public void cleanupMatrixObject(MatrixObject mo) throws DMLRuntimeException {
try {
if (mo.isCleanupEnabled()) {
// compute ref count only if matrix cleanup actually necessary
if (!getVariables().hasReferences(mo)) {
// clean cached data
mo.clearData();
if (mo.isHDFSFileExists()) {
// clean hdfs data
String fpath = mo.getFileName();
if (fpath != null) {
MapReduceTool.deleteFileIfExistOnHDFS(fpath);
MapReduceTool.deleteFileIfExistOnHDFS(fpath + ".mtd");
}
}
}
}
} catch (Exception ex) {
throw new DMLRuntimeException(ex);
}
}
/**
* @param pfid
* @param program
* @param taskFile
* @param resultFile
* @param _enableCPCaching
* @param mode
* @param numMappers
* @param replication
* @return
* @throws DMLRuntimeException
*/
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;
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
// use FLEX scheduler configuration properties
if (ParForProgramBlock.USE_FLEX_SCHEDULER_CONF) {
job.setInt("flex.priority", 0); // highest
job.setInt("flex.map.min", 0);
job.setInt("flex.map.max", numMappers);
job.setInt("flex.reduce.min", 0);
job.setInt("flex.reduce.max", numMappers);
}
// set jvm memory size (if require)
String memKey = "mapred.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("mapred.task.timeout", 0);
job.setMapSpeculativeExecution(false);
// set up map/reduce memory configurations (if in AM context)
DMLConfig config = ConfigurationManager.getConfig();
DMLAppMasterUtils.setupMRJobRemoteMaxMemory(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("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("mapreduce.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;
}
