedMap<ByteBuffer, Column>> getRecordReader(
            org.apache.hadoop.mapred.InputSplit split, JobConf jobConf, final Reporter reporter)
            throws IOException {
        TaskAttemptContext tac = HadoopCompat.newMapContext(jobConf,
                TaskAttemptID.forName(jobConf.get(MAPRED_TASK_ID)), null, null, null, new ReporterWrapper(reporter),
                null);

        ColumnFamilyRecordReader recordReader = new ColumnFamilyRecordReader(
                jobConf.getInt(CASSANDRA_HADOOP_MAX_KEY_SIZE, CASSANDRA_HADOOP_MAX_KEY_SIZE_DEFAULT));
        recordReader.initialize((org.apache.hadoop.mapreduce.InputSplit) split, tac);
        return recordReader;
    }

    @Override
    protected void validateConfiguration(Configuration conf) {
        super.validateConfiguration(conf);

        if (ConfigHelper.getInputSlicePredicate(conf) == null) {
            throw new UnsupportedOperationException("you must set the predicate with setInputSlicePredicate");
        }
    }

}