- Adding HoodieCombineHiveInputFormat for COW tables (#811)
- Combine input format helps to reduce large scans into smaller ones by combining map tasks - Implementation to support Hive 2.x and above
This commit is contained in:
n3nash
@@ -0,0 +1,933 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package com.uber.hoodie.hadoop.hive;
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import com.google.common.annotations.VisibleForTesting;
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import com.uber.hoodie.hadoop.HoodieInputFormat;
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import com.uber.hoodie.hadoop.realtime.HoodieRealtimeInputFormat;
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import java.io.DataInput;
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import java.io.DataOutput;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.HashMap;
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import java.util.HashSet;
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import java.util.Iterator;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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import java.util.concurrent.Callable;
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import java.util.concurrent.ExecutionException;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.Executors;
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import java.util.concurrent.Future;
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import org.apache.hadoop.conf.Configuration;
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import org.apache.hadoop.fs.FileStatus;
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import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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import org.apache.hadoop.fs.PathFilter;
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import org.apache.hadoop.hive.common.StringInternUtils;
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import org.apache.hadoop.hive.conf.HiveConf;
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import org.apache.hadoop.hive.ql.exec.Operator;
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import org.apache.hadoop.hive.ql.exec.Utilities;
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import org.apache.hadoop.hive.ql.io.CombineHiveRecordReader;
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import org.apache.hadoop.hive.ql.io.HiveFileFormatUtils;
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import org.apache.hadoop.hive.ql.io.HiveInputFormat;
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import org.apache.hadoop.hive.ql.io.IOPrepareCache;
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import org.apache.hadoop.hive.ql.io.SymlinkTextInputFormat;
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import org.apache.hadoop.hive.ql.log.PerfLogger;
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import org.apache.hadoop.hive.ql.parse.SplitSample;
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import org.apache.hadoop.hive.ql.plan.OperatorDesc;
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import org.apache.hadoop.hive.ql.plan.PartitionDesc;
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import org.apache.hadoop.hive.ql.plan.TableDesc;
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import org.apache.hadoop.hive.ql.session.SessionState;
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import org.apache.hadoop.hive.shims.HadoopShims.CombineFileInputFormatShim;
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import org.apache.hadoop.hive.shims.HadoopShimsSecure;
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import org.apache.hadoop.hive.shims.HadoopShimsSecure.InputSplitShim;
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import org.apache.hadoop.hive.shims.ShimLoader;
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import org.apache.hadoop.io.Writable;
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import org.apache.hadoop.io.WritableComparable;
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import org.apache.hadoop.mapred.FileInputFormat;
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import org.apache.hadoop.mapred.InputFormat;
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import org.apache.hadoop.mapred.InputSplit;
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import org.apache.hadoop.mapred.JobConf;
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import org.apache.hadoop.mapred.RecordReader;
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import org.apache.hadoop.mapred.Reporter;
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import org.apache.hadoop.mapred.lib.CombineFileInputFormat;
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import org.apache.hadoop.mapred.lib.CombineFileSplit;
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import org.apache.hadoop.mapreduce.JobContext;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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/**
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* This is just a copy of the org.apache.hadoop.hive.ql.io.CombineHiveInputFormat from Hive 2.x
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* Search for **MOD** to see minor modifications to support custom inputformat in CombineHiveInputFormat.
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* See https://issues.apache.org/jira/browse/HIVE-9771
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* <p>
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* <p>
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* CombineHiveInputFormat is a parameterized InputFormat which looks at the path
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* name and determine the correct InputFormat for that path name from
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* mapredPlan.pathToPartitionInfo(). It can be used to read files with different
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* input format in the same map-reduce job.
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*
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* NOTE : This class is implemented to work with Hive 2.x +
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*/
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public class HoodieCombineHiveInputFormat<K extends WritableComparable, V extends Writable>
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extends HiveInputFormat<K, V> {
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private static final String CLASS_NAME = HoodieCombineHiveInputFormat.class.getName();
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public static final Logger LOG = LoggerFactory.getLogger(CLASS_NAME);
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// max number of threads we can use to check non-combinable paths
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private static final int MAX_CHECK_NONCOMBINABLE_THREAD_NUM = 50;
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private static final int DEFAULT_NUM_PATH_PER_THREAD = 100;
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private class CheckNonCombinablePathCallable implements Callable<Set<Integer>> {
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private final Path[] paths;
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private final int start;
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private final int length;
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private final JobConf conf;
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public CheckNonCombinablePathCallable(Path[] paths, int start, int length, JobConf conf) {
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this.paths = paths;
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this.start = start;
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this.length = length;
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this.conf = conf;
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}
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@Override
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public Set<Integer> call() throws Exception {
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Set<Integer> nonCombinablePathIndices = new HashSet<Integer>();
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for (int i = 0; i < length; i++) {
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PartitionDesc part =
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HiveFileFormatUtils.getPartitionDescFromPathRecursively(
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pathToPartitionInfo, paths[i + start],
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IOPrepareCache.get().allocatePartitionDescMap());
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// Use HiveInputFormat if any of the paths is not splittable
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Class<? extends InputFormat> inputFormatClass = part.getInputFileFormatClass();
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InputFormat<WritableComparable, Writable> inputFormat =
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getInputFormatFromCache(inputFormatClass, conf);
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if (inputFormat instanceof AvoidSplitCombination
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&& ((AvoidSplitCombination) inputFormat).shouldSkipCombine(paths[i + start], conf)) {
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if (LOG.isDebugEnabled()) {
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LOG.debug("The path [" + paths[i + start]
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+ "] is being parked for HiveInputFormat.getSplits");
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}
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nonCombinablePathIndices.add(i + start);
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}
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}
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return nonCombinablePathIndices;
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}
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}
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/**
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* CombineHiveInputSplit encapsulates an InputSplit with its corresponding
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* inputFormatClassName. A CombineHiveInputSplit comprises of multiple chunks
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* from different files. Since, they belong to a single directory, there is a
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* single inputformat for all the chunks.
