List of usage examples for org.apache.hadoop.mapred JobConf setMapSpeculativeExecution
public void setMapSpeculativeExecution(boolean speculativeExecution)
From source file:com.scaleunlimited.helpful.tools.AnalyzeEmail.java
License:Apache License
private static JobConf getDefaultJobConf() throws IOException { JobClient jobClient = new JobClient(new JobConf()); ClusterStatus status = jobClient.getClusterStatus(); int trackers = status.getTaskTrackers(); JobConf conf = new JobConf(); conf.setNumMapTasks(trackers * 10);//from ww w . java 2 s.co m conf.setNumReduceTasks((trackers * conf.getInt("mapred.tasktracker.reduce.tasks.maximum", 2))); conf.setMapSpeculativeExecution(false); conf.setReduceSpeculativeExecution(false); conf.set("mapred.child.java.opts", "-server -Xmx512m -Xss128k"); // Should match the value used for Xss above. Note no 'k' suffix for the ulimit command. // New support that one day will be in Hadoop. conf.set("mapred.child.ulimit.stack", "128"); return conf; }
From source file:com.twitter.maple.jdbc.db.DBOutputFormat.java
License:Apache License
/** * Initializes the reduce-part of the job with the appropriate output settings * * @param job The job//from w w w . j a v a 2 s . c o m * @param dbOutputFormatClass * @param tableName The table to insert data into * @param fieldNames The field names in the table. If unknown, supply the appropriate */ public static void setOutput(JobConf job, Class<? extends DBOutputFormat> dbOutputFormatClass, String tableName, String[] fieldNames, String[] updateFields, int batchSize) { if (dbOutputFormatClass == null) { job.setOutputFormat(DBOutputFormat.class); } else { job.setOutputFormat(dbOutputFormatClass); } // writing doesn't always happen in reduce job.setReduceSpeculativeExecution(false); job.setMapSpeculativeExecution(false); DBConfiguration dbConf = new DBConfiguration(job); dbConf.setOutputTableName(tableName); dbConf.setOutputFieldNames(fieldNames); if (updateFields != null) { dbConf.setOutputUpdateFieldNames(updateFields); } if (batchSize != -1) { dbConf.setBatchStatementsNum(batchSize); } }
From source file:eu.larkc.iris.Main.java
License:Apache License
private JobConf setupJob(Configuration conf) { JobConf jobConf = new JobConf(conf, Main.class); // run the job here. /* REAL CLUSTER */ jobConf.set("dfs.blocksize", "536870912"); jobConf.set("dfs.namenode.handler.count", "40"); //jobConf.set("dfs.replication", "1"); jobConf.set("mapreduce.reduce.shuffle.parallelcopies", "10"); jobConf.set("mapreduce.task.io.sort.factor", "100"); jobConf.set("mapreduce.task.io.sort.mb", "1024"); jobConf.set("io.file.buffer.size", "131072"); jobConf.set("mapred.child.java.opts", "-Xmx2560m"); jobConf.set("mapred.child.ulimit", "4194304"); jobConf.set("mapred.min.split.size", "536870912"); jobConf.set("mapreduce.input.fileinputformat.split.minsize", "536870912"); jobConf.set("mapreduce.reduce.merge.inmem.threshold", "0"); /**///w w w . j a va 2s . c o m /* compression settings jobConf.set("mapreduce.map.output.compress", "false"); jobConf.set("mapreduce.output.fileoutputformat.compress", "true"); jobConf.set("mapreduce.output.fileoutputformat.compression.type", "BLOCK"); ~~~ */ //!!!IMPORTANT, if not : Caused by: java.io.FileNotFoundException: File does not exist: hdfs://ec2-50-19-191-200.compute-1.amazonaws.com:8020/user/root/lubm/facts/lubm50/data