Examples with StatsCollectionContext org.apache.hadoop.hive.ql.stats.StatsCollectionContext used on opensource projects

Example 1 with StatsCollectionContext

use of org.apache.hadoop.hive.ql.stats.StatsCollectionContext in project hive by apache.

the class StatsTask method getContext.

private StatsCollectionContext getContext() throws HiveException {
    StatsCollectionContext scc = new StatsCollectionContext(conf);
    Task sourceTask = getWork().getSourceTask();
    if (sourceTask == null) {
        throw new HiveException(ErrorMsg.STATSAGGREGATOR_SOURCETASK_NULL.getErrorCodedMsg());
    }
    scc.setTask(sourceTask);
    scc.setStatsTmpDir(this.getWork().getStatsTmpDir());
    return scc;
}

Example 2 with StatsCollectionContext

use of org.apache.hadoop.hive.ql.stats.StatsCollectionContext in project hive by apache.

the class StatsTask method aggregateStats.

private int aggregateStats(Hive db) {
    StatsAggregator statsAggregator = null;
    int ret = 0;
    StatsCollectionContext scc = null;
    EnvironmentContext environmentContext = null;
    try {
        // Stats setup:
        final Warehouse wh = new Warehouse(conf);
        if (!getWork().getNoStatsAggregator() && !getWork().isNoScanAnalyzeCommand()) {
            try {
                scc = getContext();
                statsAggregator = createStatsAggregator(scc, conf);
            } catch (HiveException e) {
                if (HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_STATS_RELIABLE)) {
                    throw e;
                }
                console.printError(ErrorMsg.STATS_SKIPPING_BY_ERROR.getErrorCodedMsg(e.toString()));
            }
        }
        List<Partition> partitions = getPartitionsList(db);
        boolean atomic = HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_STATS_ATOMIC);
        String tableFullName = table.getDbName() + "." + table.getTableName();
        if (partitions == null) {
            org.apache.hadoop.hive.metastore.api.Table tTable = table.getTTable();
            Map<String, String> parameters = tTable.getParameters();
            // acidTable will not have accurate stats unless it is set through analyze command.
            if (work.getTableSpecs() == null && AcidUtils.isAcidTable(table)) {
                StatsSetupConst.setBasicStatsState(parameters, StatsSetupConst.FALSE);
            } else if (work.getTableSpecs() != null || (work.getLoadTableDesc() != null && work.getLoadTableDesc().getReplace()) || (work.getLoadFileDesc() != null && !work.getLoadFileDesc().getDestinationCreateTable().isEmpty())) {
                StatsSetupConst.setBasicStatsState(parameters, StatsSetupConst.TRUE);
            }
            // non-partitioned tables:
            if (!existStats(parameters) && atomic) {
                return 0;
            }
            // For eg. if a file is being loaded, the old number of rows are not valid
            if (work.isClearAggregatorStats()) {
                // we choose to keep the invalid stats and only change the setting.
                StatsSetupConst.setBasicStatsState(parameters, StatsSetupConst.FALSE);
            }
            updateQuickStats(wh, parameters, tTable.getSd());
            if (StatsSetupConst.areBasicStatsUptoDate(parameters)) {
                if (statsAggregator != null) {
                    String prefix = getAggregationPrefix(table, null);
                    updateStats(statsAggregator, parameters, prefix, atomic);
                }
                // write table stats to metastore
                if (!getWork().getNoStatsAggregator()) {
                    environmentContext = new EnvironmentContext();
                    environmentContext.putToProperties(StatsSetupConst.STATS_GENERATED, StatsSetupConst.TASK);
                }
            }
            getHive().alterTable(tableFullName, new Table(tTable), environmentContext);
            if (conf.getBoolVar(ConfVars.TEZ_EXEC_SUMMARY)) {
                console.printInfo("Table " + tableFullName + " stats: [" + toString(parameters) + ']');
            }
            LOG.info("Table " + tableFullName + " stats: [" + toString(parameters) + ']');
        } else {
            // Partitioned table:
            // Need to get the old stats of the partition
            // and update the table stats based on the old and new stats.
            List<Partition> updates = new ArrayList<Partition>();
            //Get the file status up-front for all partitions. Beneficial in cases of blob storage systems
            final Map<String, FileStatus[]> fileStatusMap = new ConcurrentHashMap<String, FileStatus[]>();
            int poolSize = conf.getInt(ConfVars.HIVE_MOVE_FILES_THREAD_COUNT.varname, 1);
            // In case thread count is set to 0, use single thread.
            poolSize = Math.max(poolSize, 1);
            final ExecutorService pool = Executors.newFixedThreadPool(poolSize, new ThreadFactoryBuilder().setDaemon(true).setNameFormat("stats-updater-thread-%d").build());
            final List<Future<Void>> futures = Lists.newLinkedList();
            LOG.debug("Getting file stats of all partitions. threadpool size:" + poolSize);
            try {
                for (final Partition partn : partitions) {
                    final String partitionName = partn.getName();
                    final org.apache.hadoop.hive.metastore.api.Partition tPart = partn.getTPartition();
                    Map<String, String> parameters = tPart.getParameters();
                    if (!existStats(parameters) && atomic) {
                        continue;
                    }
                    futures.add(pool.submit(new Callable<Void>() {

