Yes, your broadcast should be about 300M, much smaller than 2G, I didn't read your post carefully.
The broadcast in Python had been improved much since 1.1, I think it will work in 1.1 or upcoming 1.2 release, could you upgrade to 1.1? Davies On Tue, Nov 11, 2014 at 8:37 PM, bliuab <bli...@cse.ust.hk> wrote: > Dear Liu: > > Thank you very much for your help. I will update that patch. By the way, as > I have succeed to broadcast an array of size(30M) the log said that such > array takes around 230MB memory. As a result, I think the numpy array that > leads to error is much smaller than 2G. > > On Wed, Nov 12, 2014 at 12:29 PM, Davies Liu-2 [via Apache Spark User List] > <[hidden email]> wrote: >> >> This PR fix the problem: https://github.com/apache/spark/pull/2659 >> >> cc @josh >> >> Davies >> >> On Tue, Nov 11, 2014 at 7:47 PM, bliuab <[hidden email]> wrote: >> >> > 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) >> > >> > >> > >> > >> > >> > >> > -- >> > View this message in context: >> > http://apache-spark-user-list.1001560.n3.nabble.com/Pyspark-Error-when-broadcast-numpy-array-tp18662.html >> > Sent from the Apache Spark User List mailing list archive at Nabble.com. >> > >> > --------------------------------------------------------------------- >> > To unsubscribe, e-mail: [hidden email] >> > For additional commands, e-mail: [hidden email] >> > >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: [hidden email] >> For additional commands, e-mail: [hidden email] >> >> >> >> ________________________________ >> If you reply to this email, your message will be added to the discussion >> below: >> >> http://apache-spark-user-list.1001560.n3.nabble.com/Pyspark-Error-when-broadcast-numpy-array-tp18662p18673.html >> To unsubscribe from Pyspark Error when broadcast numpy array, click here. >> NAML > > > > > -- > My Homepage: www.cse.ust.hk/~bliuab > MPhil student in Hong Kong University of Science and Technology. > Clear Water Bay, Kowloon, Hong Kong. > Profile at LinkedIn. > > ________________________________ > View this message in context: Re: Pyspark Error when broadcast numpy array > > Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