jobConf.setBoolean("mapred.input.dir.recursive", true); jobConf.set("cascading.serialization.tokens", "130=eu.larkc.iris.storage.IRIWritable,131=eu.larkc.iris.storage.StringTermWritable"); defaultConfiguration.flowProperties.put("cascading.serialization.tokens", "130=eu.larkc.iris.storage.IRIWritable,131=eu.larkc.iris.storage.StringTermWritable"); /* if( System.getProperty("log4j.logger") != null ) defaultConfiguration.flowProperties.put( "log4j.logger", System.getProperty("log4j.logger") ); */ //jobConf.set("mapred.min.split.size", "134217728"); //jobConf.set("mapred.child.java.opts", "-Xms64m -Xmx512m"); jobConf.setMapSpeculativeExecution(false); jobConf.setReduceSpeculativeExecution(false); //FIXME //jobConf.setNumMapTasks(8); jobConf.setNumReduceTasks(32); FlowConnector.setDebugLevel(defaultConfiguration.flowProperties, DebugLevel.VERBOSE); MultiMapReducePlanner.setJobConf(defaultConfiguration.flowProperties, jobConf); //Flow.setJobPollingInterval(defaultConfiguration.flowProperties, 500); return jobConf; }
From source file:fr.ens.biologie.genomique.eoulsan.modules.mgmt.hadoop.DistCp.java
License:LGPL
private static JobConf createJobConf(final Configuration conf) { JobConf jobconf = new JobConf(conf, DistCp.class); jobconf.setJobName(NAME);/*from w ww .ja v a2 s . com*/ // turn off speculative execution, because DFS doesn't handle // multiple writers to the same file. jobconf.setMapSpeculativeExecution(false); jobconf.setInputFormat(CopyInputFormat.class); jobconf.setOutputKeyClass(Text.class); jobconf.setOutputValueClass(Text.class); jobconf.setMapperClass(CopyFilesMapper.class); jobconf.setNumReduceTasks(0); return jobconf; }
From source file:io.hops.erasure_coding.MapReduceEncoder.java
License:Apache License
/** * create new job conf based on configuration passed. * * @param conf/*from ww w . j a v a 2 s .c o m*/ * @return */ private static JobConf createJobConf(Configuration conf) { JobConf jobconf = new JobConf(conf, MapReduceEncoder.class); jobName = NAME + " " + dateForm.format(new Date(BaseEncodingManager.now())); jobconf.setUser(BaseEncodingManager.JOBUSER); jobconf.setJobName(jobName); jobconf.setMapSpeculativeExecution(false); RaidUtils.parseAndSetOptions(jobconf, SCHEDULER_OPTION_LABEL); jobconf.setJarByClass(MapReduceEncoder.class); jobconf.setInputFormat(DistRaidInputFormat.class); jobconf.setOutputKeyClass(Text.class); jobconf.setOutputValueClass(Text.class); jobconf.setMapperClass(DistRaidMapper.class); jobconf.setNumReduceTasks(0); return jobconf; }
From source file:org.apache.sysml.runtime.controlprogram.parfor.DataPartitionerRemoteMR.java
License:Apache License
@Override protected void partitionMatrix(MatrixObject in, String fnameNew, InputInfo ii, OutputInfo oi, long rlen, long clen, int brlen, int bclen) throws DMLRuntimeException { String jobname = "ParFor-DPMR"; long t0 = DMLScript.STATISTICS ? System.nanoTime() : 0; JobConf job; job = new JobConf(DataPartitionerRemoteMR.class); if (_pfid >= 0) //use in parfor job.setJobName(jobname + _pfid); else //use for partition instruction job.setJobName("Partition-MR"); //maintain dml script counters Statistics.incrementNoOfCompiledMRJobs(); try {// w w w . j a v a 2s. com //force writing to disk (typically not required since partitioning only applied if dataset exceeds CP size) in.exportData(); //written to disk iff dirty Path path = new Path(in.getFileName()); ///// //configure the MR job