                        @Override
                        public Void call() throws Exception {
                            FileStatus[] partfileStatus = wh.getFileStatusesForSD(tPart.getSd());
                            fileStatusMap.put(partitionName, partfileStatus);
                            return null;
                        }
                    }));
                }
                pool.shutdown();
                for (Future<Void> future : futures) {
                    future.get();
                }
            } catch (InterruptedException e) {
                LOG.debug("Cancelling " + futures.size() + " file stats lookup tasks");
                //cancel other futures
                for (Future future : futures) {
                    future.cancel(true);
                }
                // Fail the query if the stats are supposed to be reliable
                if (work.isStatsReliable()) {
                    ret = 1;
                }
            } finally {
                if (pool != null) {
                    pool.shutdownNow();
                }
                LOG.debug("Finished getting file stats of all partitions");
            }
            for (Partition partn : partitions) {
                //
                // get the old partition stats
                //
                org.apache.hadoop.hive.metastore.api.Partition tPart = partn.getTPartition();
                Map<String, String> parameters = tPart.getParameters();
                if (work.getTableSpecs() == null && AcidUtils.isAcidTable(table)) {
                    StatsSetupConst.setBasicStatsState(parameters, StatsSetupConst.FALSE);
                } else if (work.getTableSpecs() != null || (work.getLoadTableDesc() != null && work.getLoadTableDesc().getReplace()) || (work.getLoadFileDesc() != null && !work.getLoadFileDesc().getDestinationCreateTable().isEmpty())) {
                    StatsSetupConst.setBasicStatsState(parameters, StatsSetupConst.TRUE);
                }
                //only when the stats exist, it is added to fileStatusMap
                if (!fileStatusMap.containsKey(partn.getName())) {
                    continue;
                }
                // For eg. if a file is being loaded, the old number of rows are not valid
                if (work.isClearAggregatorStats()) {
                    // we choose to keep the invalid stats and only change the setting.
                    StatsSetupConst.setBasicStatsState(parameters, StatsSetupConst.FALSE);
                }
                updateQuickStats(parameters, fileStatusMap.get(partn.getName()));
                if (StatsSetupConst.areBasicStatsUptoDate(parameters)) {
                    if (statsAggregator != null) {
                        String prefix = getAggregationPrefix(table, partn);
                        updateStats(statsAggregator, parameters, prefix, atomic);
                    }
                    if (!getWork().getNoStatsAggregator()) {
                        environmentContext = new EnvironmentContext();
                        environmentContext.putToProperties(StatsSetupConst.STATS_GENERATED, StatsSetupConst.TASK);
                    }
                }
                updates.add(new Partition(table, tPart));
                if (conf.getBoolVar(ConfVars.TEZ_EXEC_SUMMARY)) {
                    console.printInfo("Partition " + tableFullName + partn.getSpec() + " stats: [" + toString(parameters) + ']');
                }
                LOG.info("Partition " + tableFullName + partn.getSpec() + " stats: [" + toString(parameters) + ']');
            }
            if (!updates.isEmpty()) {
                db.alterPartitions(tableFullName, updates, environmentContext);
            }
        }
    } catch (Exception e) {
        console.printInfo("[Warning] could not update stats.", "Failed with exception " + e.getMessage() + "\n" + StringUtils.stringifyException(e));
        // Fail the query if the stats are supposed to be reliable
        if (work.isStatsReliable()) {
            ret = 1;
        }
    } finally {
        if (statsAggregator != null) {
            statsAggregator.closeConnection(scc);
        }
    }
    // anything else indicates failure
    return ret;
}

