diff pyspark/test_timeside_vamp_spark_charm.py @ 0:e34cf1b6fe09 tip

commit

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pyspark/test_timeside_vamp_spark_charm.py	Sat Feb 20 18:14:24 2016 +0100
@@ -0,0 +1,101 @@
+# Part of DML (Digital Music Laboratory)
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public License
+# as published by the Free Software Foundation; either version 2
+# of the License, or (at your option) any later version.
+# 
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+# 
+# You should have received a copy of the GNU General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+#!/usr/local/spark-1.0.0-bin-hadoop2/bin/spark-submit
+# -*- coding: utf-8 -*-
+__author__="wolffd"
+__date__ ="$11-Jul-2014 15:31:01$"
+
+# How to run this?
+
+# to start hdfs:  /usr/local/hadoop/sbin/start-dfs.sh
+
+# Running python applications through ./bin/pyspark is deprecated as of Spark 1.0.
+# Use ./bin/spark-submit
+# spark-submit test_timeside_vamp_spark_charm.py --py-files vamp_plugin_dml.py,timeside_vamp.py,decode_to_wav.py
+
+#import pydoop.hdfs as hdfs
+from pyspark import SparkConf, SparkContext
+# @todo: timeside has to be packed for multi-pc usage
+import os.path
+import os
+import sys
+from os import walk
+# NOTE: this is only for debugging purposes, we can 
+# now use a regular timeside installation, e.g. installed by 
+sys.path.append(os.getcwd() + '/../TimeSide/')
+
+# mappers
+from timeside_vamp import *
+from decode_to_wav import *
+
+def main():
+    print "PySpark Telemeta and Vamp Test on CHARM"
+    
+    # configure the Spark Setup
+    conf = (SparkConf()
+            .setMaster("spark://0.0.0.0:7077") 
+            #.setMaster("local")
+            .setAppName("CharmVamp")
+            .set("spark.executor.memory", "1g"))
+    sc = SparkContext(conf = conf)
+
+    # SMB Share
+    # mount.cifs //10.2.165.194/mirg /home/wolffd/wansteadshare -o username=dml,password=xxx,domain=ENTERPRISE")
+
+
+    # uses local paths
+    # get list of obkects to process
+    mypath = '/samples/'
+    data = []
+    for (dirpath, dirnames, filenames) in walk(mypath):
+        for file in filenames:
+            if  file.endswith(".wav") or file.endswith(".flac"): 
+                data.append(os.path.join(dirpath, file))
+
+    data = data[0:2]
+    # HDFS
+    # note: for HDFS we need wrappers for VAMP and gstreamer :/
+    # copy to hdfs (put in different file before)
+    #hdfs.mkdir("test")
+    #hdfs.chmod("test","o+rw")
+    ##this copies the test wavs to hdfs
+    #hdfs.put("samples/","test/")
+    # get hdfs paths
+#    data = []
+#    filenames = hdfs.ls("hdfs://0.0.0.0:9000/user/hduser/test/samples")
+#    print filenames 
+#    for file in filenames:
+#        if file[-4:]== ".wav" or file[-4:]==".flac":
+#            data.append(file)
+#    
+    # define distributed dataset
+    # todo: can we do this with the wav data itself?
+    distData = sc.parallelize(data)
+  
+    # define map that decodes to wav
+    m0 = distData.map(lambda x: decode_to_wav(source=x))
+    
+    # define map that applies the vamp plugin
+    m1 = m0.map(lambda x: transform(wav_file=x)).collect()
+    print m1
+    return m1
+    #process 2
+    #m1.take(2)
+
+if __name__ == "__main__":
+    main()
+