add yarn script

tracker/rabit_yarn.py

@@ -0,0 +1,100 @@
+#!/usr/bin/python
+"""
+This is a script to submit rabit job using hadoop streaming
+submit the rabit process as mappers of MapReduce
+"""
+import argparse
+import sys
+import os
+import time
+import subprocess
+import rabit_tracker as tracker
+
+#!!! Set path to hadoop and hadoop streaming jar here
+hadoop_binary = 'hadoop'
+hadoop_streaming_jar = None
+
+# code 
+hadoop_home = os.getenv('HADOOP_HOME')
+if hadoop_home != None:
+    if hadoop_binary == None:
+        hadoop_binary = hadoop_home + '/bin/hadoop'
+        assert os.path.exists(hadoop_binary), "HADDOP_HOME does not contain the hadoop binary"
+    if hadoop_streaming_jar == None:
+	hadoop_streaming_jar = hadoop_home + '/lib/hadoop-streaming.jar'
+        assert os.path.exists(hadoop_streaming_jar), "HADDOP_HOME does not contain the haddop streaming jar"
+
+if hadoop_binary == None or hadoop_streaming_jar == None:
+    print 'Warning: Cannot auto-detect path to hadoop and streaming jar, need to set them via arguments -hs and -hb'
+    print '\tTo enable auto-detection, you can set enviroment variable HADOOP_HOME or modify rabit_hadoop.py line 14'
+
+parser = argparse.ArgumentParser(description='Rabit script to submit rabit jobs using Hadoop Streaming')
+parser.add_argument('-nw', '--nworker', required=True, type=int,
+                    help = 'number of worker proccess to be launched')
+parser.add_argument('-nt', '--nthread', required=True, type=int,
+		                    help = 'number of thread of each mapper to be launched')
+parser.add_argument('-i', '--input', required=True,
+                    help = 'input path in HDFS')
+parser.add_argument('-o', '--output', required=True,
+                    help = 'output path in HDFS')
+parser.add_argument('-v', '--verbose', default=0, choices=[0, 1], type=int,
+                    help = 'print more messages into the console')
+parser.add_argument('-ac', '--auto_file_cache', default=1, choices=[0, 1], type=int,
+                    help = 'whether automatically cache the files in the command to hadoop localfile, this is on by default')
+parser.add_argument('-f', '--files', nargs = '*',
+                    help = 'the cached file list in mapreduce,'\
+                        ' the submission script will automatically cache all the files which appears in command.'\
+                        ' You may need this option to cache additional files.'\
+                        ' You can also use it to manually cache files when auto_file_cache is off')
+parser.add_argument('--jobname', default='auto', help = 'customize jobname in tracker')
+parser.add_argument('--timeout', default=600000000, type=int,
+		    help = 'timeout (in million seconds) of each mapper job, automatically set to a very long time,'\
+		       'normally you do not need to set this ')
+parser.add_argument('-m', '--memory_mb', default=1024, type=int,
+		    help = 'maximum memory used by the process, Guide: set it large (near mapreduce.jobtracker.maxmapmemory.mb).'\
+		    'if you are running multi-threading rabit,'\
+		    'so that each node can occupy all the mapper slots in a machine for maximum performance')
+
+
+if hadoop_binary == None:
+    parser.add_argument('-hb', '--hadoop_binary', required = True,
+                        help="path-to-hadoop binary folder")  
+else:
+    parser.add_argument('-hb', '--hadoop_binary', default = hadoop_binary, 
+                        help="path-to-hadoop binary folder")  
+
+if hadoop_streaming_jar == None:
+    parser.add_argument('-jar', '--hadoop_streaming_jar', required = True,
+                        help='path-to hadoop streamimg jar file')
+else:
+    parser.add_argument('-jar', '--hadoop_streaming_jar', default = hadoop_streaming_jar,
+                        help='path-to hadoop streamimg jar file')
+parser.add_argument('command', nargs='+',
+                    help = 'command for rabit program')
+args = parser.parse_args()
+
+if args.jobname == 'auto':
+	args.jobname = ('Rabit[nworker=%d]:' % args.nworker) + args.command[0].split('/')[-1];
+
+def hadoop_streaming(nworker, slave_args):
+    cmd = '%s jar %s -D mapreduce.job.maps=%d' % (args.hadoop_binary, args.hadoop_streaming_jar, nworker)
+    cmd += ' -D mapreduce.job.name=%s' % (args.jobname)
+    cmd += ' -D mapreduce.map.cpu.vcores=%d' % (args.nthread)
+    cmd += ' -D mapreduce.task.timeout=%d' % (args.timeout)
+    cmd += ' -D mapreduce.map.memory.mb=%d' % (args.memory_mb)
+    cmd += ' -input %s -output %s' % (args.input, args.output)
+    cmd += ' -mapper \"%s\" -reducer \"/bin/cat\" ' % (' '.join(args.command + slave_args))
+    fset = set()
+    if args.auto_file_cache:
+        for f in args.command:
+            if os.path.exists(f):
+                fset.add(f)
+    for flst in args.files:
+        for f in flst.split('#'):
+            fset.add(f)
+    for f in fset:
+        cmd += ' -file %s' % f
+    print cmd
+    subprocess.check_call(cmd, shell = True)
+
+tracker.submit(args.nworker, [], fun_submit = hadoop_streaming, verbose = args.verbose)