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*/
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public static class CombineHiveInputSplit extends InputSplitShim {
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private String inputFormatClassName;
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private CombineFileSplit inputSplitShim;
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private Map<Path, PartitionDesc> pathToPartitionInfo;
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public CombineHiveInputSplit() throws IOException {
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this(ShimLoader.getHadoopShims().getCombineFileInputFormat()
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.getInputSplitShim());
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}
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public CombineHiveInputSplit(CombineFileSplit inputSplitShim) throws IOException {
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this(inputSplitShim.getJob(), inputSplitShim);
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}
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public CombineHiveInputSplit(JobConf job, CombineFileSplit inputSplitShim)
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throws IOException {
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this(job, inputSplitShim, null);
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}
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public CombineHiveInputSplit(JobConf job, CombineFileSplit inputSplitShim,
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Map<Path, PartitionDesc> pathToPartitionInfo) throws IOException {
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this.inputSplitShim = inputSplitShim;
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this.pathToPartitionInfo = pathToPartitionInfo;
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if (job != null) {
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if (this.pathToPartitionInfo == null) {
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this.pathToPartitionInfo = Utilities.getMapWork(job).getPathToPartitionInfo();
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}
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// extract all the inputFormatClass names for each chunk in the
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// CombinedSplit.
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Path[] ipaths = inputSplitShim.getPaths();
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if (ipaths.length > 0) {
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PartitionDesc part = HiveFileFormatUtils
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.getPartitionDescFromPathRecursively(this.pathToPartitionInfo,
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ipaths[0], IOPrepareCache.get().getPartitionDescMap());
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inputFormatClassName = part.getInputFileFormatClass().getName();
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}
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}
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}
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public CombineFileSplit getInputSplitShim() {
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return inputSplitShim;
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}
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/**
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* Returns the inputFormat class name for the i-th chunk.
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*/
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public String inputFormatClassName() {
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return inputFormatClassName;
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}
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public void setInputFormatClassName(String inputFormatClassName) {
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this.inputFormatClassName = inputFormatClassName;
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}
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@Override
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public JobConf getJob() {
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return inputSplitShim.getJob();
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}
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@Override
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public long getLength() {
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return inputSplitShim.getLength();
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}
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/**
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* Returns an array containing the startoffsets of the files in the split.
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*/
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@Override
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public long[] getStartOffsets() {
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return inputSplitShim.getStartOffsets();
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}
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/**
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* Returns an array containing the lengths of the files in the split.
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*/
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@Override
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public long[] getLengths() {
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return inputSplitShim.getLengths();
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}
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/**
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* Returns the start offset of the i<sup>th</sup> Path.
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*/
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@Override
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public long getOffset(int i) {
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return inputSplitShim.getOffset(i);
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}
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/**
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* Returns the length of the i<sup>th</sup> Path.
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*/
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@Override
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public long getLength(int i) {
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return inputSplitShim.getLength(i);
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}
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/**
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* Returns the number of Paths in the split.
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*/
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@Override
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public int getNumPaths() {
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return inputSplitShim.getNumPaths();
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}
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/**
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* Returns the i<sup>th</sup> Path.
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*/
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@Override
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public Path getPath(int i) {
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return inputSplitShim.getPath(i);
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}
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/**
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* Returns all the Paths in the split.
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*/
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@Override
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public Path[] getPaths() {
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return inputSplitShim.getPaths();
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}
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/**
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* Returns all the Paths where this input-split resides.
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*/
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@Override
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public String[] getLocations() throws IOException {
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return inputSplitShim.getLocations();
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}
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/**
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* Prints this obejct as a string.
