/**
* 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.hadoop.hive.ql.exec.mr;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import java.io.Serializable;
import java.lang.management.ManagementFactory;
import java.lang.management.MemoryMXBean;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.Enumeration;
import java.util.List;
import java.util.Properties;
import org.apache.commons.lang.StringUtils;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.filecache.DistributedCache;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hive.common.CompressionUtils;
import org.apache.hadoop.hive.common.LogUtils;
import org.apache.hadoop.hive.common.LogUtils.LogInitializationException;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.conf.HiveConf.ConfVars;
import org.apache.hadoop.hive.ql.Context;
import org.apache.hadoop.hive.ql.DriverContext;
import org.apache.hadoop.hive.ql.ErrorMsg;
import org.apache.hadoop.hive.ql.QueryPlan;
import org.apache.hadoop.hive.ql.exec.FetchOperator;
import org.apache.hadoop.hive.ql.exec.HiveTotalOrderPartitioner;
import org.apache.hadoop.hive.ql.exec.JobCloseFeedBack;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.PartitionKeySampler;
import org.apache.hadoop.hive.ql.exec.TableScanOperator;
import org.apache.hadoop.hive.ql.exec.Task;
import org.apache.hadoop.hive.ql.exec.Utilities;
import org.apache.hadoop.hive.ql.io.BucketizedHiveInputFormat;
import org.apache.hadoop.hive.ql.io.HiveKey;
import org.apache.hadoop.hive.ql.io.HiveOutputFormatImpl;
import org.apache.hadoop.hive.ql.io.IOPrepareCache;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.plan.FetchWork;
import org.apache.hadoop.hive.ql.plan.MapWork;
import org.apache.hadoop.hive.ql.plan.MapredLocalWork;
import org.apache.hadoop.hive.ql.plan.MapredWork;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
import org.apache.hadoop.hive.ql.plan.PartitionDesc;
import org.apache.hadoop.hive.ql.plan.ReduceWork;
import org.apache.hadoop.hive.ql.plan.api.StageType;
import org.apache.hadoop.hive.ql.session.SessionState;
import org.apache.hadoop.hive.ql.session.SessionState.LogHelper;
import org.apache.hadoop.hive.ql.stats.StatsFactory;
import org.apache.hadoop.hive.ql.stats.StatsPublisher;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.shims.ShimLoader;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.Counters;
import org.apache.hadoop.mapred.InputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.Partitioner;
import org.apache.hadoop.mapred.RunningJob;
import org.apache.log4j.Appender;
import org.apache.log4j.BasicConfigurator;
import org.apache.log4j.FileAppender;
import org.apache.log4j.LogManager;
import org.apache.log4j.varia.NullAppender;
/**
* ExecDriver is the central class in co-ordinating execution of any map-reduce task.
* It's main responsabilities are:
*
* - Converting the plan (MapredWork) into a MR Job (JobConf)
* - Submitting a MR job to the cluster via JobClient and ExecHelper
* - Executing MR job in local execution mode (where applicable)
*
*/
public class ExecDriver extends Task<MapredWork> implements Serializable, HadoopJobExecHook {
private static final long serialVersionUID = 1L;
private static final String JOBCONF_FILENAME = "jobconf.xml";
protected transient JobConf job;
public static MemoryMXBean memoryMXBean;
protected HadoopJobExecHelper jobExecHelper;
protected static transient final Log LOG = LogFactory.getLog(ExecDriver.class);
private RunningJob rj;
/**
* Constructor when invoked from QL.
*/
public ExecDriver() {
super();
console = new LogHelper(LOG);
this.jobExecHelper = new HadoopJobExecHelper(job, console, this, this);
}
@Override
public boolean requireLock() {
return true;
}
private void initializeFiles(String prop, String files) {
if (files != null && files.length() > 0) {
job.set(prop, files);
ShimLoader.getHadoopShims().setTmpFiles(prop, files);
}
}
/**
* Initialization when invoked from QL.
*/
@Override
public void initialize(HiveConf conf, QueryPlan queryPlan, DriverContext driverContext) {
super.initialize(conf, queryPlan, driverContext);
job = new JobConf(conf, ExecDriver.class);
// NOTE: initialize is only called if it is in non-local mode.