MRJobConfiguration.setPartitioningInfo(job, rlen, clen, brlen, bclen, ii, oi, _format, _n, fnameNew, _keepIndexes); //set mappers, reducers, combiners job.setMapperClass(DataPartitionerRemoteMapper.class); job.setReducerClass(DataPartitionerRemoteReducer.class); if (oi == OutputInfo.TextCellOutputInfo) { //binary cell intermediates for reduced IO job.setMapOutputKeyClass(LongWritable.class); job.setMapOutputValueClass(PairWritableCell.class); } else if (oi == OutputInfo.BinaryCellOutputInfo) { job.setMapOutputKeyClass(LongWritable.class); job.setMapOutputValueClass(PairWritableCell.class); } else if (oi == OutputInfo.BinaryBlockOutputInfo) { job.setMapOutputKeyClass(LongWritable.class); job.setMapOutputValueClass(PairWritableBlock.class); //check Alignment if ((_format == PDataPartitionFormat.ROW_BLOCK_WISE_N && rlen > _n && _n % brlen != 0) || (_format == PDataPartitionFormat.COLUMN_BLOCK_WISE_N && clen > _n && _n % bclen != 0)) { throw new DMLRuntimeException( "Data partitioning format " + _format + " requires aligned blocks."); } } //set input format job.setInputFormat(ii.inputFormatClass); //set the input path and output path FileInputFormat.setInputPaths(job, path); //set output path MapReduceTool.deleteFileIfExistOnHDFS(fnameNew); //FileOutputFormat.setOutputPath(job, pathNew); job.setOutputFormat(NullOutputFormat.class); ////// //set optimization parameters //set the number of mappers and reducers //job.setNumMapTasks( _numMappers ); //use default num mappers long reducerGroups = -1; switch (_format) { case ROW_WISE: reducerGroups = rlen; break; case COLUMN_WISE: reducerGroups = clen; break; case ROW_BLOCK_WISE: reducerGroups = (rlen / brlen) + ((rlen % brlen == 0) ? 0 : 1); break; case COLUMN_BLOCK_WISE: reducerGroups = (clen / bclen) + ((clen % bclen == 0) ? 0 : 1); break; case ROW_BLOCK_WISE_N: reducerGroups = (rlen / _n) + ((rlen % _n == 0) ? 0 : 1); break; case COLUMN_BLOCK_WISE_N: reducerGroups = (clen / _n) + ((clen % _n == 0) ? 0 : 1); break; default: //do nothing } job.setNumReduceTasks((int) Math.min(_numReducers, reducerGroups)); //disable automatic tasks timeouts and speculative task exec job.setInt(MRConfigurationNames.MR_TASK_TIMEOUT, 0); job.setMapSpeculativeExecution(false); //set up preferred custom serialization framework for binary block format if (MRJobConfiguration.USE_BINARYBLOCK_SERIALIZATION) MRJobConfiguration.addBinaryBlockSerializationFramework(job); //enables the reuse of JVMs (multiple tasks per MR task) if (_jvmReuse) job.setNumTasksToExecutePerJvm(-1); //unlimited //enables compression - not conclusive for different codecs (empirically good compression ratio, but significantly slower) //job.set(MRConfigurationNames.MR_MAP_OUTPUT_COMPRESS, "true"); //job.set(MRConfigurationNames.MR_MAP_OUTPUT_COMPRESS_CODEC, "org.apache.hadoop.io.compress.GzipCodec"); //set the replication factor for the results job.setInt(MRConfigurationNames.DFS_REPLICATION, _replication); //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); //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 JobClient.runJob(job); //maintain dml script counters Statistics.incrementNoOfExecutedMRJobs(); } catch (Exception ex) { throw new DMLRuntimeException(ex); } if (DMLScript.STATISTICS && _pfid >= 0) { long t1 = System.nanoTime(); //only for parfor Statistics.maintainCPHeavyHitters("MR-Job_" + jobname, t1 - t0); } }
From source file:org.apache.sysml.runtime.controlprogram.parfor.RemoteDPParForMR.java