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*/
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@Override
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public String toString() {
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StringBuilder sb = new StringBuilder();
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sb.append(inputSplitShim.toString());
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sb.append("InputFormatClass: " + inputFormatClassName);
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sb.append("\n");
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return sb.toString();
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}
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/**
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* Writable interface.
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*/
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@Override
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public void readFields(DataInput in) throws IOException {
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inputSplitShim.readFields(in);
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inputFormatClassName = in.readUTF();
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}
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/**
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* Writable interface.
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*/
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@Override
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public void write(DataOutput out) throws IOException {
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inputSplitShim.write(out);
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if (inputFormatClassName == null) {
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if (pathToPartitionInfo == null) {
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pathToPartitionInfo = Utilities.getMapWork(getJob()).getPathToPartitionInfo();
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}
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// extract all the inputFormatClass names for each chunk in the
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// CombinedSplit.
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PartitionDesc part =
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HiveFileFormatUtils.getPartitionDescFromPathRecursively(pathToPartitionInfo,
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inputSplitShim.getPath(0), IOPrepareCache.get().getPartitionDescMap());
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// create a new InputFormat instance if this is the first time to see
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// this class
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inputFormatClassName = part.getInputFileFormatClass().getName();
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}
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out.writeUTF(inputFormatClassName);
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}
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}
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// Splits are not shared across different partitions with different input formats.
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// For example, 2 partitions (1 sequencefile and 1 rcfile) will have 2 different splits
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private static class CombinePathInputFormat {
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private final List<Operator<? extends OperatorDesc>> opList;
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private final String inputFormatClassName;
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private final String deserializerClassName;
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public CombinePathInputFormat(List<Operator<? extends OperatorDesc>> opList,
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String inputFormatClassName,
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String deserializerClassName) {
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this.opList = opList;
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this.inputFormatClassName = inputFormatClassName;
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this.deserializerClassName = deserializerClassName;
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}
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@Override
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public boolean equals(Object o) {
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if (o instanceof CombinePathInputFormat) {
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CombinePathInputFormat mObj = (CombinePathInputFormat) o;
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return (opList.equals(mObj.opList))
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&& (inputFormatClassName.equals(mObj.inputFormatClassName))
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&& (deserializerClassName == null ? (mObj.deserializerClassName == null) :
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deserializerClassName.equals(mObj.deserializerClassName));
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}
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return false;
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}
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@Override
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public int hashCode() {
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return (opList == null) ? 0 : opList.hashCode();
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}
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}
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/**
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* Create Hive splits based on CombineFileSplit.
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*/
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private InputSplit[] getCombineSplits(JobConf job, int numSplits,
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Map<Path, PartitionDesc> pathToPartitionInfo)
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throws IOException {
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init(job);
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Map<Path, ArrayList<String>> pathToAliases = mrwork.getPathToAliases();
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Map<String, Operator<? extends OperatorDesc>> aliasToWork =
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mrwork.getAliasToWork();
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/** MOD - Initialize a custom combine input format shim that will call listStatus on the custom inputFormat **/
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HoodieCombineHiveInputFormat.HoodieCombineFileInputFormatShim
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combine = new HoodieCombineHiveInputFormat.HoodieCombineFileInputFormatShim();
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InputSplit[] splits = null;
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if (combine == null) {
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splits = super.getSplits(job, numSplits);
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return splits;
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}
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if (combine.getInputPathsShim(job).length == 0) {
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throw new IOException("No input paths specified in job");
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}
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ArrayList<InputSplit> result = new ArrayList<InputSplit>();
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// combine splits only from same tables and same partitions. Do not combine splits from multiple
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// tables or multiple partitions.