// In case it's in non-local mode, we need to move the SessionState files
// and jars to jobConf.
// In case it's in local mode, MapRedTask will set the jobConf.
//
// "tmpfiles" and "tmpjars" are set by the method ExecDriver.execute(),
// which will be called by both local and NON-local mode.
String addedFiles = Utilities.getResourceFiles(job, SessionState.ResourceType.FILE);
if (StringUtils.isNotBlank(addedFiles)) {
HiveConf.setVar(job, ConfVars.HIVEADDEDFILES, addedFiles);
}
String addedJars = Utilities.getResourceFiles(job, SessionState.ResourceType.JAR);
if (StringUtils.isNotBlank(addedJars)) {
HiveConf.setVar(job, ConfVars.HIVEADDEDJARS, addedJars);
}
String addedArchives = Utilities.getResourceFiles(job, SessionState.ResourceType.ARCHIVE);
if (StringUtils.isNotBlank(addedArchives)) {
HiveConf.setVar(job, ConfVars.HIVEADDEDARCHIVES, addedArchives);
}
this.jobExecHelper = new HadoopJobExecHelper(job, console, this, this);
}
/**
* Constructor/Initialization for invocation as independent utility.
*/
public ExecDriver(MapredWork plan, JobConf job, boolean isSilent) throws HiveException {
setWork(plan);
this.job = job;
console = new LogHelper(LOG, isSilent);
this.jobExecHelper = new HadoopJobExecHelper(job, console, this, this);
}
/**
* Fatal errors are those errors that cannot be recovered by retries. These are application
* dependent. Examples of fatal errors include: - the small table in the map-side joins is too
* large to be feasible to be handled by one mapper. The job should fail and the user should be
* warned to use regular joins rather than map-side joins. Fatal errors are indicated by counters
* that are set at execution time. If the counter is non-zero, a fatal error occurred. The value
* of the counter indicates the error type.
*
* @return true if fatal errors happened during job execution, false otherwise.
*/
public boolean checkFatalErrors(Counters ctrs, StringBuilder errMsg) {
for (Operator<? extends OperatorDesc> op : work.getMapWork().getAliasToWork().values()) {
if (op.checkFatalErrors(ctrs, errMsg)) {
return true;
}
}
if (work.getReduceWork() != null) {
if (work.getReduceWork().getReducer().checkFatalErrors(ctrs, errMsg)) {
return true;
}
}
return false;
}
/**
* Execute a query plan using Hadoop.
*/
@SuppressWarnings({"deprecation", "unchecked"})
@Override
public int execute(DriverContext driverContext) {
IOPrepareCache ioPrepareCache = IOPrepareCache.get();
ioPrepareCache.clear();
boolean success = true;
Context ctx = driverContext.getCtx();
boolean ctxCreated = false;
String emptyScratchDirStr;
Path emptyScratchDir;
MapWork mWork = work.getMapWork();
ReduceWork rWork = work.getReduceWork();
try {
if (ctx == null) {
ctx = new Context(job);
ctxCreated = true;
}
emptyScratchDirStr = ctx.getMRTmpFileURI();
emptyScratchDir = new Path(emptyScratchDirStr);
FileSystem fs = emptyScratchDir.getFileSystem(job);
fs.mkdirs(emptyScratchDir);
} catch (IOException e) {
e.printStackTrace();
console.printError("Error launching map-reduce job", "\n"
+ org.apache.hadoop.util.StringUtils.stringifyException(e));
return 5;
}
ShimLoader.getHadoopShims().prepareJobOutput(job);
//See the javadoc on HiveOutputFormatImpl and HadoopShims.prepareJobOutput()
job.setOutputFormat(HiveOutputFormatImpl.class);
job.setMapperClass(ExecMapper.class);
job.setMapOutputKeyClass(HiveKey.class);
