Re: GraphX performance feedback

Ok thanks! Le jeu. 28 nov. 2019 à 11:27, Phillip Henry a écrit : > I saw a large improvement in my GraphX processing by: > > - using fewer partitions > - using fewer executors but with much more memory. > > YMMV. > > Phillip > > On Mon, 25 Nov 2019, 19:14 mahzad kalantari, > wrote: > >> Thanks

Re: GraphX performance feedback

I saw a large improvement in my GraphX processing by: - using fewer partitions - using fewer executors but with much more memory. YMMV. Phillip On Mon, 25 Nov 2019, 19:14 mahzad kalantari, wrote: > Thanks for your answer, my use case is friend recommandation for 200 > million profils. > > Le

Re: GraphX performance feedback

Thanks for your answer, my use case is friend recommandation for 200 million profils. Le lun. 25 nov. 2019 à 14:10, Jörn Franke a écrit : > I think it depends what you want do. Interactive big data graph analytics > are probably better of in Janusgraph or similar. > Batch processing (once-off)

Re: GraphX performance feedback

I think it depends what you want do. Interactive big data graph analytics are probably better of in Janusgraph or similar. Batch processing (once-off) can be still fine in graphx - you have though to carefully design the process. > Am 25.11.2019 um 20:04 schrieb mahzad kalantari : > >  > Hi

GraphX performance feedback

Hi all My question is about GraphX, I 'm looking for user feedbacks on the performance. I read this paper written by Facebook team that says Graphx has very poor performance. https://engineering.fb.com/core-data/a-comparison-of-state-of-the-art-graph-processing-systems/ Has anyone already

Re: GraphX performance and settings

Hi, We are also running Connected Components test with GraphX. We ran experiments using Spark 1.6.1 on machine which have 16 cores with 2-way and run only a single executor per machine. We got this result: Facebook-like graph with 2^24 edges, using 4 executors with 90GB each, it took 100

Re: GraphX performance and settings

Hi, We are also running Connected Components test with GraphX. We ran experiments using Spark 1.6.1 on machine which have 16 cores with 2-way and run only a single executor per machine. We got this result: Facebook-like graph with 2^24 edges, using 4 executors with 90GB each, it took 100

Re: GraphX performance and settings

which we'd kill them. Maja From: Deepak Goel <deic...@gmail.com<mailto:deic...@gmail.com>> Date: Wednesday, June 15, 2016 at 7:13 PM To: Maja Kabiljo <majakabi...@fb.com<mailto:majakabi...@fb.com>> Cc: "user @spark" <user@spark.apache.org<mailto:use

Re: GraphX performance and settings

I am not an expert but some thoughts inline On Jun 16, 2016 6:31 AM, "Maja Kabiljo" wrote: > > Hi, > > We are running some experiments with GraphX in order to compare it with other systems. There are multiple settings which significantly affect performance, and we

GraphX performance and settings

Hi, We are running some experiments with GraphX in order to compare it with other systems. There are multiple settings which significantly affect performance, and we experimented a lot in order to tune them well. I'll share here what are the best we found so far and which results we got with

GraphX Performance

Hi, I am writting to know if there is any performance data on GraphX? I run 4 workes in AWS (c3.xlarge), 4g memory for executor, 85,331,846 edges from( http://socialcomputing.asu.edu/pages/dataset http://socialcomputing.asu.edu/pages/datasetss). For PageRank algorithm, the job can not be