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Path[] paths = StringInternUtils.internUriStringsInPathArray(combine.getInputPathsShim(job));
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List<Path> inpDirs = new ArrayList<Path>();
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List<Path> inpFiles = new ArrayList<Path>();
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Map<CombinePathInputFormat, CombineFilter> poolMap =
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new HashMap<CombinePathInputFormat, CombineFilter>();
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Set<Path> poolSet = new HashSet<Path>();
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for (Path path : paths) {
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PartitionDesc part = HiveFileFormatUtils.getPartitionDescFromPathRecursively(
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pathToPartitionInfo, path, IOPrepareCache.get().allocatePartitionDescMap());
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TableDesc tableDesc = part.getTableDesc();
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if ((tableDesc != null) && tableDesc.isNonNative()) {
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return super.getSplits(job, numSplits);
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}
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// Use HiveInputFormat if any of the paths is not splittable
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Class inputFormatClass = part.getInputFileFormatClass();
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String inputFormatClassName = inputFormatClass.getName();
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InputFormat inputFormat = getInputFormatFromCache(inputFormatClass, job);
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LOG.info("Input Format => " + inputFormatClass.getName());
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// **MOD** Set the hoodie filter in the combine
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if (inputFormatClass.getName().equals(HoodieInputFormat.class.getName())) {
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combine.setHoodieFilter(true);
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} else if (inputFormatClass.getName().equals(HoodieRealtimeInputFormat.class.getName())) {
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LOG.info("Setting hoodie filter and realtime input format");
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combine.setHoodieFilter(true);
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combine.setRealTime(true);
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}
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String deserializerClassName = null;
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try {
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deserializerClassName = part.getDeserializer(job).getClass().getName();
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} catch (Exception e) {
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// ignore
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}
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FileSystem inpFs = path.getFileSystem(job);
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//don't combine if inputformat is a SymlinkTextInputFormat
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if (inputFormat instanceof SymlinkTextInputFormat) {
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splits = super.getSplits(job, numSplits);
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return splits;
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}
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Path filterPath = path;
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// Does a pool exist for this path already
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CombineFilter f = null;
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List<Operator<? extends OperatorDesc>> opList = null;
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if (!mrwork.isMapperCannotSpanPartns()) {
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//if mapper can span partitions, make sure a splits does not contain multiple
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// opList + inputFormatClassName + deserializerClassName combination
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// This is done using the Map of CombinePathInputFormat to PathFilter
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opList = HiveFileFormatUtils.doGetWorksFromPath(
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pathToAliases, aliasToWork, filterPath);
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CombinePathInputFormat combinePathInputFormat =
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new CombinePathInputFormat(opList, inputFormatClassName, deserializerClassName);
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f = poolMap.get(combinePathInputFormat);
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if (f == null) {
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f = new CombineFilter(filterPath);
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LOG.info("CombineHiveInputSplit creating pool for "
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+ path + "; using filter path " + filterPath);
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combine.createPool(job, f);
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poolMap.put(combinePathInputFormat, f);
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} else {
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LOG.info("CombineHiveInputSplit: pool is already created for "
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+ path + "; using filter path " + filterPath);
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f.addPath(filterPath);
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}
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} else {
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// In the case of tablesample, the input paths are pointing to files rather than directories.
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// We need to get the parent directory as the filtering path so that all files in the same
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// parent directory will be grouped into one pool but not files from different parent
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// directories. This guarantees that a split will combine all files in the same partition
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// but won't cross multiple partitions if the user has asked so.
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if (!path.getFileSystem(job).getFileStatus(path).isDir()) { // path is not directory
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filterPath = path.getParent();
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inpFiles.add(path);
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poolSet.add(filterPath);
|
||||
} else {
|
||||
inpDirs.add(path);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Processing directories
|
||||
List<CombineFileSplit> iss = new ArrayList<CombineFileSplit>();
|
||||
if (!mrwork.isMapperCannotSpanPartns()) {
|
||||
//mapper can span partitions
|
||||
//combine into as few as one split, subject to the PathFilters set
|
||||
// using combine.createPool.
|
||||
iss = Arrays.asList(combine.getSplits(job, 1));
|
||||
} else {
|
||||
for (Path path : inpDirs) {
|
||||
processPaths(job, combine, iss, path);
|
||||
}
|
||||
|
||||
if (inpFiles.size() > 0) {
|
||||
// Processing files
|
||||
for (Path filterPath : poolSet) {
|
||||
combine.createPool(job, new CombineFilter(filterPath));
|
||||
}
|
||||
processPaths(job, combine, iss, inpFiles.toArray(new Path[0]));
|
||||
}
|
||||
}
|
||||
|
||||
if (mrwork.getNameToSplitSample() != null && !mrwork.getNameToSplitSample().isEmpty()) {
|
||||
iss = sampleSplits(iss);
|
||||
}
|
||||
|
||||
for (CombineFileSplit is : iss) {
|
||||
CombineHiveInputSplit csplit = new CombineHiveInputSplit(job, is, pathToPartitionInfo);
|
||||
result.add(csplit);
|
||||
}
|
||||
|
||||
LOG.info("number of splits " + result.size());
|
||||
return result.toArray(new CombineHiveInputSplit[result.size()]);
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets all the path indices that should not be combined
|
||||
*/
|
||||
@VisibleForTesting
|
||||
public Set<Integer> getNonCombinablePathIndices(JobConf job, Path[] paths, int numThreads)
|
||||
throws ExecutionException, InterruptedException {
|
||||
LOG.info("Total number of paths: " + paths.length
|
||||
+ ", launching " + numThreads + " threads to check non-combinable ones.");
|
||||
int numPathPerThread = (int) Math.ceil((double) paths.length / numThreads);
|
||||
|
||||
ExecutorService executor = Executors.newFixedThreadPool(numThreads);
|
||||
List<Future<Set<Integer>>> futureList = new ArrayList<Future<Set<Integer>>>(numThreads);
|
||||
try {
|
||||
for (int i = 0; i < numThreads; i++) {
|
||||
int start = i * numPathPerThread;
|
||||
int length = i != numThreads - 1 ? numPathPerThread : paths.length - start;
|
||||
futureList.add(executor.submit(
|
||||
new CheckNonCombinablePathCallable(paths, start, length, job)));
|
||||
}
|
||||
Set<Integer> nonCombinablePathIndices = new HashSet<Integer>();
|
||||
for (Future<Set<Integer>> future : futureList) {
|
||||
nonCombinablePathIndices.addAll(future.get());
|
||||
}
|
||||
return nonCombinablePathIndices;
|
||||
} finally {
|
||||
executor.shutdownNow();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create Hive splits based on CombineFileSplit.
