Re: RDD Partitions not distributed evenly to executors

I have a similar experience. Using 32 machines, I can see than number of tasks (partitions) assigned to executors (machines) is not even. Moreover, the distribution change every stage (iteration). I wonder why Spark needs to move partitions around any way, should not the scheduler reduce network

GraphX replication factor

Hi, I wonder if it is possible to figure out the replication factor used in GraphX partitioning from its log files. -- Thanks, -Khaled

Re: Graphx

This is an interesting discussion, I have had some success running GraphX on large graphs with more than a Billion edges using clusters of different size up to 64 machines. However, the performance goes down when I double the cluster size to reach 128 machines of r3.xlarge. Does any one have

GraphX stopped without finishing and with no ERRORs !

Hi all, I have a problem running some algorithms on GraphX. Occasionally, it stopped running without any errors. The task state is FINISHED, but the executers state is KILLED. However, I can see that one job is not finished yet. It took too much time (minutes) while every job/iteration were

"Master: got disassociated, removing it."

Hi, I am using GRAPHX in standalone SPARK 1.5.1 in a medium size cluster (64+1). I could execute PageRank with large number of iterations on this cluster. However, when I run SSSP, it always fail at iteration 23 or 24. This is always at after about 11 mins. Note that PageRank takes more than

Re: Why some executors are lazy?

rs. > > -adrian > > From: Khaled Ammar > Date: Tuesday, November 3, 2015 at 11:43 PM > To: "user@spark.apache.org" > Subject: Why some executors are lazy? > > Hi, > > I'm using the most recent Spark version on a standalone setup of 16+1 > machines. &g

Why some executors are lazy?

Hi, I'm using the most recent Spark version on a standalone setup of 16+1 machines. While running GraphX workloads, I found that some executors are lazy? They *rarely* participate in computation. This causes some other executors to do their work. This behavior is consistent in all iterations and

What does "write time" means exactly in Spark UI?

Hi, I wonder what does write time means exactly? I run GraphX workloads and noticed the main bottleneck in most stages is one or two tasks takes too long in "write time" and delay the whole job. Enabling speculation helps a little but I am still interested to know how to fix that? I use

Performance issues in SSSP using GraphX

Hi all, I have an interesting behavior from GraphX while running SSSP. I use the stand-alone mode with 16+1 machines, each has 30GB memory and 4 cores. The dataset is 63GB. However, the input for some stages is huge, about 16 TB ! The computation takes very long time. I stopped it. For your

NaN in GraphX PageRank answer

Hi all, I was trying to use GraphX to compute pagerank and found that pagerank value for several vertices is NaN. I am using Spark 1.3. Any idea how to fix that? -- Thanks, -Khaled

Fwd: Performance questions regarding Spark 1.3 standalone mode

Hi all, I wonder if any one has an explanation for this behavior. Thank you, -Khaled -- Forwarded message -- From: Khaled Ammar khaled.am...@gmail.com Date: Fri, Jul 24, 2015 at 9:35 AM Subject: Performance questions regarding Spark 1.3 standalone mode To: user@spark.apache.org

Performance questions regarding Spark 1.3 standalone mode

Hi all, I have a standalone spark cluster setup on EC2 machines. I did the setup manually without the ec2 scripts. I have two questions about Spark/GraphX performance: 1) When I run the PageRank example, the storage tab does not show that all RDDs are cached. Only one RDD is 100% cached, but the

Re: GraphX Synth Benchmark

Hi, I am not a spark expert but I found that passing a small partitions value might help. Try to use this option --numEPart=$partitions where partitions=3 (number of workers) or at most 3*40 (total number of cores). Thanks, -Khaled On Thu, Jul 9, 2015 at 11:37 AM, AshutoshRaghuvanshi

Question about master memory requirement and GraphX pagerank performance !

. There is one that was taking 4+ hours, and its input is 400+ GB. I must be doing something wrong, any comment? -- Thanks, -Khaled Ammar www.khaledammar.com

Basic GraphX deployment and usage question

Hi, I'm very new to Spark and GraphX. I downloaded and configured Spark on a cluster, which uses Hadoop 1.x. The master UI shows all workers. The example command run-example SparkPi works fine and completes successfully. I'm interested in GraphX. Although the documentation says it is built-in