/*
* 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.flink.api.java.hadoop.mapreduce;
import org.apache.flink.annotation.Internal;
import org.apache.flink.api.common.io.FileInputFormat.FileBaseStatistics;
import org.apache.flink.api.common.io.LocatableInputSplitAssigner;
import org.apache.flink.api.common.io.statistics.BaseStatistics;
import org.apache.flink.api.java.hadoop.common.HadoopInputFormatCommonBase;
import org.apache.flink.api.java.hadoop.mapreduce.utils.HadoopUtils;
import org.apache.flink.api.java.hadoop.mapreduce.wrapper.HadoopInputSplit;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.core.fs.FileStatus;
import org.apache.flink.core.fs.FileSystem;
import org.apache.flink.core.fs.Path;
import org.apache.flink.core.io.InputSplitAssigner;
import org.apache.flink.util.Preconditions;
import org.apache.hadoop.conf.Configurable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.JobID;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.TaskAttemptID;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.security.Credentials;
import org.apache.hadoop.security.UserGroupInformation;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.util.ArrayList;
import java.util.List;
/**
* Base class shared between the Java and Scala API of Flink
*/
@Internal
public abstract class HadoopInputFormatBase<K, V, T> extends HadoopInputFormatCommonBase<T, HadoopInputSplit> {
private static final long serialVersionUID = 1L;
private static final Logger LOG = LoggerFactory.getLogger(HadoopInputFormatBase.class);
// Mutexes to avoid concurrent operations on Hadoop InputFormats.
// Hadoop parallelizes tasks across JVMs which is why they might rely on this JVM isolation.
// In contrast, Flink parallelizes using Threads, so multiple Hadoop InputFormat instances
// might be used in the same JVM.
private static final Object OPEN_MUTEX = new Object();
private static final Object CONFIGURE_MUTEX = new Object();
private static final Object CLOSE_MUTEX = new Object();
// NOTE: this class is using a custom serialization logic, without a defaultWriteObject() method.
// Hence, all fields here are "transient".
private org.apache.hadoop.mapreduce.InputFormat<K, V> mapreduceInputFormat;
protected Class<K> keyClass;
protected Class<V> valueClass;
private org.apache.hadoop.conf.Configuration configuration;
protected transient RecordReader<K, V> recordReader;
protected boolean fetched = false;
protected boolean hasNext;
public HadoopInputFormatBase(org.apache.hadoop.mapreduce.InputFormat<K, V> mapreduceInputFormat, Class<K> key, Class<V> value, Job job) {
super(Preconditions.checkNotNull(job, "Job can not be null").getCredentials());
this.mapreduceInputFormat = Preconditions.checkNotNull(mapreduceInputFormat);
this.keyClass = Preconditions.checkNotNull(key);
this.valueClass = Preconditions.checkNotNull(value);
this.configuration = job.getConfiguration();
HadoopUtils.mergeHadoopConf(configuration);
}
public org.apache.hadoop.conf.Configuration getConfiguration() {
return this.configuration;
}
// --------------------------------------------------------------------------------------------
// InputFormat
// --------------------------------------------------------------------------------------------
@Override
public void configure(Configuration parameters) {
// enforce sequential configuration() calls
synchronized (CONFIGURE_MUTEX) {
if (mapreduceInputFormat instanceof Configurable) {
((Configurable) mapreduceInputFormat).setConf(configuration);
}
}
}
@Override
public BaseStatistics getStatistics(BaseStatistics cachedStats) throws IOException {
// only gather base statistics for FileInputFormats
if (!(mapreduceInputFormat instanceof FileInputFormat)) {
return null;
}
JobContext jobContext;
try {
jobContext = HadoopUtils.instantiateJobContext(configuration, null);
} catch (Exception e) {
throw new RuntimeException(e);
}
final FileBaseStatistics cachedFileStats = (cachedStats != null && cachedStats instanceof FileBaseStatistics) ?
