In spark-1.0.2, I have come across an error when I try to broadcast a quite
large numpy array(with 35M dimension). The error information except the
java.lang.NegativeArraySizeException error and details is listed below.
Moreover, when broadcast a relatively smaller numpy array(30M dimension),
everything works fine. And 30M dimension numpy array takes 230M memory
which, in my opinion, not very large.
As far as I have surveyed, it seems related with py4j. However, I have no
idea how to fix this. I would be appreciated if I can get some hint.
------------
py4j.protocol.Py4JError: An error occurred while calling o23.broadcast.
Trace:
java.lang.NegativeArraySizeException
at py4j.Base64.decode(Base64.java:292)
at py4j.Protocol.getBytes(Protocol.java:167)
at py4j.Protocol.getObject(Protocol.java:276)
at
py4j.commands.AbstractCommand.getArguments(AbstractCommand.java:81)
at py4j.commands.CallCommand.execute(CallCommand.java:77)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
-------------
And the test code is a follows:
conf =
SparkConf().setAppName('brodyliu_LR').setMaster('spark://10.231.131.87:5051')
conf.set('spark.executor.memory', '4000m')
conf.set('spark.akka.timeout', '100000')
conf.set('spark.ui.port','8081')
conf.set('spark.cores.max','150')
#conf.set('spark.rdd.compress', 'True')
conf.set('spark.default.parallelism', '300')
#configure the spark environment
sc = SparkContext(conf=conf, batchSize=1)
vec = np.random.rand(35000000)
a = sc.broadcast(vec)
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