License:Apache License
public static RemoteParForJobReturn runJob(long pfid, String itervar, String matrixvar, String program, String resultFile, MatrixObject input, PartitionFormat dpf, OutputInfo oi, boolean tSparseCol, //config params boolean enableCPCaching, int numReducers, int replication) //opt params throws DMLRuntimeException { RemoteParForJobReturn ret = null;//from ww w .ja v a2 s . c o m String jobname = "ParFor-DPEMR"; long t0 = DMLScript.STATISTICS ? System.nanoTime() : 0; JobConf job; job = new JobConf(RemoteDPParForMR.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 reducers MRJobConfiguration.setProgramBlocks(job, program); //enable/disable caching MRJobConfiguration.setParforCachingConfig(job, enableCPCaching); //setup input matrix Path path = new Path(input.getFileName()); long rlen = input.getNumRows(); long clen = input.getNumColumns(); int brlen = (int) input.getNumRowsPerBlock(); int bclen = (int) input.getNumColumnsPerBlock(); MRJobConfiguration.setPartitioningInfo(job, rlen, clen, brlen, bclen, InputInfo.BinaryBlockInputInfo, oi, dpf._dpf, dpf._N, input.getFileName(), itervar, matrixvar, tSparseCol); job.setInputFormat(InputInfo.BinaryBlockInputInfo.inputFormatClass); FileInputFormat.setInputPaths(job, path); //set mapper and reducers classes job.setMapperClass(DataPartitionerRemoteMapper.class); job.setReducerClass(RemoteDPParWorkerReducer.class); //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 //parfor partitioning outputs (intermediates) job.setMapOutputKeyClass(LongWritable.class); if (oi == OutputInfo.BinaryBlockOutputInfo) job.setMapOutputValueClass(PairWritableBlock.class); else if (oi == OutputInfo.BinaryCellOutputInfo) job.setMapOutputValueClass(PairWritableCell.class); else throw new DMLRuntimeException("Unsupported intermrediate output info: " + oi); //parfor exec output job.setOutputKeyClass(LongWritable.class); job.setOutputValueClass(Text.class); ////// //set optimization parameters //set the number of mappers and reducers job.setNumReduceTasks(numReducers); //disable automatic tasks timeouts and speculative task exec job.setInt(MRConfigurationNames.MR_TASK_TIMEOUT, 0); job.setMapSpeculativeExecution(false); //set up preferred custom serialization framework for binary block format if (MRJobConfiguration.USE_BINARYBLOCK_SERIALIZATION) MRJobConfiguration.addBinaryBlockSerializationFramework(job); //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); //disable JVM reuse job.setNumTasksToExecutePerJvm(1); //-1 for unlimited //set the replication factor for the results job.setInt(MRConfigurationNames.DFS_REPLICATION, replication); //set the max number of retries per map task //note: currently disabled to use cluster config //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(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; }
From source file:org.apache.sysml.runtime.controlprogram.parfor.RemoteParForMR.java
License:Apache License
public static RemoteParForJobReturn runJob(long pfid, String program, String taskFile, String resultFile, MatrixObject colocatedDPMatrixObj, //inputs boolean enableCPCaching, int numMappers, int replication, int max_retry, long minMem, boolean jvmReuse) //opt params throws DMLRuntimeException { RemoteParForJobReturn ret = null;/*from ww w . j a va 2 s . com*/ 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 job.setMapperClass(RemoteParWorkerMapper.class); //map-only //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 job.setNumMapTasks(numMappers); //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) job.setNumTasksToExecutePerJvm(-1); //unlimited //set sort io buffer (reduce unnecessary large io buffer, guaranteed memory consumption) job.setInt(MRConfigurationNames.MR_TASK_IO_SORT_MB, 8); //8MB //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; }