(FileBaseStatistics) cachedStats : null;
try {
final org.apache.hadoop.fs.Path[] paths = FileInputFormat.getInputPaths(jobContext);
return getFileStats(cachedFileStats, paths, new ArrayList<FileStatus>(1));
} catch (IOException ioex) {
if (LOG.isWarnEnabled()) {
LOG.warn("Could not determine statistics due to an io error: "
+ ioex.getMessage());
}
} catch (Throwable t) {
if (LOG.isErrorEnabled()) {
LOG.error("Unexpected problem while getting the file statistics: "
+ t.getMessage(), t);
}
}
// no statistics available
return null;
}
@Override
public HadoopInputSplit[] createInputSplits(int minNumSplits)
throws IOException {
configuration.setInt("mapreduce.input.fileinputformat.split.minsize", minNumSplits);
JobContext jobContext;
try {
jobContext = HadoopUtils.instantiateJobContext(configuration, new JobID());
} catch (Exception e) {
throw new RuntimeException(e);
}
jobContext.getCredentials().addAll(this.credentials);
Credentials currentUserCreds = getCredentialsFromUGI(UserGroupInformation.getCurrentUser());
if (currentUserCreds != null) {
jobContext.getCredentials().addAll(currentUserCreds);
}
List<org.apache.hadoop.mapreduce.InputSplit> splits;
try {
splits = this.mapreduceInputFormat.getSplits(jobContext);
} catch (InterruptedException e) {
throw new IOException("Could not get Splits.", e);
}
HadoopInputSplit[] hadoopInputSplits = new HadoopInputSplit[splits.size()];
for (int i = 0; i < hadoopInputSplits.length; i++) {
hadoopInputSplits[i] = new HadoopInputSplit(i, splits.get(i), jobContext);
}
return hadoopInputSplits;
}
@Override
public InputSplitAssigner getInputSplitAssigner(HadoopInputSplit[] inputSplits) {
return new LocatableInputSplitAssigner(inputSplits);
}
@Override
public void open(HadoopInputSplit split) throws IOException {
// enforce sequential open() calls
synchronized (OPEN_MUTEX) {
TaskAttemptContext context;
try {
context = HadoopUtils.instantiateTaskAttemptContext(configuration, new TaskAttemptID());
} catch (Exception e) {
throw new RuntimeException(e);
}
try {
this.recordReader = this.mapreduceInputFormat
.createRecordReader(split.getHadoopInputSplit(), context);
this.recordReader.initialize(split.getHadoopInputSplit(), context);
} catch (InterruptedException e) {
throw new IOException("Could not create RecordReader.", e);
} finally {
this.fetched = false;
}
}
}
@Override
public boolean reachedEnd() throws IOException {
if (!this.fetched) {
fetchNext();
}
return !this.hasNext;
}
protected void fetchNext() throws IOException {
try {
this.hasNext = this.recordReader.nextKeyValue();
} catch (InterruptedException e) {
throw new IOException("Could not fetch next KeyValue pair.", e);
} finally {
this.fetched = true;
}
}
@Override
public void close() throws IOException {
if (this.recordReader != null) {
// enforce sequential close() calls
synchronized (CLOSE_MUTEX) {
this.recordReader.close();
}
}
}
// --------------------------------------------------------------------------------------------
// Helper methods
// --------------------------------------------------------------------------------------------
private FileBaseStatistics getFileStats(FileBaseStatistics cachedStats, org.apache.hadoop.fs.Path[] hadoopFilePaths,
ArrayList<FileStatus> files) throws IOException {
long latestModTime = 0L;
// get the file info and check whether the cached statistics are still valid.
for (org.apache.hadoop.fs.Path hadoopPath : hadoopFilePaths) {
final Path filePath = new Path(hadoopPath.toUri());
final FileSystem fs = FileSystem.get(filePath.toUri());
final FileStatus file = fs.getFileStatus(filePath);
latestModTime = Math.max(latestModTime, file.getModificationTime());
// enumerate all files and check their modification time stamp.
if (file.isDir()) {
FileStatus[] fss = fs.listStatus(filePath);
files.ensureCapacity(files.size() + fss.length);
for (FileStatus s : fss) {
if (!s.isDir()) {
files.add(s);
latestModTime = Math.max(s.getModificationTime(), latestModTime);
}
}
} else {
files.add(file);
}
}
// check whether the cached statistics are still valid, if we have any
if (cachedStats != null && latestModTime <= cachedStats.getLastModificationTime()) {
return cachedStats;
}
// calculate the whole length
long len = 0;
for (FileStatus s : files) {
len += s.getLen();
}
// sanity check
if (len <= 0) {
len = BaseStatistics.SIZE_UNKNOWN;
}
return new FileBaseStatistics(latestModTime, len, BaseStatistics.AVG_RECORD_BYTES_UNKNOWN);
}
// --------------------------------------------------------------------------------------------
// Custom serialization methods
// --------------------------------------------------------------------------------------------
private void writeObject(ObjectOutputStream out) throws IOException {
super.write(out);
out.writeUTF(this.mapreduceInputFormat.getClass().getName());
out.writeUTF(this.keyClass.getName());
out.writeUTF(this.valueClass.getName());
this.configuration.write(out);
}
@SuppressWarnings("unchecked")
private void readObject(ObjectInputStream in) throws IOException, ClassNotFoundException {
super.read(in);
String hadoopInputFormatClassName = in.readUTF();
String keyClassName = in.readUTF();
String valueClassName = in.readUTF();
org.apache.hadoop.conf.Configuration configuration = new org.apache.hadoop.conf.Configuration();
configuration.readFields(in);
if (this.configuration == null) {
this.configuration = configuration;
}
try {
this.mapreduceInputFormat = (org.apache.hadoop.mapreduce.InputFormat<K,V>) Class.forName(hadoopInputFormatClassName, true, Thread.currentThread().getContextClassLoader()).newInstance();
} catch (Exception e) {
throw new RuntimeException("Unable to instantiate the hadoop input format", e);
}
try {
this.keyClass = (Class<K>) Class.forName(keyClassName, true, Thread.currentThread().getContextClassLoader());
} catch (Exception e) {
throw new RuntimeException("Unable to find key class.", e);
}
try {
this.valueClass = (Class<V>) Class.forName(valueClassName, true, Thread.currentThread().getContextClassLoader());
} catch (Exception e) {
throw new RuntimeException("Unable to find value class.", e);
}
}
}