package org.apache.cassandra.hadoop;
/*
*
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* 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
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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.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.
*
* 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
*
* 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.
*
* 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(host, ConfigHelper.getInputRpcPort(conf), true);
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;
}
}