From source file:org.apache.sysml.runtime.controlprogram.parfor.ResultMergeRemoteMR.java
License:Apache License
@SuppressWarnings({ "unused", "deprecation" })
protected void executeMerge(String fname, String fnameNew, String[] srcFnames, InputInfo ii, OutputInfo oi,
long rlen, long clen, int brlen, int bclen) throws DMLRuntimeException {
String jobname = "ParFor-RMMR";
long t0 = DMLScript.STATISTICS ? System.nanoTime() : 0;
JobConf job = new JobConf(ResultMergeRemoteMR.class);
job.setJobName(jobname + _pfid);/* w ww. j a v a 2 s . c o m*/
//maintain dml script counters
Statistics.incrementNoOfCompiledMRJobs();
//warning for textcell/binarycell without compare
boolean withCompare = (fname != null);
if ((oi == OutputInfo.TextCellOutputInfo || oi == OutputInfo.BinaryCellOutputInfo) && !withCompare
&& ResultMergeLocalFile.ALLOW_COPY_CELLFILES)
LOG.warn("Result merge for " + OutputInfo.outputInfoToString(oi)
+ " without compare can be realized more efficiently with LOCAL_FILE than REMOTE_MR.");
try {
Path pathCompare = null;
Path pathNew = new Path(fnameNew);
/////
//configure the MR job
if (withCompare) {
FileSystem fs = IOUtilFunctions.getFileSystem(pathNew, job);
pathCompare = new Path(fname).makeQualified(fs);
MRJobConfiguration.setResultMergeInfo(job, pathCompare.toString(), ii,
LocalFileUtils.getWorkingDir(LocalFileUtils.CATEGORY_RESULTMERGE), rlen, clen, brlen,
bclen);
} else
MRJobConfiguration.setResultMergeInfo(job, "null", ii,
LocalFileUtils.getWorkingDir(LocalFileUtils.CATEGORY_RESULTMERGE), rlen, clen, bclen,
bclen);
//set mappers, reducers, combiners
job.setMapperClass(ResultMergeRemoteMapper.class);
job.setReducerClass(ResultMergeRemoteReducer.class);
if (oi == OutputInfo.TextCellOutputInfo) {
job.setMapOutputKeyClass(MatrixIndexes.class);
job.setMapOutputValueClass(TaggedMatrixCell.class);
job.setOutputKeyClass(NullWritable.class);
job.setOutputValueClass(Text.class);
} else if (oi == OutputInfo.BinaryCellOutputInfo) {
job.setMapOutputKeyClass(MatrixIndexes.class);
job.setMapOutputValueClass(TaggedMatrixCell.class);
job.setOutputKeyClass(MatrixIndexes.class);
job.setOutputValueClass(MatrixCell.class);
} else if (oi == OutputInfo.BinaryBlockOutputInfo) {
//setup partitioning, grouping, sorting for composite key (old API)
job.setPartitionerClass(ResultMergeRemotePartitioning.class); //partitioning
job.setOutputValueGroupingComparator(ResultMergeRemoteGrouping.class); //grouping
job.setOutputKeyComparatorClass(ResultMergeRemoteSorting.class); //sorting
job.setMapOutputKeyClass(ResultMergeTaggedMatrixIndexes.class);
job.setMapOutputValueClass(TaggedMatrixBlock.class);
job.setOutputKeyClass(MatrixIndexes.class);
job.setOutputValueClass(MatrixBlock.class);
}
//set input format
job.setInputFormat(ii.inputFormatClass);
//set the input path
Path[] paths = null;
if (withCompare) {
paths = new Path[srcFnames.length + 1];
paths[0] = pathCompare;
for (int i = 1; i < paths.length; i++)
paths[i] = new Path(srcFnames[i - 1]);
} else {
