예제 #1
0
  /** 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);
  }
예제 #2
0
  private void run(String[] args) throws Exception {
    LlapOptionsProcessor optionsProcessor = new LlapOptionsProcessor();
    LlapOptions options = optionsProcessor.processOptions(args);

    if (options == null) {
      // help
      return;
    }

    Path tmpDir = new Path(options.getDirectory());

    if (conf == null) {
      throw new Exception("Cannot load any configuration to run command");
    }

    FileSystem fs = FileSystem.get(conf);
    FileSystem lfs = FileSystem.getLocal(conf).getRawFileSystem();

    // needed so that the file is actually loaded into configuration.
    for (String f : NEEDED_CONFIGS) {
      conf.addResource(f);
      if (conf.getResource(f) == null) {
        throw new Exception("Unable to find required config file: " + f);
      }
    }
    for (String f : OPTIONAL_CONFIGS) {
      conf.addResource(f);
    }
    conf.reloadConfiguration();

    if (options.getName() != null) {
      // update service registry configs - caveat: this has nothing to do with the actual settings
      // as read by the AM
      // if needed, use --hiveconf llap.daemon.service.hosts=@llap0 to dynamically switch between
      // instances
      conf.set(ConfVars.LLAP_DAEMON_SERVICE_HOSTS.varname, "@" + options.getName());
    }

    if (options.getSize() != -1) {
      if (options.getCache() != -1) {
        Preconditions.checkArgument(
            options.getCache() < options.getSize(),
            "Cache has to be smaller than the container sizing");
      }
      if (options.getXmx() != -1) {
        Preconditions.checkArgument(
            options.getXmx() < options.getSize(),
            "Working memory has to be smaller than the container sizing");
      }
      if (HiveConf.getBoolVar(conf, HiveConf.ConfVars.LLAP_ALLOCATOR_DIRECT)) {
        Preconditions.checkArgument(
            options.getXmx() + options.getCache() < options.getSize(),
            "Working memory + cache has to be smaller than the containing sizing ");
      }
    }

    final long minAlloc = conf.getInt(YarnConfiguration.RM_SCHEDULER_MINIMUM_ALLOCATION_MB, -1);
    if (options.getSize() != -1) {
      final long containerSize = options.getSize() / (1024 * 1024);
      Preconditions.checkArgument(
          containerSize >= minAlloc,
          "Container size should be greater than minimum allocation(%s)",
          minAlloc + "m");
      conf.setLong(ConfVars.LLAP_DAEMON_YARN_CONTAINER_MB.varname, containerSize);
    }

    if (options.getExecutors() != -1) {
      conf.setLong(ConfVars.LLAP_DAEMON_NUM_EXECUTORS.varname, options.getExecutors());
      // TODO: vcpu settings - possibly when DRFA works right
    }

    if (options.getCache() != -1) {
      conf.setLong(HiveConf.ConfVars.LLAP_IO_MEMORY_MAX_SIZE.varname, options.getCache());
    }

    if (options.getXmx() != -1) {
      // Needs more explanation here
      // Xmx is not the max heap value in JDK8
      // You need to subtract 50% of the survivor fraction from this, to get actual usable memory
      // before it goes into GC
      conf.setLong(
          ConfVars.LLAP_DAEMON_MEMORY_PER_INSTANCE_MB.varname,
          (long) (options.getXmx()) / (1024 * 1024));
    }

    for (Entry<Object, Object> props : options.getConfig().entrySet()) {
      conf.set((String) props.getKey(), (String) props.getValue());
    }

    URL logger = conf.getResource("llap-daemon-log4j2.properties");

    if (null == logger) {
      throw new Exception("Unable to find required config file: llap-daemon-log4j2.properties");
    }

    Path home = new Path(System.getenv("HIVE_HOME"));
    Path scripts = new Path(new Path(new Path(home, "scripts"), "llap"), "bin");

    if (!lfs.exists(home)) {
      throw new Exception("Unable to find HIVE_HOME:" + home);
    } else if (!lfs.exists(scripts)) {
      LOG.warn("Unable to find llap scripts:" + scripts);
    }

    Path libDir = new Path(tmpDir, "lib");

    String tezLibs = conf.get("tez.lib.uris");
    if (tezLibs == null) {
      LOG.warn("Missing tez.lib.uris in tez-site.xml");
    }
    if (LOG.isDebugEnabled()) {
      LOG.debug("Copying tez libs from " + tezLibs);
    }
    lfs.mkdirs(libDir);
    fs.copyToLocalFile(new Path(tezLibs), new Path(libDir, "tez.tar.gz"));
    CompressionUtils.unTar(new Path(libDir, "tez.tar.gz").toString(), libDir.toString(), true);
    lfs.delete(new Path(libDir, "tez.tar.gz"), false);

    lfs.copyFromLocalFile(new Path(Utilities.jarFinderGetJar(LlapInputFormat.class)), libDir);
    lfs.copyFromLocalFile(new Path(Utilities.jarFinderGetJar(HiveInputFormat.class)), libDir);

