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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 org.apache.mrql;
import org.apache.mrql.gen.*;
import java.io.*;
import java.util.Hashtable;
import java.util.Iterator;
import java.util.Enumeration;
import java.util.Map;
import org.apache.hadoop.fs.*;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.MultipleInputs;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
/** The MapReduce operation that uses an in-mapper combiner to partially reduce groups during mapping */
final public class MapReduceOperation extends MapReducePlan {
public final static class MRContainerPartitioner extends Partitioner<MRContainer,MRContainer> {
final public int getPartition ( MRContainer key, MRContainer value, int numPartitions ) {
return Math.abs(key.hashCode()) % numPartitions;
}
}
/** The mapper of the MapReduce operation */
private final static class MRMapper extends Mapper<MRContainer,MRContainer,MRContainer,MRContainer> {
private static Function map_fnc; // the map function
private static Function combine_fnc; // the combiner function
private static Hashtable<MRData,MRData> hashTable; // in-mapper combiner
private static int index;
private static Tuple tkey = new Tuple(2);
private static Bag tbag = new Bag(2);
private static MRContainer ckey = new MRContainer(new MR_int(0));
private static MRContainer cvalue = new MRContainer(new MR_int(0));
@Override
public void map ( MRContainer key, MRContainer value, Context context )
throws IOException, InterruptedException {
for ( MRData e: (Bag)map_fnc.eval(value.data()) ) {
Tuple p = (Tuple)e;
if (hashTable == null) {
ckey.set(p.first());
cvalue.set(p.second());
context.write(ckey,cvalue);
} else {
// in-mapper combiner
MRData old = hashTable.get(p.first());
if (old == null) {
if (index++ == Config.map_cache_size)
flush_table(context);
hashTable.put(p.first(),p.second());
} else {
tkey.set(0,p.first());
tbag.clear();
tbag.add_element(p.second()).add_element(old);
tkey.set(1,tbag);
for ( MRData x: (Bag)combine_fnc.eval(tkey) )
hashTable.put(p.first(),x); // normally, done once
}
}
}
}
private static void flush_table ( Context context ) throws IOException, InterruptedException {
for ( Map.Entry<MRData,MRData> me: hashTable.entrySet() ) {
ckey.set(me.getKey());
cvalue.set(me.getValue());
if (me.getValue() != null)
context.write(ckey,cvalue);
};
index = 0;
hashTable.clear();
}
@Override
protected void setup ( Context context ) throws IOException,InterruptedException {
super.setup(context);
try {
Configuration conf = context.getConfiguration();
Config.read(conf);
if (Plan.conf == null)
Plan.conf = conf;
Tree code = Tree.parse(conf.get("mrql.mapper"));
map_fnc = functional_argument(conf,code);
code = Tree.parse(conf.get("mrql.combiner"));
hashTable = null;
if (code != null && !code.equals(new VariableLeaf("null"))) {
combine_fnc = functional_argument(conf,code);
hashTable = new Hashtable<MRData,MRData>(Config.map_cache_size);
index = 0;
}
} catch (Exception e) {
throw new Error("Cannot retrieve the mapper plan");
}
}
@Override
protected void cleanup ( Context context ) throws IOException,InterruptedException {
if (hashTable != null)
flush_table(context);
hashTable = null; // garbage-collect it
super.cleanup(context);
}
}
/** The reducer of the MapReduce operation */
private final static class MRReducer extends Reducer<MRContainer,MRContainer,MRContainer,MRContainer> {
private static String counter; // a Hadoop user-defined counter used in the repeat operation
private static Function reduce_fnc; // the reduce function
private static Bag s = new Bag(); // a cached bag of input fragments
private static Function acc_fnc; // aggregator
private static MRData result; // aggregation result
private static boolean streamed = false;
private static Tuple pair = new Tuple(2);
private static MRContainer container = new MRContainer(new MR_int(0));
private void write ( MRContainer key, MRData value, Context context )
throws IOException, InterruptedException {
if (result != null) { // aggregation
pair.set(0,result);
pair.set(1,value);
result = acc_fnc.eval(pair);
} else if (counter.equals("-")) {
container.set(value);
context.write(key,container);
} else { // increment the repetition counter if the repeat condition is true
Tuple t = (Tuple)value;
if (((MR_bool)t.second()).get())
context.getCounter("mrql",counter).increment(1);
container.set(t.first());
