A colleague did the experiments and I don’t know exactly how he observed that. I think it was indirect from the Spark diagnostics indicating the amount of I/O he deduced that this was RDD serialization. Also when he added light compression to RDD serialization this improved matters.
John Lilley Chief Architect, RedPoint Global Inc. T: +1 303 541 1516 | M: +1 720 938 5761 | F: +1 781-705-2077 Skype: jlilley.redpoint | john.lil...@redpoint.net<mailto:john.lil...@redpoint.net> | www.redpoint.net<http://www.redpoint.net/> From: lihu [mailto:lihu...@gmail.com] Sent: Friday, March 11, 2016 7:58 AM To: John Lilley <john.lil...@redpoint.net> Cc: Andrew A <andrew.a...@gmail.com>; u...@spark.incubator.apache.org Subject: Re: Graphx Hi, John: I am very intersting in your experiment, How can you get that RDD serialization cost lots of time, from the log or some other tools? On Fri, Mar 11, 2016 at 8:46 PM, John Lilley <john.lil...@redpoint.net<mailto:john.lil...@redpoint.net>> wrote: Andrew, We conducted some tests for using Graphx to solve the connected-components problem and were disappointed. On 8 nodes of 16GB each, we could not get above 100M edges. On 8 nodes of 60GB each, we could not process 1bn edges. RDD serialization would take excessive time and then we would get failures. By contrast, we have a C++ algorithm that solves 1bn edges using memory+disk on a single 16GB node in about an hour. I think that a very large cluster will do better, but we did not explore that. John Lilley Chief Architect, RedPoint Global Inc. T: +1 303 541 1516<tel:%2B1%C2%A0303%C2%A0541%201516> | M: +1 720 938 5761<tel:%2B1%20720%20938%205761> | F: +1 781-705-2077<tel:%2B1%20781-705-2077> Skype: jlilley.redpoint | john.lil...@redpoint.net<mailto:john.lil...@redpoint.net> | www.redpoint.net<http://www.redpoint.net/> From: Andrew A [mailto:andrew.a...@gmail.com<mailto:andrew.a...@gmail.com>] Sent: Thursday, March 10, 2016 2:44 PM To: u...@spark.incubator.apache.org<mailto:u...@spark.incubator.apache.org> Subject: Graphx Hi, is there anyone who use graphx in production? What maximum size of graphs did you process by spark and what cluster are you use for it? i tried calculate pagerank for 1 Gb edges LJ - dataset for LiveJournalPageRank from spark examples and i faced with large volume shuffles produced by spark which fail my spark job. Thank you, Andrew