    // copy default aux classes (json/hbase)

    for (String className : DEFAULT_AUX_CLASSES) {
      localizeJarForClass(lfs, libDir, className, false);
    }

    if (options.getIsHBase()) {
      try {
        localizeJarForClass(lfs, libDir, HBASE_SERDE_CLASS, true);
        Job fakeJob = new Job(new JobConf()); // HBase API is convoluted.
        TableMapReduceUtil.addDependencyJars(fakeJob);
        Collection<String> hbaseJars = fakeJob.getConfiguration().getStringCollection("tmpjars");
        for (String jarPath : hbaseJars) {
          if (!jarPath.isEmpty()) {
            lfs.copyFromLocalFile(new Path(jarPath), libDir);
          }
        }
      } catch (Throwable t) {
        String err = "Failed to add HBase jars. Use --auxhbase=false to avoid localizing them";
        LOG.error(err);
        System.err.println(err);
        throw new RuntimeException(t);
      }
    }

    String auxJars = options.getAuxJars();
    if (auxJars != null && !auxJars.isEmpty()) {
      // TODO: transitive dependencies warning?
      String[] jarPaths = auxJars.split(",");
      for (String jarPath : jarPaths) {
        if (!jarPath.isEmpty()) {
          lfs.copyFromLocalFile(new Path(jarPath), libDir);
        }
      }
    }

    Path confPath = new Path(tmpDir, "conf");
    lfs.mkdirs(confPath);

    for (String f : NEEDED_CONFIGS) {
      copyConfig(options, lfs, confPath, f);
    }
    for (String f : OPTIONAL_CONFIGS) {
      try {
        copyConfig(options, lfs, confPath, f);
      } catch (Throwable t) {
        LOG.info("Error getting an optional config " + f + "; ignoring: " + t.getMessage());
      }
    }

    lfs.copyFromLocalFile(new Path(logger.toString()), confPath);

    // extract configs for processing by the python fragments in Slider
    JSONObject configs = new JSONObject();

    configs.put(
        ConfVars.LLAP_DAEMON_YARN_CONTAINER_MB.varname,
        HiveConf.getIntVar(conf, ConfVars.LLAP_DAEMON_YARN_CONTAINER_MB));

    configs.put(
        HiveConf.ConfVars.LLAP_IO_MEMORY_MAX_SIZE.varname,
        HiveConf.getLongVar(conf, HiveConf.ConfVars.LLAP_IO_MEMORY_MAX_SIZE));

    configs.put(
        HiveConf.ConfVars.LLAP_ALLOCATOR_DIRECT.varname,
        HiveConf.getBoolVar(conf, HiveConf.ConfVars.LLAP_ALLOCATOR_DIRECT));

    configs.put(
        ConfVars.LLAP_DAEMON_MEMORY_PER_INSTANCE_MB.varname,
        HiveConf.getIntVar(conf, ConfVars.LLAP_DAEMON_MEMORY_PER_INSTANCE_MB));

    configs.put(
        ConfVars.LLAP_DAEMON_VCPUS_PER_INSTANCE.varname,
        HiveConf.getIntVar(conf, ConfVars.LLAP_DAEMON_VCPUS_PER_INSTANCE));

    configs.put(
        ConfVars.LLAP_DAEMON_NUM_EXECUTORS.varname,
        HiveConf.getIntVar(conf, ConfVars.LLAP_DAEMON_NUM_EXECUTORS));

    configs.put(
        YarnConfiguration.RM_SCHEDULER_MINIMUM_ALLOCATION_MB,
        conf.getInt(YarnConfiguration.RM_SCHEDULER_MINIMUM_ALLOCATION_MB, -1));

    configs.put(
        YarnConfiguration.RM_SCHEDULER_MINIMUM_ALLOCATION_VCORES,
        conf.getInt(YarnConfiguration.RM_SCHEDULER_MINIMUM_ALLOCATION_VCORES, -1));

    FSDataOutputStream os = lfs.create(new Path(tmpDir, "config.json"));
    OutputStreamWriter w = new OutputStreamWriter(os);
    configs.write(w);
    w.close();
    os.close();

    lfs.close();
    fs.close();

    if (LOG.isDebugEnabled()) {
      LOG.debug("Exiting successfully");
    }
  }