job.setMapOutputValueClass(BytesWritable.class);
try {
job.setPartitionerClass((Class<? extends Partitioner>) (Class.forName(HiveConf.getVar(job,
HiveConf.ConfVars.HIVEPARTITIONER))));
} catch (ClassNotFoundException e) {
throw new RuntimeException(e.getMessage());
}
if (mWork.getNumMapTasks() != null) {
job.setNumMapTasks(mWork.getNumMapTasks().intValue());
}
if (mWork.getMaxSplitSize() != null) {
HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMAXSPLITSIZE, mWork.getMaxSplitSize().longValue());
}
if (mWork.getMinSplitSize() != null) {
HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMINSPLITSIZE, mWork.getMinSplitSize().longValue());
}
if (mWork.getMinSplitSizePerNode() != null) {
HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMINSPLITSIZEPERNODE, mWork.getMinSplitSizePerNode().longValue());
}
if (mWork.getMinSplitSizePerRack() != null) {
HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMINSPLITSIZEPERRACK, mWork.getMinSplitSizePerRack().longValue());
}
job.setNumReduceTasks(rWork != null ? rWork.getNumReduceTasks().intValue() : 0);
job.setReducerClass(ExecReducer.class);
// set input format information if necessary
setInputAttributes(job);
// Turn on speculative execution for reducers
boolean useSpeculativeExecReducers = HiveConf.getBoolVar(job,
HiveConf.ConfVars.HIVESPECULATIVEEXECREDUCERS);
HiveConf.setBoolVar(job, HiveConf.ConfVars.HADOOPSPECULATIVEEXECREDUCERS,
useSpeculativeExecReducers);
String inpFormat = HiveConf.getVar(job, HiveConf.ConfVars.HIVEINPUTFORMAT);
if ((inpFormat == null) || (!StringUtils.isNotBlank(inpFormat))) {
inpFormat = ShimLoader.getHadoopShims().getInputFormatClassName();
}
if (mWork.isUseBucketizedHiveInputFormat()) {
inpFormat = BucketizedHiveInputFormat.class.getName();
}
LOG.info("Using " + inpFormat);
try {
job.setInputFormat((Class<? extends InputFormat>) (Class.forName(inpFormat)));
} catch (ClassNotFoundException e) {
throw new RuntimeException(e.getMessage());
}
// No-Op - we don't really write anything here ..
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
// Transfer HIVEAUXJARS and HIVEADDEDJARS to "tmpjars" so hadoop understands
// it
String auxJars = HiveConf.getVar(job, HiveConf.ConfVars.HIVEAUXJARS);
String addedJars = HiveConf.getVar(job, HiveConf.ConfVars.HIVEADDEDJARS);
if (StringUtils.isNotBlank(auxJars) || StringUtils.isNotBlank(addedJars)) {
String allJars = StringUtils.isNotBlank(auxJars) ? (StringUtils.isNotBlank(addedJars) ? addedJars
+ "," + auxJars
: auxJars)
: addedJars;
LOG.info("adding libjars: " + allJars);
initializeFiles("tmpjars", allJars);
}
// Transfer HIVEADDEDFILES to "tmpfiles" so hadoop understands it
String addedFiles = HiveConf.getVar(job, HiveConf.ConfVars.HIVEADDEDFILES);
if (StringUtils.isNotBlank(addedFiles)) {
initializeFiles("tmpfiles", addedFiles);
}
int returnVal = 0;
boolean noName = StringUtils.isEmpty(HiveConf.getVar(job, HiveConf.ConfVars.HADOOPJOBNAME));
if (noName) {
// This is for a special case to ensure unit tests pass
HiveConf.setVar(job, HiveConf.ConfVars.HADOOPJOBNAME, "JOB" + Utilities.randGen.nextInt());
}
String addedArchives = HiveConf.getVar(job, HiveConf.ConfVars.HIVEADDEDARCHIVES);
// Transfer HIVEADDEDARCHIVES to "tmparchives" so hadoop understands it
if (StringUtils.isNotBlank(addedArchives)) {
initializeFiles("tmparchives", addedArchives);
}
try{