Example 3 with StatsCollectionContext

use of org.apache.hadoop.hive.ql.stats.StatsCollectionContext in project hive by apache.

the class DagUtils method createVertex.

/**
 * Create a vertex from a given work object.
 *
 * @param conf JobConf to be used to this execution unit
 * @param work The instance of BaseWork representing the actual work to be performed
 * by this vertex.
 * @param scratchDir HDFS scratch dir for this execution unit.
 * @param fileSystem FS corresponding to scratchDir and LocalResources
 * @param ctx This query's context
 * @return Vertex
 */
@SuppressWarnings("deprecation")
public Vertex createVertex(JobConf conf, BaseWork work, Path scratchDir, FileSystem fileSystem, Context ctx, boolean hasChildren, TezWork tezWork, VertexType vertexType, Map<String, LocalResource> localResources) throws Exception {
    Vertex v = null;
    // BaseWork.
    if (work instanceof MapWork) {
        v = createVertex(conf, (MapWork) work, fileSystem, scratchDir, ctx, vertexType, localResources);
    } else if (work instanceof ReduceWork) {
        v = createVertex(conf, (ReduceWork) work, fileSystem, scratchDir, ctx, localResources);
    } else if (work instanceof MergeJoinWork) {
        v = createVertex(conf, (MergeJoinWork) work, fileSystem, scratchDir, ctx, vertexType, localResources);
        // set VertexManagerPlugin if whether it's a cross product destination vertex
        List<String> crossProductSources = new ArrayList<>();
        for (BaseWork parentWork : tezWork.getParents(work)) {
            if (tezWork.getEdgeType(parentWork, work) == EdgeType.XPROD_EDGE) {
                crossProductSources.add(parentWork.getName());
            }
        }
        if (!crossProductSources.isEmpty()) {
            CartesianProductConfig cpConfig = new CartesianProductConfig(crossProductSources);
            v.setVertexManagerPlugin(VertexManagerPluginDescriptor.create(CartesianProductVertexManager.class.getName()).setUserPayload(cpConfig.toUserPayload(new TezConfiguration(conf))));
        // parallelism shouldn't be set for cartesian product vertex
        }
    } else {
        // something is seriously wrong if this is happening
        throw new HiveException(ErrorMsg.GENERIC_ERROR.getErrorCodedMsg());
    }
    // initialize stats publisher if necessary
    if (work.isGatheringStats()) {
        StatsPublisher statsPublisher;
        StatsFactory factory = StatsFactory.newFactory(conf);
        if (factory != null) {
            StatsCollectionContext sCntxt = new StatsCollectionContext(conf);
            sCntxt.setStatsTmpDirs(Utilities.getStatsTmpDirs(work, conf));
            statsPublisher = factory.getStatsPublisher();
            if (!statsPublisher.init(sCntxt)) {
                // creating stats table if not exists
                if (HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_STATS_RELIABLE)) {
                    throw new HiveException(ErrorMsg.STATSPUBLISHER_INITIALIZATION_ERROR.getErrorCodedMsg());
                }
            }
        }
    }
    // final vertices need to have at least one output
    if (!hasChildren) {
        v.addDataSink("out_" + work.getName(), new DataSinkDescriptor(OutputDescriptor.create(MROutput.class.getName()).setUserPayload(TezUtils.createUserPayloadFromConf(conf)), null, null));
    }
    return v;
}

Example 4 with StatsCollectionContext

use of org.apache.hadoop.hive.ql.stats.StatsCollectionContext in project hive by apache.

the class ExecDriver method execute.

