Examples with MatrixCharacteristics org.apache.sysml.runtime.matrix.MatrixCharacteristics used on opensource projects

Example 61 with MatrixCharacteristics

use of org.apache.sysml.runtime.matrix.MatrixCharacteristics in project incubator-systemml by apache.

the class RemoteParForMR method runJob.

public static // inputs
RemoteParForJobReturn runJob(// inputs
long pfid, // inputs
String program, // inputs
String taskFile, // inputs
String resultFile, // inputs
MatrixObject colocatedDPMatrixObj, // opt params
boolean enableCPCaching, // opt params
int numMappers, // opt params
int replication, // opt params
int max_retry, // opt params
long minMem, // opt params
boolean jvmReuse) {
    RemoteParForJobReturn ret = null;
    String jobname = "ParFor-EMR";
    long t0 = DMLScript.STATISTICS ? System.nanoTime() : 0;
    JobConf job;
    job = new JobConf(RemoteParForMR.class);
    job.setJobName(jobname + pfid);
    // maintain dml script counters
    Statistics.incrementNoOfCompiledMRJobs();
    try {
        // ///
        // configure the MR job
        // set arbitrary CP program blocks that will perform in the mapper
        MRJobConfiguration.setProgramBlocks(job, program);
        // enable/disable caching
        MRJobConfiguration.setParforCachingConfig(job, enableCPCaching);
        // set mappers, reducers, combiners
        // map-only
        job.setMapperClass(RemoteParWorkerMapper.class);
        // set input format (one split per row, NLineInputFormat default N=1)
        if (ParForProgramBlock.ALLOW_DATA_COLOCATION && colocatedDPMatrixObj != null) {
            job.setInputFormat(RemoteParForColocatedNLineInputFormat.class);
            MRJobConfiguration.setPartitioningFormat(job, colocatedDPMatrixObj.getPartitionFormat());
            MatrixCharacteristics mc = colocatedDPMatrixObj.getMatrixCharacteristics();
            MRJobConfiguration.setPartitioningBlockNumRows(job, mc.getRowsPerBlock());
            MRJobConfiguration.setPartitioningBlockNumCols(job, mc.getColsPerBlock());
            MRJobConfiguration.setPartitioningFilename(job, colocatedDPMatrixObj.getFileName());
        } else // default case
        {
            job.setInputFormat(NLineInputFormat.class);
        }
        // set the input path and output path
        FileInputFormat.setInputPaths(job, new Path(taskFile));
        // set output format
        job.setOutputFormat(SequenceFileOutputFormat.class);
        // set output path
        MapReduceTool.deleteFileIfExistOnHDFS(resultFile);
        FileOutputFormat.setOutputPath(job, new Path(resultFile));
        // set the output key, value schema
        job.setMapOutputKeyClass(LongWritable.class);
        job.setMapOutputValueClass(Text.class);
        job.setOutputKeyClass(LongWritable.class);
        job.setOutputValueClass(Text.class);
        // ////
        // set optimization parameters
        // set the number of mappers and reducers
        // numMappers
        job.setNumMapTasks(numMappers);
        job.setNumReduceTasks(0);
        // job.setInt("mapred.map.tasks.maximum", 1); //system property
        // job.setInt("mapred.tasktracker.tasks.maximum",1); //system property
        // job.setInt("mapred.jobtracker.maxtasks.per.job",1); //system property
        // set jvm memory size (if require)
        String memKey = MRConfigurationNames.MR_CHILD_JAVA_OPTS;
        if (minMem > 0 && minMem > InfrastructureAnalyzer.extractMaxMemoryOpt(job.get(memKey))) {
            InfrastructureAnalyzer.setMaxMemoryOpt(job, memKey, minMem);
            LOG.warn("Forcing '" + memKey + "' to -Xmx" + minMem / (1024 * 1024) + "M.");
        }
        // disable automatic tasks timeouts and speculative task exec
        job.setInt(MRConfigurationNames.MR_TASK_TIMEOUT, 0);
        job.setMapSpeculativeExecution(false);
        // set up map/reduce memory configurations (if in AM context)
        DMLConfig config = ConfigurationManager.getDMLConfig();
        DMLAppMasterUtils.setupMRJobRemoteMaxMemory(job, config);