|
||||
*/
|
||||
@Override
|
||||
public InputSplit[] getSplits(JobConf job, int numSplits) throws IOException {
|
||||
PerfLogger perfLogger = SessionState.getPerfLogger();
|
||||
perfLogger.PerfLogBegin(CLASS_NAME, PerfLogger.GET_SPLITS);
|
||||
init(job);
|
||||
|
||||
ArrayList<InputSplit> result = new ArrayList<InputSplit>();
|
||||
|
||||
Path[] paths = getInputPaths(job);
|
||||
|
||||
List<Path> nonCombinablePaths = new ArrayList<Path>(paths.length / 2);
|
||||
List<Path> combinablePaths = new ArrayList<Path>(paths.length / 2);
|
||||
|
||||
int numThreads = Math.min(MAX_CHECK_NONCOMBINABLE_THREAD_NUM,
|
||||
(int) Math.ceil((double) paths.length / DEFAULT_NUM_PATH_PER_THREAD));
|
||||
|
||||
// This check is necessary because for Spark branch, the result array from
|
||||
// getInputPaths() above could be empty, and therefore numThreads could be 0.
|
||||
// In that case, Executors.newFixedThreadPool will fail.
|
||||
if (numThreads > 0) {
|
||||
try {
|
||||
Set<Integer> nonCombinablePathIndices = getNonCombinablePathIndices(job, paths, numThreads);
|
||||
for (int i = 0; i < paths.length; i++) {
|
||||
if (nonCombinablePathIndices.contains(i)) {
|
||||
nonCombinablePaths.add(paths[i]);
|
||||
} else {
|
||||
combinablePaths.add(paths[i]);
|
||||
}
|
||||
}
|
||||
} catch (Exception e) {
|
||||
LOG.error("Error checking non-combinable path", e);
|
||||
perfLogger.PerfLogEnd(CLASS_NAME, PerfLogger.GET_SPLITS);
|
||||
throw new IOException(e);
|
||||
}
|
||||
}
|
||||
|
||||
// Store the previous value for the path specification
|
||||
String oldPaths = job.get(org.apache.hadoop.mapreduce.lib.input.FileInputFormat.INPUT_DIR);
|
||||
if (LOG.isDebugEnabled()) {
|
||||
LOG.debug("The received input paths are: [" + oldPaths
|
||||
+ "] against the property "
|
||||
+ org.apache.hadoop.mapreduce.lib.input.FileInputFormat.INPUT_DIR);
|
||||
}
|
||||
|
||||
// Process the normal splits
|
||||
if (nonCombinablePaths.size() > 0) {
|
||||
FileInputFormat.setInputPaths(job,
|
||||
nonCombinablePaths.toArray(new Path[nonCombinablePaths.size()]));
|
||||
InputSplit[] splits = super.getSplits(job, numSplits);
|
||||
for (InputSplit split : splits) {
|
||||
result.add(split);
|
||||
}
|
||||
}
|
||||
|
||||
// Process the combine splits
|
||||
if (combinablePaths.size() > 0) {
|
||||
FileInputFormat.setInputPaths(job,
|
||||
combinablePaths.toArray(new Path[combinablePaths.size()]));
|
||||
Map<Path, PartitionDesc> pathToPartitionInfo = this.pathToPartitionInfo != null
|
||||
? this.pathToPartitionInfo : Utilities.getMapWork(job).getPathToPartitionInfo();
|
||||
InputSplit[] splits = getCombineSplits(job, numSplits, pathToPartitionInfo);
|
||||
for (InputSplit split : splits) {
|
||||
result.add(split);
|
||||
}
|
||||
}
|
||||
|
||||
// Restore the old path information back
|
||||
// This is just to prevent incompatibilities with previous versions Hive
|
||||
// if some application depends on the original value being set.
|
||||
if (oldPaths != null) {
|
||||
job.set(org.apache.hadoop.mapreduce.lib.input.FileInputFormat.INPUT_DIR, oldPaths);
|
||||
}
|
||||
|
||||
// clear work from ThreadLocal after splits generated in case of thread is reused in pool.