context.write(key,container);
}
}
@Override
public void reduce ( MRContainer key, Iterable<MRContainer> values, Context context )
throws IOException, InterruptedException {
if (!streamed) { // store the values in a Bag and then reduce
s.clear();
for ( MRContainer val: values )
s.add(val.data());
pair.set(0,key.data());
pair.set(1,s);
for ( MRData e: (Bag)reduce_fnc.eval(pair) )
write(key,e,context);
} else { // it accesses the values in stream-like fashion
final Iterator<MRContainer> iterator = values.iterator();
Bag s = new Bag(new BagIterator() {
public boolean hasNext () {
return iterator.hasNext();
}
public MRData next () {
return iterator.next().data();
}
});
pair.set(0,key.data());
pair.set(1,s);
for ( MRData e: (Bag)reduce_fnc.eval(pair) )
write(key,e,context);
}
}
@Override
protected void setup ( Context context ) throws IOException,InterruptedException {
super.setup(context);
try {
conf = context.getConfiguration();
Plan.conf = conf;
Config.read(Plan.conf);
Tree code = Tree.parse(conf.get("mrql.reducer"));
reduce_fnc = functional_argument(conf,code);
streamed = PlanGeneration.streamed_MapReduce_reducer(code);
if (conf.get("mrql.zero") != null) {
code = Tree.parse(conf.get("mrql.zero"));
result = Interpreter.evalE(code);
code = Tree.parse(conf.get("mrql.accumulator"));
acc_fnc = functional_argument(conf,code);
} else result = null;
counter = conf.get("mrql.counter");
} catch (Exception e) {
throw new Error("Cannot retrieve the reduce plan");
}
}
@Override
protected void cleanup ( Context context ) throws IOException,InterruptedException {
if (result != null) // emit the result of aggregation
context.write(new MRContainer(new MR_int(0)),new MRContainer(result));
super.cleanup(context);
}
}
/**
* The MapReduce physical operator
* @param map_fnc the mapper function
* @param combine_fnc optional in-mapper combiner function
* @param reduce_fnc the reducer function
* @param acc_fnc optional accumulator function
* @param zero optional the zero value for the accumulator
* @param source the input data source
* @param num_reduces number of reducers
* @param stop_counter optional counter used in repeat operation
* @param orderp does the result need to be ordered?
* @return a new data source that contains the result
*/
public final static DataSet mapReduce ( Tree map_fnc, // mapper function
Tree combine_fnc, // optional in-mapper combiner function
Tree reduce_fnc, // reducer function
Tree acc_fnc, // optional accumulator function
Tree zero, // optional the zero value for the accumulator
DataSet source, // input data source
int num_reduces, // number of reducers
String stop_counter, // optional counter used in repeat operation
boolean orderp ) // does the result need to be ordered?
throws Exception {
conf = MapReduceEvaluator.clear_configuration(conf);
String newpath = new_path(conf);
conf.set("mrql.mapper",map_fnc.toString());
if (combine_fnc != null)
conf.set("mrql.combiner",combine_fnc.toString());
conf.set("mrql.reducer",reduce_fnc.toString());
if (zero != null) { // will use in-mapper combiner
conf.set("mrql.accumulator",acc_fnc.toString());
conf.set("mrql.zero",zero.toString());
} else conf.set("mrql.zero","");
conf.set("mrql.counter",stop_counter);
setupSplits(source,conf);
Job job = new Job(conf,newpath);
distribute_compiled_arguments(job.getConfiguration());
job.setJarByClass(MapReducePlan.class);
job.setOutputKeyClass(MRContainer.class);
job.setOutputValueClass(MRContainer.class);
job.setPartitionerClass(MRContainerPartitioner.class);
job.setSortComparatorClass(MRContainerKeyComparator.class);
job.setGroupingComparatorClass(MRContainerKeyComparator.class);
job.setOutputFormatClass(SequenceFileOutputFormat.class);
for (DataSource p: source.source)
MultipleInputs.addInputPath(job,new Path(p.path),(Class<? extends MapReduceMRQLFileInputFormat>)p.inputFormat,MRMapper.class);
FileOutputFormat.setOutputPath(job,new Path(newpath));
job.setReducerClass(MRReducer.class);
if (Config.trace && PlanGeneration.streamed_MapReduce_reducer(reduce_fnc))
System.out.println("Streamed MapReduce reducer");
if (num_reduces > 0)
job.setNumReduceTasks(num_reduces);
job.waitForCompletion(true);
long c = (stop_counter.equals("-")) ? 0
: job.getCounters().findCounter("mrql",stop_counter).getValue();
DataSource s = new BinaryDataSource(newpath,conf);
s.to_be_merged = orderp;
return new DataSet(s,c,outputRecords(job));
}
}