        // set up custom map/reduce configurations
        MRJobConfiguration.setupCustomMRConfigurations(job, config);
        // enables the reuse of JVMs (multiple tasks per MR task)
        if (jvmReuse)
            // unlimited
            job.setNumTasksToExecutePerJvm(-1);
        // set sort io buffer (reduce unnecessary large io buffer, guaranteed memory consumption)
        // 8MB
        job.setInt(MRConfigurationNames.MR_TASK_IO_SORT_MB, 8);
        // set the replication factor for the results
        job.setInt(MRConfigurationNames.DFS_REPLICATION, replication);
        // set the max number of retries per map task
        // disabled job-level configuration to respect cluster configuration
        // note: this refers to hadoop2, hence it never had effect on mr1
        // job.setInt(MRConfigurationNames.MR_MAP_MAXATTEMPTS, max_retry);
        // set unique working dir
        MRJobConfiguration.setUniqueWorkingDir(job);
        // ///
        // execute the MR job
        RunningJob runjob = JobClient.runJob(job);
        // Process different counters
        Statistics.incrementNoOfExecutedMRJobs();
        Group pgroup = runjob.getCounters().getGroup(ParForProgramBlock.PARFOR_COUNTER_GROUP_NAME);
        int numTasks = (int) pgroup.getCounter(Stat.PARFOR_NUMTASKS.toString());
        int numIters = (int) pgroup.getCounter(Stat.PARFOR_NUMITERS.toString());
        if (DMLScript.STATISTICS && !InfrastructureAnalyzer.isLocalMode()) {
            Statistics.incrementJITCompileTime(pgroup.getCounter(Stat.PARFOR_JITCOMPILE.toString()));
            Statistics.incrementJVMgcCount(pgroup.getCounter(Stat.PARFOR_JVMGC_COUNT.toString()));
            Statistics.incrementJVMgcTime(pgroup.getCounter(Stat.PARFOR_JVMGC_TIME.toString()));
            Group cgroup = runjob.getCounters().getGroup(CacheableData.CACHING_COUNTER_GROUP_NAME.toString());
            CacheStatistics.incrementMemHits((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_HITS_MEM.toString()));
            CacheStatistics.incrementFSBuffHits((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_HITS_FSBUFF.toString()));
            CacheStatistics.incrementFSHits((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_HITS_FS.toString()));
            CacheStatistics.incrementHDFSHits((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_HITS_HDFS.toString()));
            CacheStatistics.incrementFSBuffWrites((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_WRITES_FSBUFF.toString()));
            CacheStatistics.incrementFSWrites((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_WRITES_FS.toString()));
            CacheStatistics.incrementHDFSWrites((int) cgroup.getCounter(CacheStatistics.Stat.CACHE_WRITES_HDFS.toString()));
            CacheStatistics.incrementAcquireRTime(cgroup.getCounter(CacheStatistics.Stat.CACHE_TIME_ACQR.toString()));
            CacheStatistics.incrementAcquireMTime(cgroup.getCounter(CacheStatistics.Stat.CACHE_TIME_ACQM.toString()));
            CacheStatistics.incrementReleaseTime(cgroup.getCounter(CacheStatistics.Stat.CACHE_TIME_RLS.toString()));
            CacheStatistics.incrementExportTime(cgroup.getCounter(CacheStatistics.Stat.CACHE_TIME_EXP.toString()));
        }
        // read all files of result variables and prepare for return
        LocalVariableMap[] results = readResultFile(job, resultFile);
        ret = new RemoteParForJobReturn(runjob.isSuccessful(), numTasks, numIters, results);
    } catch (Exception ex) {
        throw new DMLRuntimeException(ex);
    } finally {
        // remove created files
        try {
            MapReduceTool.deleteFileIfExistOnHDFS(new Path(taskFile), job);
            MapReduceTool.deleteFileIfExistOnHDFS(new Path(resultFile), job);
        } catch (IOException ex) {
            throw new DMLRuntimeException(ex);
        }
    }
    if (DMLScript.STATISTICS) {
        long t1 = System.nanoTime();
        Statistics.maintainCPHeavyHitters("MR-Job_" + jobname, t1 - t0);
    }
    return ret;
}