/**
 * Execute a query plan using Hadoop.
 */
@SuppressWarnings({ "deprecation", "unchecked" })
@Override
public int execute() {
    IOPrepareCache ioPrepareCache = IOPrepareCache.get();
    ioPrepareCache.clear();
    boolean success = true;
    boolean ctxCreated = false;
    Path emptyScratchDir;
    JobClient jc = null;
    if (taskQueue.isShutdown()) {
        LOG.warn("Task was cancelled");
        return 5;
    }
    MapWork mWork = work.getMapWork();
    ReduceWork rWork = work.getReduceWork();
    Context ctx = context;
    try {
        if (ctx == null) {
            ctx = new Context(job);
            ctxCreated = true;
        }
        emptyScratchDir = ctx.getMRTmpPath();
        FileSystem fs = emptyScratchDir.getFileSystem(job);
        fs.mkdirs(emptyScratchDir);
    } catch (IOException e) {
        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.setMapRunnerClass(ExecMapRunner.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);
    }
    propagateSplitSettings(job, mWork);
    job.setNumReduceTasks(rWork != null ? rWork.getNumReduceTasks() : 0);
    job.setReducerClass(ExecReducer.class);
    // set input format information if necessary
    setInputAttributes(job);
    // HIVE-23354 enforces that MR speculative execution is disabled
    job.setBoolean(MRJobConfig.REDUCE_SPECULATIVE, false);
    job.setBoolean(MRJobConfig.MAP_SPECULATIVE, false);
    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);
    int returnVal = 0;
    boolean noName = StringUtils.isEmpty(job.get(MRJobConfig.JOB_NAME));
    if (noName) {
        // This is for a special case to ensure unit tests pass
        job.set(MRJobConfig.JOB_NAME, "JOB" + ThreadLocalRandom.current().nextInt());
    }
    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);
            }
        }
        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();
        // TODO: why is there a TezSession in MR ExecDriver?
        if (ss != null && HiveConf.getVar(job, ConfVars.HIVE_EXECUTION_ENGINE).equals("tez")) {
            // TODO: this is the only place that uses keepTmpDir. Why?
            TezSessionPoolManager.closeIfNotDefault(ss.getTezSession(), true);
        }
        HiveConfUtil.updateJobCredentialProviders(job);
        // Finally SUBMIT the JOB!
        if (taskQueue.isShutdown()) {
            LOG.warn("Task was cancelled");
            return 5;
        }
        rj = jc.submitJob(job);
        if (taskQueue.isShutdown()) {
            LOG.warn("Task was cancelled");
            killJob();
            return 5;
        }
        this.jobID = rj.getJobID();
        updateStatusInQueryDisplay();
        returnVal = jobExecHelper.progress(rj, jc, ctx);
        success = (returnVal == 0);
    } catch (Exception e) {
        setException(e);
        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.lang3.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) {
                    killJob();
                }
                jobID = rj.getID().toString();
            }
            if (jc != null) {
                jc.close();
            }
        } 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) {
            setException(e);
            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);
}

Example 5 with StatsCollectionContext

use of org.apache.hadoop.hive.ql.stats.StatsCollectionContext in project hive by apache.

the class FileSinkOperator method publishStats.

