public void close() throws IOException {
if (txnMgr != null) txnMgr.closeTxnManager();
JavaUtils.closeClassLoadersTo(conf.getClassLoader(), parentLoader);
File resourceDir = new File(getConf().getVar(HiveConf.ConfVars.DOWNLOADED_RESOURCES_DIR));
LOG.debug("Removing resource dir " + resourceDir);
try {
if (resourceDir.exists()) {
FileUtils.deleteDirectory(resourceDir);
}
} catch (IOException e) {
LOG.info("Error removing session resource dir " + resourceDir, e);
} finally {
detachSession();
}
try {
if (tezSessionState != null) {
TezSessionPoolManager.getInstance().close(tezSessionState, false);
}
} catch (Exception e) {
LOG.info("Error closing tez session", e);
} finally {
tezSessionState = null;
}
if (sparkSession != null) {
try {
SparkSessionManagerImpl.getInstance().closeSession(sparkSession);
} catch (Exception ex) {
LOG.error("Error closing spark session.", ex);
} finally {
sparkSession = null;
}
}
dropSessionPaths(conf);
}
/** 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;
Path emptyScratchDir;
MapWork mWork = work.getMapWork();
ReduceWork rWork = work.getReduceWork();
try {
if (ctx == null) {
ctx = new Context(job);
ctxCreated = true;
}
emptyScratchDir = ctx.getMRTmpPath();
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;
}
HiveFileFormatUtils.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 {
String partitioner = HiveConf.getVar(job, ConfVars.HIVEPARTITIONER);
job.setPartitionerClass(JavaUtils.loadClass(partitioner));
} catch (ClassNotFoundException e) {
throw new RuntimeException(e.getMessage(), e);
}
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 (mWork.isUseBucketizedHiveInputFormat()) {
inpFormat = BucketizedHiveInputFormat.class.getName();
}
LOG.info("Using " + inpFormat);
try {
job.setInputFormat(JavaUtils.loadClass(inpFormat));
} catch (ClassNotFoundException e) {
throw new RuntimeException(e.getMessage(), e);
}
// 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.getMapRedLocalWork();
if (localwork != null && localwork.hasStagedAlias()) {
if (!ShimLoader.getHadoopShims().isLocalMode(job)) {
Path localPath = localwork.getTmpPath();
Path hdfsPath = mWork.getTmpHDFSPath();
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 stageId = this.getId();
String archiveFileName = Utilities.generateTarFileName(stageId);
localwork.setStageID(stageId);
CompressionUtils.tar(localPath.toUri().getPath(), fileNames, archiveFileName);
Path archivePath = Utilities.generateTarPath(localPath, stageId);
LOG.info("Archive " + hashtableFiles.length + " hash table files to " + archivePath);
// upload archive file to hdfs
Path hdfsFilePath = Utilities.generateTarPath(hdfsPath, stageId);
short replication = (short) job.getInt("mapred.submit.replication", 10);
hdfs.copyFromLocalFile(archivePath, hdfsFilePath);
hdfs.setReplication(hdfsFilePath, replication);
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, emptyScratchDir, ctx, false);
Utilities.setInputPaths(job, inputPaths);
Utilities.setMapRedWork(job, work, ctx.getMRTmpPath());
if (mWork.getSamplingType() > 0 && rWork != null && job.getNumReduceTasks() > 1) {
try {
handleSampling(ctx, mWork, job);
job.setPartitionerClass(HiveTotalOrderPartitioner.class);
} catch (IllegalStateException e) {
console.printInfo("Not enough sampling data.. Rolling back to single reducer task");
rWork.setNumReduceTasks(1);
job.setNumReduceTasks(1);
} catch (Exception e) {
LOG.error("Sampling error", e);
console.printError(
e.toString(), "\n" + org.apache.hadoop.util.StringUtils.stringifyException(e));
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 tracker is not behaving well.
Throttle.checkJobTracker(job, LOG);
if (mWork.isGatheringStats() || (rWork != null && rWork.isGatheringStats())) {
// initialize stats publishing table
StatsPublisher statsPublisher;
StatsFactory factory = StatsFactory.newFactory(job);
if (factory != null) {
statsPublisher = factory.getStatsPublisher();
List<String> statsTmpDir = Utilities.getStatsTmpDirs(mWork, job);
if (rWork != null) {
statsTmpDir.addAll(Utilities.getStatsTmpDirs(rWork, job));
}
StatsCollectionContext sc = new StatsCollectionContext(job);
sc.setStatsTmpDirs(statsTmpDir);
if (!statsPublisher.init(sc)) { // 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);
SessionState ss = SessionState.get();
if (HiveConf.getVar(job, HiveConf.ConfVars.HIVE_EXECUTION_ENGINE).equals("tez")
&& ss != null) {
TezSessionState session = ss.getTezSession();
TezSessionPoolManager.getInstance().close(session, true);
}
// 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, ctx.getHiveTxnManager());
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();
}
jobID = rj.getID().toString();
}
} catch (Exception e) {
LOG.warn("Failed while cleaning up ", e);
} finally {
HadoopJobExecHelper.runningJobs.remove(rj);
}
}
// get the list of Dynamic partition paths
try {
if (rj != null) {
if (mWork.getAliasToWork() != null) {
for (Operator<? extends OperatorDesc> op : mWork.getAliasToWork().values()) {
op.jobClose(job, success);
}
}
if (rWork != null) {
rWork.getReducer().jobClose(job, success);
}
}
} 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);
}