Java tutorial
/* * 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.ifesdjeen.cascading.cassandra.hadoop; import java.io.IOException; import java.net.InetAddress; import java.nio.ByteBuffer; import java.util.ArrayList; import java.util.Collections; import java.util.List; import java.util.Random; import java.util.SortedMap; import java.util.concurrent.Callable; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.util.concurrent.Future; import com.google.common.collect.ImmutableList; import org.apache.cassandra.db.IColumn; import org.apache.cassandra.dht.IPartitioner; import org.apache.cassandra.dht.Range; import org.apache.cassandra.dht.Token; import org.apache.cassandra.hadoop.ColumnFamilySplit; import org.apache.cassandra.hadoop.ConfigHelper; import org.apache.cassandra.thrift.Cassandra; import org.apache.cassandra.thrift.InvalidRequestException; import org.apache.cassandra.thrift.KeyRange; import org.apache.cassandra.thrift.TokenRange; import org.apache.commons.lang.StringUtils; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.mapred.*; 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.hadoop.mapreduce.TaskAttemptID; import org.apache.thrift.TException; import org.slf4j.Logger; import org.slf4j.LoggerFactory; /** * 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.setColumnFamily * ConfigHelper.setSlicePredicate * <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 InputFormat<ByteBuffer, SortedMap<ByteBuffer, IColumn>> implements org.apache.hadoop.mapred.InputFormat<ByteBuffer, SortedMap<ByteBuffer, IColumn>> { private static final Logger logger = LoggerFactory.getLogger(ColumnFamilyInputFormat.class); public static final String MAPRED_TASK_ID = "mapred.task.id"; // The simple fact that we need this is because the old Hadoop API wants us to "write" // to the key and value whereas the new asks for it. // I choose 8kb as the default max key size (instanciated only once), but you can // override it in your jobConf with this setting. public static final String CASSANDRA_HADOOP_MAX_KEY_SIZE = "cassandra.hadoop.max_key_size"; public static final int CASSANDRA_HADOOP_MAX_KEY_SIZE_DEFAULT = 8192; private String keyspace; private String cfName; private IPartitioner partitioner; private static void validateConfiguration(Configuration conf) { if (ConfigHelper.getInputKeyspace(conf) == null || ConfigHelper.getInputColumnFamily(conf) == null) { throw new UnsupportedOperationException( "you must set the keyspace and columnfamily with setColumnFamily()"); } if (ConfigHelper.getInputSlicePredicate(conf) == null) { throw new UnsupportedOperationException("you must set the predicate with setPredicate"); } if (ConfigHelper.getInputInitialAddress(conf) == null) throw new UnsupportedOperationException("You must set the initial output address to a Cassandra node"); if (ConfigHelper.getInputPartitioner(conf) == null) throw new UnsupportedOperationException("You must set the Cassandra partitioner class"); } public List<InputSplit> getSplits(JobContext context) throws IOException { Configuration conf = context.getConfiguration(); validateConfiguration(conf); // cannonical ranges and nodes holding replicas List<TokenRange> masterRangeNodes = getRangeMap(conf); keyspace = ConfigHelper.getInputKeyspace(context.getConfiguration()); cfName = ConfigHelper.getInputColumnFamily(context.getConfiguration()); partitioner = ConfigHelper.getInputPartitioner(context.getConfiguration()); logger.debug("partitioner is " + partitioner); // cannonical ranges, split into pieces, fetching the splits in parallel ExecutorService executor = Executors.newCachedThreadPool(); List<InputSplit> splits = new ArrayList<InputSplit>(); try { List<Future<List<InputSplit>>> splitfutures = new ArrayList<Future<List<InputSplit>>>(); KeyRange jobKeyRange = ConfigHelper.getInputKeyRange(conf); Range<Token> jobRange = null; if (jobKeyRange != null && jobKeyRange.start_token != null) { assert partitioner .preservesOrder() : "ConfigHelper.setInputKeyRange(..) can only be used with a order preserving paritioner"; assert jobKeyRange.start_key == null : "only start_token supported"; assert jobKeyRange.end_key == null : "only end_token supported"; jobRange = new Range<Token>(partitioner.getTokenFactory().fromString(jobKeyRange.start_token), partitioner.getTokenFactory().fromString(jobKeyRange.end_token), partitioner); } for (TokenRange range : masterRangeNodes) { if (jobRange == null) { // for each range, pick a live owner and ask it to compute bite-sized splits splitfutures.add(executor.submit(new SplitCallable(range, conf))); } else { Range<Token> dhtRange = new Range<Token>( partitioner.getTokenFactory().fromString(range.start_token), partitioner.getTokenFactory().fromString(range.end_token), partitioner); if (dhtRange.intersects(jobRange)) { for (Range<Token> intersection : dhtRange.intersectionWith(jobRange)) { range.start_token = partitioner.getTokenFactory().toString(intersection.left); range.end_token = partitioner.getTokenFactory().toString(intersection.right); // for each range, pick a live owner and ask it to compute bite-sized splits splitfutures.add(executor.submit(new SplitCallable(range, conf))); } } } } // wait until we have all the results back for (Future<List<InputSplit>> futureInputSplits : splitfutures) { try { splits.addAll(futureInputSplits.get()); } catch (Exception e) { throw new IOException("Could not get input splits", e); } } } finally { executor.shutdownNow(); } assert splits.size() > 0; Collections.shuffle(splits, new Random(System.nanoTime())); return splits; } /** * Gets a token range and splits it up according to the suggested * size into input splits that Hadoop can use. */ class SplitCallable implements Callable<List<InputSplit>> { private final TokenRange range; private final Configuration conf; public SplitCallable(TokenRange tr, Configuration conf) { this.range = tr; this.conf = conf; } public List<InputSplit> call() throws Exception { ArrayList<InputSplit> splits = new ArrayList<InputSplit>(); List<String> tokens = getSubSplits(keyspace, cfName, range, conf); assert range.rpc_endpoints.size() == range.endpoints .size() : "rpc_endpoints size must match endpoints size"; // turn the sub-ranges into InputSplits String[] endpoints = range.endpoints.toArray(new String[range.endpoints.size()]); // hadoop needs hostname, not ip int endpointIndex = 0; for (String endpoint : range.rpc_endpoints) { String endpoint_address = endpoint; if (endpoint_address == null || endpoint_address.equals("0.0.0.0")) endpoint_address = range.endpoints.get(endpointIndex); endpoints[endpointIndex++] = InetAddress.getByName(endpoint_address).getHostName(); } Token.TokenFactory factory = partitioner.getTokenFactory(); for (int i = 1; i < tokens.size(); i++) { Token left = factory.fromString(tokens.get(i - 1)); Token right = factory.fromString(tokens.get(i)); Range<Token> range = new Range<Token>(left, right, partitioner); List<Range<Token>> ranges = range.isWrapAround() ? range.unwrap() : ImmutableList.of(range); for (Range<Token> subrange : ranges) { ColumnFamilySplit split = new ColumnFamilySplit(factory.toString(subrange.left), factory.toString(subrange.right), endpoints); logger.debug("adding " + split); splits.add(split); } } return splits; } } private List<String> getSubSplits(String keyspace, String cfName, TokenRange range, Configuration conf) throws IOException { int splitsize = ConfigHelper.getInputSplitSize(conf); for (int i = 0; i < range.rpc_endpoints.size(); i++) { String host = range.rpc_endpoints.get(i); if (host == null || host.equals("0.0.0.0")) host = range.endpoints.get(i); try { Cassandra.Client client = ConfigHelper.createConnection(conf, host, ConfigHelper.getInputRpcPort(conf)); client.set_keyspace(keyspace); return client.describe_splits(cfName, range.start_token, range.end_token, splitsize); } catch (IOException e) { logger.debug("failed connect to endpoint " + host, e); } catch (TException e) { throw new RuntimeException(e); } catch (InvalidRequestException e) { throw new RuntimeException(e); } } throw new IOException("failed connecting to all endpoints " + StringUtils.join(range.endpoints, ",")); } private List<TokenRange> getRangeMap(Configuration conf) throws IOException { Cassandra.Client client = ConfigHelper.getClientFromInputAddressList(conf); List<TokenRange> map; try { map = client.describe_ring(ConfigHelper.getInputKeyspace(conf)); } catch (TException e) { throw new RuntimeException(e); } catch (InvalidRequestException e) { throw new RuntimeException(e); } return map; } public RecordReader<ByteBuffer, SortedMap<ByteBuffer, IColumn>> createRecordReader(InputSplit inputSplit, TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException { return new ColumnFamilyRecordReader(); } // // Old Hadoop API // public org.apache.hadoop.mapred.InputSplit[] getSplits(JobConf jobConf, int numSplits) throws IOException { TaskAttemptContext tac = new TaskAttemptContext(jobConf, new TaskAttemptID()); List<org.apache.hadoop.mapreduce.InputSplit> newInputSplits = this.getSplits(tac); org.apache.hadoop.mapred.InputSplit[] oldInputSplits = new org.apache.hadoop.mapred.InputSplit[newInputSplits .size()]; for (int i = 0; i < newInputSplits.size(); i++) oldInputSplits[i] = (ColumnFamilySplit) newInputSplits.get(i); return oldInputSplits; } public org.apache.hadoop.mapred.RecordReader<ByteBuffer, SortedMap<ByteBuffer, IColumn>> getRecordReader( org.apache.hadoop.mapred.InputSplit split, JobConf jobConf, final Reporter reporter) throws IOException { TaskAttemptContext tac = new TaskAttemptContext(jobConf, TaskAttemptID.forName(jobConf.get(MAPRED_TASK_ID))) { @Override public void progress() { reporter.progress(); } }; 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; } }