MapredLocalWork localwork = mWork.getMapLocalWork();
if (localwork != null) {
if (!ShimLoader.getHadoopShims().isLocalMode(job)) {
Path localPath = new Path(localwork.getTmpFileURI());
Path hdfsPath = new Path(mWork.getTmpHDFSFileURI());
FileSystem hdfs = hdfsPath.getFileSystem(job);
FileSystem localFS = localPath.getFileSystem(job);
FileStatus[] hashtableFiles = localFS.listStatus(localPath);
int fileNumber = hashtableFiles.length;
String[] fileNames = new String[fileNumber];
for ( int i = 0; i < fileNumber; i++){
fileNames[i] = hashtableFiles[i].getPath().getName();
}
//package and compress all the hashtable files to an archive file
String parentDir = localPath.toUri().getPath();
String stageId = this.getId();
String archiveFileURI = Utilities.generateTarURI(parentDir, stageId);
String archiveFileName = Utilities.generateTarFileName(stageId);
localwork.setStageID(stageId);
CompressionUtils.tar(parentDir, fileNames,archiveFileName);
Path archivePath = new Path(archiveFileURI);
LOG.info("Archive "+ hashtableFiles.length+" hash table files to " + archiveFileURI);
//upload archive file to hdfs
String hdfsFile =Utilities.generateTarURI(hdfsPath, stageId);
Path hdfsFilePath = new Path(hdfsFile);
short replication = (short) job.getInt("mapred.submit.replication", 10);
hdfs.setReplication(hdfsFilePath, replication);
hdfs.copyFromLocalFile(archivePath, hdfsFilePath);
LOG.info("Upload 1 archive file from" + archivePath + " to: " + hdfsFilePath);
//add the archive file to distributed cache
DistributedCache.createSymlink(job);
DistributedCache.addCacheArchive(hdfsFilePath.toUri(), job);
LOG.info("Add 1 archive file to distributed cache. Archive file: " + hdfsFilePath.toUri());
}
}
work.configureJobConf(job);
List<Path> inputPaths = Utilities.getInputPaths(job, mWork, emptyScratchDirStr, ctx);
Utilities.setInputPaths(job, inputPaths);
Utilities.setMapRedWork(job, work, ctx.getMRTmpFileURI());
if (mWork.getSamplingType() > 0 && rWork != null && rWork.getNumReduceTasks() > 1) {
try {
handleSampling(driverContext, mWork, job, conf);
job.setPartitionerClass(HiveTotalOrderPartitioner.class);
} catch (Exception e) {
console.printInfo("Not enough sampling data.. Rolling back to single reducer task");
rWork.setNumReduceTasks(1);
job.setNumReduceTasks(1);
}
}
// remove the pwd from conf file so that job tracker doesn't show this
// logs
String pwd = HiveConf.getVar(job, HiveConf.ConfVars.METASTOREPWD);
if (pwd != null) {
HiveConf.setVar(job, HiveConf.ConfVars.METASTOREPWD, "HIVE");
}
JobClient jc = new JobClient(job);
// make this client wait if job trcker is not behaving well.
Throttle.checkJobTracker(job, LOG);
if (mWork.isGatheringStats() || (rWork != null && rWork.isGatheringStats())) {
// initialize stats publishing table
StatsPublisher statsPublisher;
String statsImplementationClass = HiveConf.getVar(job, HiveConf.ConfVars.HIVESTATSDBCLASS);
if (StatsFactory.setImplementation(statsImplementationClass, job)) {
statsPublisher = StatsFactory.getStatsPublisher();
if (!statsPublisher.init(job)) { // creating stats table if not exists
if (HiveConf.getBoolVar(job, HiveConf.ConfVars.HIVE_STATS_RELIABLE)) {
throw
new HiveException(ErrorMsg.STATSPUBLISHER_INITIALIZATION_ERROR.getErrorCodedMsg());
}
}
}
}
Utilities.createTmpDirs(job, mWork);
Utilities.createTmpDirs(job, rWork);
// Finally SUBMIT the JOB!