paths = new Path[srcFnames.length];
for (int i = 0; i < paths.length; i++)
paths[i] = new Path(srcFnames[i]);
}
FileInputFormat.setInputPaths(job, paths);
//set output format
job.setOutputFormat(oi.outputFormatClass);
//set output path
MapReduceTool.deleteFileIfExistOnHDFS(fnameNew);
FileOutputFormat.setOutputPath(job, pathNew);
//////
//set optimization parameters
//set the number of mappers and reducers
//job.setNumMapTasks( _numMappers ); //use default num mappers
long reducerGroups = _numReducers;
if (oi == OutputInfo.BinaryBlockOutputInfo)
reducerGroups = Math.max(rlen / brlen, 1) * Math.max(clen / bclen, 1);
else //textcell/binarycell
reducerGroups = Math.max((rlen * clen) / StagingFileUtils.CELL_BUFFER_SIZE, 1);
job.setNumReduceTasks((int) Math.min(_numReducers, reducerGroups));
//disable automatic tasks timeouts and speculative task exec
job.setInt(MRConfigurationNames.MR_TASK_TIMEOUT, 0);
job.setMapSpeculativeExecution(false);
//set up preferred custom serialization framework for binary block format
if (MRJobConfiguration.USE_BINARYBLOCK_SERIALIZATION)
MRJobConfiguration.addBinaryBlockSerializationFramework(job);
//set up custom map/reduce configurations
DMLConfig config = ConfigurationManager.getDMLConfig();
MRJobConfiguration.setupCustomMRConfigurations(job, config);
//enables the reuse of JVMs (multiple tasks per MR task)
if (_jvmReuse)
job.setNumTasksToExecutePerJvm(-1); //unlimited
//enables compression - not conclusive for different codecs (empirically good compression ratio, but significantly slower)
//job.set(MRConfigurationNames.MR_MAP_OUTPUT_COMPRESS, "true");
//job.set(MRConfigurationNames.MR_MAP_OUTPUT_COMPRESS_CODEC, "org.apache.hadoop.io.compress.GzipCodec");
//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
JobClient.runJob(job);
//maintain dml script counters
Statistics.incrementNoOfExecutedMRJobs();
} catch (Exception ex) {
throw new DMLRuntimeException(ex);
}
if (DMLScript.STATISTICS) {
long t1 = System.nanoTime();
Statistics.maintainCPHeavyHitters("MR-Job_" + jobname, t1 - t0);
}
}
From source file:org.apache.sysml.runtime.matrix.CleanupMR.java
License:Apache License
public static boolean runJob(DMLConfig conf) throws Exception { boolean ret = false; try {//w ww.jav a2 s .c o m JobConf job; job = new JobConf(CleanupMR.class); job.setJobName("Cleanup-MR"); //set up SystemML local tmp dir String dir = conf.getTextValue(DMLConfig.LOCAL_TMP_DIR); MRJobConfiguration.setSystemMLLocalTmpDir(job, dir); //set mappers, reducers int numNodes = InfrastructureAnalyzer.getRemoteParallelNodes(); job.setMapperClass(CleanupMapper.class); //map-only job.setNumMapTasks(numNodes); //numMappers job.setNumReduceTasks(0); //set input/output format, input path String inFileName = conf.getTextValue(DMLConfig.SCRATCH_SPACE) + "/cleanup_tasks"; job.setInputFormat(NLineInputFormat.class); job.setOutputFormat(NullOutputFormat.class); Path path = new Path(inFileName); FileInputFormat.setInputPaths(job, path); writeCleanupTasksToFile(path, numNodes); //disable automatic tasks timeouts and speculative task exec job.setInt(MRConfigurationNames.MR_TASK_TIMEOUT, 0); job.setMapSpeculativeExecution(false); ///// // execute the MR job RunningJob runjob = JobClient.runJob(job); ret = runjob.isSuccessful(); } catch (Exception ex) { //don't raise an exception, just gracefully an error message. LOG.error("Failed to run cleanup MR job. ", ex); } return ret; }