|
||||
Utilities.clearWorkMapForConf(job);
|
||||
|
||||
LOG.info("Number of all splits " + result.size());
|
||||
perfLogger.PerfLogEnd(CLASS_NAME, PerfLogger.GET_SPLITS);
|
||||
return result.toArray(new InputSplit[result.size()]);
|
||||
}
|
||||
|
||||
private void processPaths(JobConf job, CombineFileInputFormatShim combine,
|
||||
List<CombineFileSplit> iss, Path... path) throws IOException {
|
||||
JobConf currJob = new JobConf(job);
|
||||
FileInputFormat.setInputPaths(currJob, path);
|
||||
iss.addAll(Arrays.asList(combine.getSplits(currJob, 1)));
|
||||
}
|
||||
|
||||
/**
|
||||
* MOD - Just added this for visibility
|
||||
**/
|
||||
Path[] getInputPaths(JobConf job) throws IOException {
|
||||
Path[] dirs = FileInputFormat.getInputPaths(job);
|
||||
if (dirs.length == 0) {
|
||||
// on tez we're avoiding to duplicate the file info in FileInputFormat.
|
||||
if (HiveConf.getVar(job, HiveConf.ConfVars.HIVE_EXECUTION_ENGINE).equals("tez")) {
|
||||
try {
|
||||
List<Path> paths = Utilities.getInputPathsTez(job, mrwork);
|
||||
dirs = paths.toArray(new Path[paths.size()]);
|
||||
} catch (Exception e) {
|
||||
throw new IOException("Could not create input files", e);
|
||||
}
|
||||
} else {
|
||||
throw new IOException("No input paths specified in job");
|
||||
}
|
||||
}
|
||||
return dirs;
|
||||
}
|
||||
|
||||
/**
|
||||
* This function is used to sample inputs for clauses like "TABLESAMPLE(1 PERCENT)"
|
||||
* <p>
|
||||
* First, splits are grouped by alias they are for. If one split serves more than one
|
||||
* alias or not for any sampled alias, we just directly add it to returned list.
|
||||
* Then we find a list of exclusive splits for every alias to be sampled.
|
||||
* For each alias, we start from position of seedNumber%totalNumber, and keep add
|
||||
* splits until the total size hits percentage.
|
||||
*
|
||||
* @return the sampled splits
|
||||
*/
|
||||
private List<CombineFileSplit> sampleSplits(List<CombineFileSplit> splits) {
|
||||
HashMap<String, SplitSample> nameToSamples = mrwork.getNameToSplitSample();
|
||||
List<CombineFileSplit> retLists = new ArrayList<CombineFileSplit>();
|
||||
Map<String, ArrayList<CombineFileSplit>> aliasToSplitList =
|
||||
new HashMap<String, ArrayList<CombineFileSplit>>();
|
||||
Map<Path, ArrayList<String>> pathToAliases = mrwork.getPathToAliases();
|
||||
Map<Path, ArrayList<String>> pathToAliasesNoScheme = removeScheme(pathToAliases);
|
||||
|
||||
// Populate list of exclusive splits for every sampled alias
|
||||
//
|
||||
for (CombineFileSplit split : splits) {
|
||||
String alias = null;
|
||||
for (Path path : split.getPaths()) {
|
||||
boolean schemeless = path.toUri().getScheme() == null;
|
||||
List<String> l = HiveFileFormatUtils.doGetAliasesFromPath(
|
||||
schemeless ? pathToAliasesNoScheme : pathToAliases, path);
|
||||
// a path for a split unqualified the split from being sampled if:
|
||||
// 1. it serves more than one alias
|
||||
// 2. the alias it serves is not sampled
|
||||
// 3. it serves different alias than another path for the same split
|
||||
if (l.size() != 1 || !nameToSamples.containsKey(l.get(0))
|
||||
|| (alias != null && l.get(0) != alias)) {
|
||||
alias = null;
|
||||
break;
|
||||
}
|
||||
alias = l.get(0);
|
||||
}
|
||||
|
||||
if (alias != null) {
|
||||
// split exclusively serves alias, which needs to be sampled
|
||||
// add it to the split list of the alias.