Example 62 with MatrixCharacteristics

use of org.apache.sysml.runtime.matrix.MatrixCharacteristics in project incubator-systemml by apache.

the class ResultMergeLocalAutomatic method executeSerialMerge.

@Override
public MatrixObject executeSerialMerge() {
    Timing time = new Timing(true);
    MatrixCharacteristics mc = _output.getMatrixCharacteristics();
    long rows = mc.getRows();
    long cols = mc.getCols();
    if (OptimizerRuleBased.isInMemoryResultMerge(rows, cols, OptimizerUtils.getLocalMemBudget()))
        _rm = new ResultMergeLocalMemory(_output, _inputs, _outputFName, _isAccum);
    else
        _rm = new ResultMergeLocalFile(_output, _inputs, _outputFName, _isAccum);
    MatrixObject ret = _rm.executeSerialMerge();
    LOG.trace("Automatic result merge (" + _rm.getClass().getName() + ") executed in " + time.stop() + "ms.");
    return ret;
}

Example 63 with MatrixCharacteristics

use of org.apache.sysml.runtime.matrix.MatrixCharacteristics in project incubator-systemml by apache.

the class ResultMergeLocalFile method createBinaryCellStagingFile.

@SuppressWarnings("deprecation")
private static void createBinaryCellStagingFile(String fnameStaging, MatrixObject mo, long ID) throws IOException, DMLRuntimeException {
    JobConf job = new JobConf(ConfigurationManager.getCachedJobConf());
    Path path = new Path(mo.getFileName());
    FileSystem fs = IOUtilFunctions.getFileSystem(path, job);
    LinkedList<Cell> buffer = new LinkedList<>();
    MatrixIndexes key = new MatrixIndexes();
    MatrixCell value = new MatrixCell();
    MatrixCharacteristics mc = mo.getMatrixCharacteristics();
    int brlen = mc.getRowsPerBlock();
    int bclen = mc.getColsPerBlock();
    for (Path lpath : IOUtilFunctions.getSequenceFilePaths(fs, path)) {
        SequenceFile.Reader reader = new SequenceFile.Reader(fs, lpath, job);
        try {
            while (reader.next(key, value)) {
                Cell tmp = new Cell(key.getRowIndex(), key.getColumnIndex(), value.getValue());
                buffer.addLast(tmp);
                if (// periodic flush
                buffer.size() > StagingFileUtils.CELL_BUFFER_SIZE) {
                    appendCellBufferToStagingArea(fnameStaging, ID, buffer, brlen, bclen);
                    buffer.clear();
                }
            }
            // final flush
            if (!buffer.isEmpty()) {
                appendCellBufferToStagingArea(fnameStaging, ID, buffer, brlen, bclen);
                buffer.clear();
            }
        } finally {
            IOUtilFunctions.closeSilently(reader);
        }
    }
}

Example 64 with MatrixCharacteristics

use of org.apache.sysml.runtime.matrix.MatrixCharacteristics in project incubator-systemml by apache.

the class ResultMergeLocalFile method createTextCellResultFile.

private void createTextCellResultFile(String fnameStaging, String fnameStagingCompare, String fnameNew, MetaDataFormat metadata, boolean withCompare) throws IOException, DMLRuntimeException {
    JobConf job = new JobConf(ConfigurationManager.getCachedJobConf());
    Path path = new Path(fnameNew);
    FileSystem fs = IOUtilFunctions.getFileSystem(path, job);
    MatrixCharacteristics mc = metadata.getMatrixCharacteristics();
    long rlen = mc.getRows();
    long clen = mc.getCols();
    int brlen = mc.getRowsPerBlock();
    int bclen = mc.getColsPerBlock();
    try (BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fs.create(path, true)))) {
        // for obj reuse and preventing repeated buffer re-allocations
        StringBuilder sb = new StringBuilder();
        boolean written = false;
        for (long brow = 1; brow <= (long) Math.ceil(rlen / (double) brlen); brow++) for (long bcol = 1; bcol <= (long) Math.ceil(clen / (double) bclen); bcol++) {
            File dir = new File(fnameStaging + "/" + brow + "_" + bcol);
            File dir2 = new File(fnameStagingCompare + "/" + brow + "_" + bcol);
            MatrixBlock mb = null;
            long row_offset = (brow - 1) * brlen + 1;
            long col_offset = (bcol - 1) * bclen + 1;
            if (dir.exists()) {
                if (// WITH COMPARE BLOCK
                withCompare && dir2.exists()) {
                    // copy only values that are different from the original
                    String[] lnames2 = dir2.list();
                    if (// there should be exactly 1 compare block
                    lnames2.length != 1)
                        throw new DMLRuntimeException("Unable to merge results because multiple compare blocks found.");
                    mb = StagingFileUtils.readCellList2BlockFromLocal(dir2 + "/" + lnames2[0], brlen, bclen);
                    boolean appendOnly = mb.isInSparseFormat();
                    DenseBlock compare = DataConverter.convertToDenseBlock(mb, false);
                    for (String lname : dir.list()) {
                        MatrixBlock tmp = StagingFileUtils.readCellList2BlockFromLocal(dir + "/" + lname, brlen, bclen);
                        mergeWithComp(mb, tmp, compare);
                    }
                    // sort sparse and exam sparsity due to append-only
                    if (appendOnly && !_isAccum)
                        mb.sortSparseRows();
                    // change sparsity if required after
                    mb.examSparsity();
                } else // WITHOUT COMPARE BLOCK
                {
                    // copy all non-zeros from all workers
                    boolean appendOnly = false;
                    for (String lname : dir.list()) {
                        if (mb == null) {
                            mb = StagingFileUtils.readCellList2BlockFromLocal(dir + "/" + lname, brlen, bclen);
                            appendOnly = mb.isInSparseFormat();
                        } else {
                            MatrixBlock tmp = StagingFileUtils.readCellList2BlockFromLocal(dir + "/" + lname, brlen, bclen);
                            mergeWithoutComp(mb, tmp, appendOnly);
                        }
                    }
                    // sort sparse due to append-only
                    if (appendOnly && !_isAccum)
                        mb.sortSparseRows();
                    // change sparsity if required after
                    mb.examSparsity();
                }
            }
            // write the block to text cell
            if (mb != null) {
                if (mb.isInSparseFormat()) {
                    Iterator<IJV> iter = mb.getSparseBlockIterator();
                    while (iter.hasNext()) {
                        IJV lcell = iter.next();
                        sb.append(row_offset + lcell.getI());
                        sb.append(' ');
                        sb.append(col_offset + lcell.getJ());
                        sb.append(' ');
                        sb.append(lcell.getV());
                        sb.append('\n');
                        out.write(sb.toString());
                        sb.setLength(0);
                        written = true;
                    }
                } else {
                    for (int i = 0; i < brlen; i++) for (int j = 0; j < bclen; j++) {
                        double lvalue = mb.getValueDenseUnsafe(i, j);
                        if (// for nnz
                        lvalue != 0) {
                            sb.append(row_offset + i);
                            sb.append(' ');
                            sb.append(col_offset + j);
                            sb.append(' ');
                            sb.append(lvalue);
                            sb.append('\n');
                            out.write(sb.toString());
                            sb.setLength(0);
                            written = true;
                        }
                    }
                }
            }
        }
        if (!written)
            out.write(IOUtilFunctions.EMPTY_TEXT_LINE);
    }
}