private void publishStats() throws HiveException {
    boolean isStatsReliable = conf.isStatsReliable();
    // Initializing a stats publisher
    StatsPublisher statsPublisher = Utilities.getStatsPublisher(jc);
    if (statsPublisher == null) {
        // just return, stats gathering should not block the main query
        LOG.error("StatsPublishing error: StatsPublisher is not initialized.");
        if (isStatsReliable) {
            throw new HiveException(ErrorMsg.STATSPUBLISHER_NOT_OBTAINED.getErrorCodedMsg());
        }
        return;
    }
    StatsCollectionContext sContext = new StatsCollectionContext(hconf);
    sContext.setStatsTmpDir(conf.getTmpStatsDir());
    if (!statsPublisher.connect(sContext)) {
        // just return, stats gathering should not block the main query
        LOG.error("StatsPublishing error: cannot connect to database");
        if (isStatsReliable) {
            throw new HiveException(ErrorMsg.STATSPUBLISHER_CONNECTION_ERROR.getErrorCodedMsg());
        }
        return;
    }
    String spSpec = conf.getStaticSpec();
    for (Map.Entry<String, FSPaths> entry : valToPaths.entrySet()) {
        // DP/LB
        String fspKey = entry.getKey();
        FSPaths fspValue = entry.getValue();
        if (Utilities.FILE_OP_LOGGER.isTraceEnabled()) {
            Utilities.FILE_OP_LOGGER.trace("Observing entry for stats " + fspKey + " => FSP with tmpPath " + fspValue.buildTmpPath());
        }
        // adds the taskId to the fspKey.
        if (conf.getDpSortState().equals(DPSortState.PARTITION_BUCKET_SORTED)) {
            String taskID = Utilities.getTaskIdFromFilename(fspKey);
            // if length of (prefix/ds=__HIVE_DEFAULT_PARTITION__/000000_0) is greater than max key prefix
            // and if (prefix/ds=10/000000_0) is less than max key prefix, then former will get hashed
            // to a smaller prefix (MD5hash/000000_0) and later will stored as such in staging stats table.
            // When stats gets aggregated in StatsTask only the keys that starts with "prefix" will be fetched.
            // Now that (prefix/ds=__HIVE_DEFAULT_PARTITION__) is hashed to a smaller prefix it will
            // not be retrieved from staging table and hence not aggregated. To avoid this issue
            // we will remove the taskId from the key which is redundant anyway.
            fspKey = fspKey.split(taskID)[0];
        }
        // split[0] = DP, split[1] = LB
        String[] split = splitKey(fspKey);
        String dpSpec = split[0];
        // key = "database.table/SP/DP/"LB/
        // Hive store lowercase table name in metastore, and Counters is character case sensitive, so we
        // use lowercase table name as prefix here, as StatsTask get table name from metastore to fetch counter.
        String prefix = conf.getTableInfo().getTableName().toLowerCase();
        prefix = Utilities.join(prefix, spSpec, dpSpec);
        prefix = prefix.endsWith(Path.SEPARATOR) ? prefix : prefix + Path.SEPARATOR;
        if (Utilities.FILE_OP_LOGGER.isTraceEnabled()) {
            Utilities.FILE_OP_LOGGER.trace("Prefix for stats " + prefix + " (from " + spSpec + ", " + dpSpec + ")");
        }
        Map<String, String> statsToPublish = new HashMap<String, String>();
        for (String statType : fspValue.getStoredStats()) {
            statsToPublish.put(statType, Long.toString(fspValue.stat.getStat(statType)));
        }
        if (!statsPublisher.publishStat(prefix, statsToPublish)) {
            LOG.error("Failed to publish stats");
            // Not changing the interface to maintain backward compatibility
            if (isStatsReliable) {
                throw new HiveException(ErrorMsg.STATSPUBLISHER_PUBLISHING_ERROR.getErrorCodedMsg());
            }
        }
    }
    sContext.setContextSuffix(getOperatorId());
    if (!statsPublisher.closeConnection(sContext)) {
        LOG.error("Failed to close stats");
        // Not changing the interface to maintain backward compatibility
        if (isStatsReliable) {
            throw new HiveException(ErrorMsg.STATSPUBLISHER_CLOSING_ERROR.getErrorCodedMsg());
        }
    }
}