|
||||
if (!aliasToSplitList.containsKey(alias)) {
|
||||
aliasToSplitList.put(alias, new ArrayList<CombineFileSplit>());
|
||||
}
|
||||
aliasToSplitList.get(alias).add(split);
|
||||
} else {
|
||||
// The split doesn't exclusively serve one alias
|
||||
retLists.add(split);
|
||||
}
|
||||
}
|
||||
|
||||
// for every sampled alias, we figure out splits to be sampled and add
|
||||
// them to return list
|
||||
//
|
||||
for (Map.Entry<String, ArrayList<CombineFileSplit>> entry : aliasToSplitList.entrySet()) {
|
||||
ArrayList<CombineFileSplit> splitList = entry.getValue();
|
||||
long totalSize = 0;
|
||||
for (CombineFileSplit split : splitList) {
|
||||
totalSize += split.getLength();
|
||||
}
|
||||
|
||||
SplitSample splitSample = nameToSamples.get(entry.getKey());
|
||||
|
||||
long targetSize = splitSample.getTargetSize(totalSize);
|
||||
int startIndex = splitSample.getSeedNum() % splitList.size();
|
||||
long size = 0;
|
||||
for (int i = 0; i < splitList.size(); i++) {
|
||||
CombineFileSplit split = splitList.get((startIndex + i) % splitList.size());
|
||||
retLists.add(split);
|
||||
long splitgLength = split.getLength();
|
||||
if (size + splitgLength >= targetSize) {
|
||||
LOG.info("Sample alias " + entry.getValue() + " using " + (i + 1) + "splits");
|
||||
if (size + splitgLength > targetSize) {
|
||||
((InputSplitShim) split).shrinkSplit(targetSize - size);
|
||||
}
|
||||
break;
|
||||
}
|
||||
size += splitgLength;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
return retLists;
|
||||
}
|
||||
|
||||
Map<Path, ArrayList<String>> removeScheme(Map<Path, ArrayList<String>> pathToAliases) {
|
||||
Map<Path, ArrayList<String>> result = new HashMap<>();
|
||||
for (Map.Entry<Path, ArrayList<String>> entry : pathToAliases.entrySet()) {
|
||||
Path newKey = Path.getPathWithoutSchemeAndAuthority(entry.getKey());
|
||||
StringInternUtils.internUriStringsInPath(newKey);
|
||||
result.put(newKey, entry.getValue());
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a generic Hive RecordReader than can iterate over all chunks in a
|
||||
* CombinedFileSplit.
|
||||
*/
|
||||
@Override
|
||||
public RecordReader getRecordReader(InputSplit split, JobConf job,
|
||||
Reporter reporter) throws IOException {
|
||||
if (!(split instanceof CombineHiveInputSplit)) {
|
||||
return super.getRecordReader(split, job, reporter);
|
||||
}
|
||||
|
||||
CombineHiveInputSplit hsplit = (CombineHiveInputSplit) split;
|
||||
|
||||
String inputFormatClassName = null;
|
||||
Class inputFormatClass = null;
|
||||
try {
|
||||
inputFormatClassName = hsplit.inputFormatClassName();
|
||||
inputFormatClass = job.getClassByName(inputFormatClassName);
|
||||
} catch (Exception e) {
|
||||
throw new IOException("cannot find class " + inputFormatClassName);
|
||||
}
|
||||
|
||||
pushProjectionsAndFilters(job, inputFormatClass, hsplit.getPath(0));
|
||||
|
||||
return ShimLoader.getHadoopShims().getCombineFileInputFormat()
|
||||
.getRecordReader(job,
|
||||
(CombineFileSplit) split, reporter,
|
||||
CombineHiveRecordReader.class);
|
||||
}
|
||||
|
||||
static class CombineFilter implements PathFilter {
|
||||
|
||||
private final Set<String> pStrings = new HashSet<String>();
|
||||
|
||||
// store a path prefix in this TestFilter
|
||||
// PRECONDITION: p should always be a directory
|
||||
public CombineFilter(Path p) {
|
||||
// we need to keep the path part only because the Hadoop CombineFileInputFormat will
|
||||
// pass the path part only to accept().
|
||||
// Trailing the path with a separator to prevent partial matching.
|
||||
addPath(p);
|
||||
}
|
||||
|
||||
public void addPath(Path p) {
|
||||
String pString = p.toUri().getPath();
|
||||
pStrings.add(pString);
|
||||
}
|
||||
|
||||
// returns true if the specified path matches the prefix stored
|
||||
// in this TestFilter.