rj = jc.submitJob(job);
// replace it back
if (pwd != null) {
HiveConf.setVar(job, HiveConf.ConfVars.METASTOREPWD, pwd);
}
returnVal = jobExecHelper.progress(rj, jc);
success = (returnVal == 0);
} catch (Exception e) {
e.printStackTrace();
String mesg = " with exception '" + Utilities.getNameMessage(e) + "'";
if (rj != null) {
mesg = "Ended Job = " + rj.getJobID() + mesg;
} else {
mesg = "Job Submission failed" + mesg;
}
// Has to use full name to make sure it does not conflict with
// org.apache.commons.lang.StringUtils
console.printError(mesg, "\n" + org.apache.hadoop.util.StringUtils.stringifyException(e));
success = false;
returnVal = 1;
} finally {
Utilities.clearWork(job);
try {
if (ctxCreated) {
ctx.clear();
}
if (rj != null) {
if (returnVal != 0) {
rj.killJob();
}
HadoopJobExecHelper.runningJobKillURIs.remove(rj.getJobID());
jobID = rj.getID().toString();
}
} catch (Exception e) {
}
}
// get the list of Dynamic partition paths
try {
if (rj != null) {
JobCloseFeedBack feedBack = new JobCloseFeedBack();
if (mWork.getAliasToWork() != null) {
for (Operator<? extends OperatorDesc> op : mWork.getAliasToWork().values()) {
op.jobClose(job, success, feedBack);
}
}
if (rWork != null) {
rWork.getReducer().jobClose(job, success, feedBack);
}
}
} catch (Exception e) {
// jobClose needs to execute successfully otherwise fail task
if (success) {
success = false;
returnVal = 3;
String mesg = "Job Commit failed with exception '" + Utilities.getNameMessage(e) + "'";
console.printError(mesg, "\n" + org.apache.hadoop.util.StringUtils.stringifyException(e));
}
}
return (returnVal);
}
private void handleSampling(DriverContext context, MapWork mWork, JobConf job, HiveConf conf)
throws Exception {
assert mWork.getAliasToWork().keySet().size() == 1;
String alias = mWork.getAliases().get(0);
Operator<?> topOp = mWork.getAliasToWork().get(alias);
PartitionDesc partDesc = mWork.getAliasToPartnInfo().get(alias);
ArrayList<String> paths = mWork.getPaths();
ArrayList<PartitionDesc> parts = mWork.getPartitionDescs();
Path onePath = new Path(paths.get(0));
String tmpPath = context.getCtx().getExternalTmpFileURI(onePath.toUri());
Path partitionFile = new Path(tmpPath, ".partitions");
ShimLoader.getHadoopShims().setTotalOrderPartitionFile(job, partitionFile);
PartitionKeySampler sampler = new PartitionKeySampler();
if (mWork.getSamplingType() == MapWork.SAMPLING_ON_PREV_MR) {
console.printInfo("Use sampling data created in previous MR");
// merges sampling data from previous MR and make paritition keys for total sort
for (String path : paths) {
Path inputPath = new Path(path);
FileSystem fs = inputPath.getFileSystem(job);
for (FileStatus status : fs.globStatus(new Path(inputPath, ".sampling*"))) {
sampler.addSampleFile(status.getPath(), job);
}
}
} else if (mWork.getSamplingType() == MapWork.SAMPLING_ON_START) {
console.printInfo("Creating sampling data..");
assert topOp instanceof TableScanOperator;
TableScanOperator ts = (TableScanOperator) topOp;
FetchWork fetchWork;
if (!partDesc.isPartitioned()) {
assert paths.size() == 1;
fetchWork = new FetchWork(paths.get(0), partDesc.getTableDesc());
} else {
fetchWork = new FetchWork(paths, parts, partDesc.getTableDesc());
}
fetchWork.setSource(ts);
// random sampling
FetchOperator fetcher = PartitionKeySampler.createSampler(fetchWork, conf, job, ts);
try {
ts.initialize(conf, new ObjectInspector[]{fetcher.getOutputObjectInspector()});
ts.setOutputCollector(sampler);
while (fetcher.pushRow()) { }
} finally {
fetcher.clearFetchContext();
}
} else {
throw new IllegalArgumentException("Invalid sampling type " + mWork.getSamplingType());
}
sampler.writePartitionKeys(partitionFile, job);
}
/**
* Set hive input format, and input format file if necessary.