Example 65 with MatrixCharacteristics

use of org.apache.sysml.runtime.matrix.MatrixCharacteristics in project incubator-systemml by apache.

the class ResultMergeLocalFile method createTextCellStagingFile.

private static void createTextCellStagingFile(String fnameStaging, MatrixObject mo, long ID) throws IOException, DMLRuntimeException {
    JobConf job = new JobConf(ConfigurationManager.getCachedJobConf());
    Path path = new Path(mo.getFileName());
    FileInputFormat.addInputPath(job, path);
    TextInputFormat informat = new TextInputFormat();
    informat.configure(job);
    InputSplit[] splits = informat.getSplits(job, 1);
    LinkedList<Cell> buffer = new LinkedList<>();
    LongWritable key = new LongWritable();
    Text value = new Text();
    MatrixCharacteristics mc = mo.getMatrixCharacteristics();
    int brlen = mc.getRowsPerBlock();
    int bclen = mc.getColsPerBlock();
    // long row = -1, col = -1; //FIXME needs reconsideration whenever textcell is used actively
    // NOTE MB: Originally, we used long row, col but this led reproducibly to JIT compilation
    // errors during runtime; experienced under WINDOWS, Intel x86-64, IBM JDK 64bit/32bit.
    // It works fine with int row, col but we require long for larger matrices.
    // Since, textcell is never used for result merge (hybrid/hadoop: binaryblock, singlenode:binarycell)
    // we just propose the to exclude it with -Xjit:exclude={package.method*}(count=0,optLevel=0)
    FastStringTokenizer st = new FastStringTokenizer(' ');
    for (InputSplit split : splits) {
        RecordReader<LongWritable, Text> reader = informat.getRecordReader(split, job, Reporter.NULL);
        try {
            while (reader.next(key, value)) {
                // reset tokenizer
                st.reset(value.toString());
                long row = st.nextLong();
                long col = st.nextLong();
                double lvalue = Double.parseDouble(st.nextToken());
                Cell tmp = new Cell(row, col, lvalue);
                buffer.addLast(tmp);
                if (// periodic flush
                buffer.size() > StagingFileUtils.CELL_BUFFER_SIZE) {
                    appendCellBufferToStagingArea(fnameStaging, ID, buffer, brlen, bclen);
                    buffer.clear();
                }
            }
            // final flush
            if (!buffer.isEmpty()) {
                appendCellBufferToStagingArea(fnameStaging, ID, buffer, brlen, bclen);
                buffer.clear();
            }
        } finally {
            IOUtilFunctions.closeSilently(reader);
        }
    }
}