|
||||
@Override
|
||||
public boolean accept(Path path) {
|
||||
boolean find = false;
|
||||
while (path != null && !find) {
|
||||
if (pStrings.contains(path.toUri().getPath())) {
|
||||
find = true;
|
||||
break;
|
||||
}
|
||||
path = path.getParent();
|
||||
}
|
||||
return find;
|
||||
}
|
||||
|
||||
@Override
|
||||
public String toString() {
|
||||
StringBuilder s = new StringBuilder();
|
||||
s.append("PathFilter: ");
|
||||
for (String pString : pStrings) {
|
||||
s.append(pString + " ");
|
||||
}
|
||||
return s.toString();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* This is a marker interface that is used to identify the formats where
|
||||
* combine split generation is not applicable
|
||||
*/
|
||||
public interface AvoidSplitCombination {
|
||||
|
||||
boolean shouldSkipCombine(Path path, Configuration conf) throws IOException;
|
||||
}
|
||||
|
||||
/**
|
||||
* **MOD** this is the implementation of CombineFileInputFormat which is a copy of
|
||||
* org.apache.hadoop.hive.shims.HadoopShimsSecure.CombineFileInputFormatShim
|
||||
* with changes in listStatus
|
||||
*/
|
||||
public static class HoodieCombineFileInputFormatShim<K, V> extends CombineFileInputFormat<K, V>
|
||||
implements org.apache.hadoop.hive.shims.HadoopShims.CombineFileInputFormatShim<K, V> {
|
||||
|
||||
private boolean hoodieFilter = false;
|
||||
private boolean isRealTime = false;
|
||||
|
||||
public HoodieCombineFileInputFormatShim() {
|
||||
}
|
||||
|
||||
public Path[] getInputPathsShim(JobConf conf) {
|
||||
try {
|
||||
return FileInputFormat.getInputPaths(conf);
|
||||
} catch (Exception var3) {
|
||||
throw new RuntimeException(var3);
|
||||
}
|
||||
}
|
||||
|
||||
public void createPool(JobConf conf, PathFilter... filters) {
|
||||
super.createPool(conf, filters);
|
||||
}
|
||||
|
||||
@Override
|
||||
public RecordReader<K, V> getRecordReader(InputSplit split, JobConf job, Reporter reporter)
|
||||
throws IOException {
|
||||
throw new IOException("CombineFileInputFormat.getRecordReader not needed.");
|
||||
}
|
||||
|
||||
protected List<FileStatus> listStatus(JobContext job) throws IOException {
|
||||
LOG.info("Listing status in HoodieCombineHiveInputFormat.HoodieCombineFileInputFormatShim");
|
||||
List<FileStatus> result;
|
||||
if (hoodieFilter) {
|
||||
HoodieInputFormat input;
|
||||
if (isRealTime) {
|
||||
LOG.info("Using HoodieRealtimeInputFormat");
|
||||
input = new HoodieRealtimeInputFormat();
|
||||
} else {
|
||||
LOG.info("Using HoodieInputFormat");
|
||||
input = new HoodieInputFormat();
|
||||
}
|
||||
input.setConf(job.getConfiguration());
|
||||
result = new ArrayList<FileStatus>(
|
||||
Arrays.asList(input.listStatus(new JobConf(job.getConfiguration()))));
|
||||
} else {
|
||||
result = super.listStatus(job);
|
||||
}
|
||||
|
||||
Iterator it = result.iterator();
|
||||
|
||||
while (it.hasNext()) {
|
||||
FileStatus stat = (FileStatus) it.next();
|
||||
if (!stat.isFile()) {
|
||||
it.remove();
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
public CombineFileSplit[] getSplits(JobConf job, int numSplits) throws IOException {
|
||||
long minSize = job.getLong(org.apache.hadoop.mapreduce.lib.input.FileInputFormat.SPLIT_MINSIZE, 0L);
|
||||
if (job.getLong("mapreduce.input.fileinputformat.split.minsize.per.node", 0L) == 0L) {
|
||||
super.setMinSplitSizeNode(minSize);
|
||||
}
|
||||
|
||||
if (job.getLong("mapreduce.input.fileinputformat.split.minsize.per.rack", 0L) == 0L) {
|
||||
super.setMinSplitSizeRack(minSize);
|
||||
}
|
||||
|
||||
if (job.getLong(org.apache.hadoop.mapreduce.lib.input.FileInputFormat.SPLIT_MAXSIZE, 0L) == 0L) {
|
||||
super.setMaxSplitSize(minSize);
|
||||
}
|
||||
|
||||
InputSplit[] splits = super.getSplits(job, numSplits);
|
||||
ArrayList inputSplitShims = new ArrayList();
|
||||
|
||||
for (int pos = 0; pos < splits.length; ++pos) {
|
||||
CombineFileSplit split = (CombineFileSplit) splits[pos];
|
||||
if (split.getPaths().length > 0) {
|
||||
inputSplitShims.add(
|
||||
new HadoopShimsSecure.InputSplitShim(job, split.getPaths(), split.getStartOffsets(),
|
||||
split.getLengths(), split.getLocations()));
|
||||
}
|
||||
}
|
||||
|
||||
return (CombineFileSplit[]) inputSplitShims
|
||||
.toArray(new HadoopShimsSecure.InputSplitShim[inputSplitShims.size()]);
|
||||
}
|
||||
|
||||
public HadoopShimsSecure.InputSplitShim getInputSplitShim() throws IOException {
|
||||
return new HadoopShimsSecure.InputSplitShim();
|
||||
}
|
||||
|
||||
public RecordReader getRecordReader(JobConf job, CombineFileSplit split, Reporter reporter,
|
||||
Class<RecordReader<K, V>> rrClass) throws IOException {
|
||||
return new HadoopShimsSecure.CombineFileRecordReader(job, split, reporter, rrClass);
|
||||
}
|
||||
|
||||
public void setHoodieFilter(boolean hoodieFilter) {
|
||||
this.hoodieFilter = hoodieFilter;
|
||||
}
|
||||
|
||||
public void setRealTime(boolean realTime) {
|
||||
isRealTime = realTime;
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user