*/
protected void setInputAttributes(Configuration conf) {
MapWork mWork = work.getMapWork();
if (mWork.getInputformat() != null) {
HiveConf.setVar(conf, HiveConf.ConfVars.HIVEINPUTFORMAT, mWork.getInputformat());
}
if (mWork.getIndexIntermediateFile() != null) {
conf.set("hive.index.compact.file", mWork.getIndexIntermediateFile());
conf.set("hive.index.blockfilter.file", mWork.getIndexIntermediateFile());
}
// Intentionally overwrites anything the user may have put here
conf.setBoolean("hive.input.format.sorted", mWork.isInputFormatSorted());
}
public boolean mapStarted() {
return this.jobExecHelper.mapStarted();
}
public boolean reduceStarted() {
return this.jobExecHelper.reduceStarted();
}
public boolean mapDone() {
return this.jobExecHelper.mapDone();
}
public boolean reduceDone() {
return this.jobExecHelper.reduceDone();
}
private static void printUsage() {
System.err.println("ExecDriver -plan <plan-file> [-jobconffile <job conf file>]"
+ "[-files <file1>[,<file2>] ...]");
System.exit(1);
}
/**
* we are running the hadoop job via a sub-command. this typically happens when we are running
* jobs in local mode. the log4j in this mode is controlled as follows: 1. if the admin provides a
* log4j properties file especially for execution mode - then we pick that up 2. otherwise - we
* default to the regular hive log4j properties if one is supplied 3. if none of the above two
* apply - we don't do anything - the log4j properties would likely be determined by hadoop.
*
* The intention behind providing a separate option #1 is to be able to collect hive run time logs
* generated in local mode in a separate (centralized) location if desired. This mimics the
* behavior of hive run time logs when running against a hadoop cluster where they are available
* on the tasktracker nodes.
*/
private static void setupChildLog4j(Configuration conf) {
try {
LogUtils.initHiveExecLog4j();
} catch (LogInitializationException e) {
System.err.println(e.getMessage());
}
}
@SuppressWarnings("unchecked")
public static void main(String[] args) throws IOException, HiveException {
String planFileName = null;
String jobConfFileName = null;
boolean noLog = false;
String files = null;
boolean localtask = false;
try {
for (int i = 0; i < args.length; i++) {
if (args[i].equals("-plan")) {
planFileName = args[++i];
} else if (args[i].equals("-jobconffile")) {
jobConfFileName = args[++i];
} else if (args[i].equals("-nolog")) {
noLog = true;
} else if (args[i].equals("-files")) {
files = args[++i];
} else if (args[i].equals("-localtask")) {
localtask = true;
}
}
} catch (IndexOutOfBoundsException e) {
System.err.println("Missing argument to option");
printUsage();
}
JobConf conf;
if (localtask) {
conf = new JobConf(MapredLocalTask.class);
} else {
conf = new JobConf(ExecDriver.class);
}
if (jobConfFileName != null) {
conf.addResource(new Path(jobConfFileName));
}
if (files != null) {
conf.set("tmpfiles", files);
}
if(ShimLoader.getHadoopShims().isSecurityEnabled()){
String hadoopAuthToken =
System.getenv(ShimLoader.getHadoopShims().getTokenFileLocEnvName());
if(hadoopAuthToken != null){
conf.set("mapreduce.job.credentials.binary", hadoopAuthToken);
}
}
boolean isSilent = HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVESESSIONSILENT);
if (noLog) {
// If started from main(), and noLog is on, we should not output
// any logs. To turn the log on, please set -Dtest.silent=false
BasicConfigurator.resetConfiguration();
BasicConfigurator.configure(new NullAppender());
} else {
setupChildLog4j(conf);
}
Log LOG = LogFactory.getLog(ExecDriver.class.getName());
LogHelper console = new LogHelper(LOG, isSilent);
if (planFileName == null) {
console.printError("Must specify Plan File Name");
printUsage();
}
// print out the location of the log file for the user so
// that it's easy to find reason for local mode execution failures
for (Appender appender : Collections.list((Enumeration<Appender>) LogManager.getRootLogger()
.getAllAppenders())) {
if (appender instanceof FileAppender) {
console.printInfo("Execution log at: " + ((FileAppender) appender).getFile());
}
}
// the plan file should always be in local directory
Path p = new Path(planFileName);
FileSystem fs = FileSystem.getLocal(conf);
InputStream pathData = fs.open(p);
// this is workaround for hadoop-17 - libjars are not added to classpath of the
// child process. so we add it here explicitly
String auxJars = HiveConf.getVar(conf, HiveConf.ConfVars.HIVEAUXJARS);
String addedJars = HiveConf.getVar(conf, HiveConf.ConfVars.HIVEADDEDJARS);
try {
// see also - code in CliDriver.java
ClassLoader loader = conf.getClassLoader();
if (StringUtils.isNotBlank(auxJars)) {
loader = Utilities.addToClassPath(loader, StringUtils.split(auxJars, ","));
}
if (StringUtils.isNotBlank(addedJars)) {
loader = Utilities.addToClassPath(loader, StringUtils.split(addedJars, ","));
}
conf.setClassLoader(loader);
// Also set this to the Thread ContextClassLoader, so new threads will
// inherit
// this class loader, and propagate into newly created Configurations by
// those
// new threads.
Thread.currentThread().setContextClassLoader(loader);
} catch (Exception e) {
throw new HiveException(e.getMessage(), e);
}
int ret;
if (localtask) {
memoryMXBean = ManagementFactory.getMemoryMXBean();
MapredLocalWork plan = (MapredLocalWork) Utilities.deserializePlan(pathData);
MapredLocalTask ed = new MapredLocalTask(plan, conf, isSilent);
ret = ed.executeFromChildJVM(new DriverContext());
} else {
MapredWork plan = (MapredWork) Utilities.deserializePlan(pathData);
ExecDriver ed = new ExecDriver(plan, conf, isSilent);
ret = ed.execute(new DriverContext());
}
if (ret != 0) {
System.exit(ret);
}
}
/**
* Given a Hive Configuration object - generate a command line fragment for passing such
* configuration information to ExecDriver.
*/
public static String generateCmdLine(HiveConf hconf, Context ctx)
throws IOException {
HiveConf tempConf = new HiveConf();
Path hConfFilePath = new Path(ctx.getLocalTmpFileURI(), JOBCONF_FILENAME);
OutputStream out = null;
Properties deltaP = hconf.getChangedProperties();
boolean hadoopLocalMode = ShimLoader.getHadoopShims().isLocalMode(hconf);
String hadoopSysDir = "mapred.system.dir";
String hadoopWorkDir = "mapred.local.dir";
for (Object one : deltaP.keySet()) {
String oneProp = (String) one;
if (hadoopLocalMode && (oneProp.equals(hadoopSysDir) || oneProp.equals(hadoopWorkDir))) {
continue;
}
tempConf.set(oneProp, deltaP.getProperty(oneProp));
}
// Multiple concurrent local mode job submissions can cause collisions in
// working dirs and system dirs
// Workaround is to rename map red working dir to a temp dir in such cases
if (hadoopLocalMode) {
tempConf.set(hadoopSysDir, hconf.get(hadoopSysDir) + "/" + Utilities.randGen.nextInt());
tempConf.set(hadoopWorkDir, hconf.get(hadoopWorkDir) + "/" + Utilities.randGen.nextInt());
}
try {
out = FileSystem.getLocal(hconf).create(hConfFilePath);
tempConf.writeXml(out);
} finally {
if (out != null) {
out.close();
}
}
return " -jobconffile " + hConfFilePath.toString();
}
@Override
public boolean isMapRedTask() {
return true;
}
@Override
public Collection<Operator<? extends OperatorDesc>> getTopOperators() {
return getWork().getMapWork().getAliasToWork().values();
}
@Override
public boolean hasReduce() {
MapredWork w = getWork();
return w.getReduceWork() != null;
}
@Override
public StageType getType() {
return StageType.MAPRED;
}
@Override
public String getName() {
return "MAPRED";
}
@Override
public void updateCounters(Counters ctrs, RunningJob rj) throws IOException {
for (Operator<? extends OperatorDesc> op : work.getMapWork().getAliasToWork().values()) {
op.updateCounters(ctrs);
}
if (work.getReduceWork() != null) {
work.getReduceWork().getReducer().updateCounters(ctrs);
}
}
@Override
public void logPlanProgress(SessionState ss) throws IOException {
ss.getHiveHistory().logPlanProgress(queryPlan);
}
@Override
public void shutdown() {
super.shutdown();
if (rj != null) {
try {
rj.killJob();
} catch (Exception e) {
LOG.warn("failed to kill job " + rj.getID(), e);
}
rj = null;
}
}
}