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From Lukas Bradley <lukasbrad...@gmail.com>
Subject Re: graphframe out of memory
Date Thu, 07 Sep 2017 16:26:33 GMT
Did you also increase the size of the heap of the Java app that is starting
Spark?

https://alvinalexander.com/blog/post/java/java-xmx-xms-memory-heap-size-control

On Thu, Sep 7, 2017 at 12:16 PM, Imran Rajjad <rajjad@gmail.com> wrote:

> I am getting Out of Memory error while running connectedComponents job on
> graph with around 12000 vertices and 134600 edges.
> I am running spark in embedded mode in a standalone Java application and
> have tried to increase the memory but it seems that its not taking any
> effect
>
> sparkConf = new SparkConf().setAppName("SOME APP
> NAME").setMaster("local[10]")
>     .set("spark.executor.memory","5g")
>     .set("spark.driver.memory","8g")
>     .set("spark.driver.maxResultSize","1g")
>     .set("spark.sql.warehouse.dir", "file:///d:/spark/tmp")
>     .set("hadoop.home.dir", "file:///D:/spark-2.1.0-bin-hadoop2.7/bin");
>
>   spark = SparkSession.builder().config(sparkConf).getOrCreate();
>   spark.sparkContext().setLogLevel("ERROR");
>   spark.sparkContext().setCheckpointDir("D:/spark/tmp");
>
> the stack trace
> java.lang.OutOfMemoryError: Java heap space
>  at java.util.Arrays.copyOf(Arrays.java:3332)
>  at java.lang.AbstractStringBuilder.ensureCapacityInternal(
> AbstractStringBuilder.java:124)
>  at java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:448)
>  at java.lang.StringBuilder.append(StringBuilder.java:136)
>  at scala.StringContext.standardInterpolator(StringContext.scala:126)
>  at scala.StringContext.s(StringContext.scala:95)
>  at org.apache.spark.sql.execution.QueryExecution.
> toString(QueryExecution.scala:230)
>  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(
> SQLExecution.scala:54)
>  at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2788)
>  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$
> execute$1(Dataset.scala:2385)
>  at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$
> Dataset$$collect$1.apply(Dataset.scala:2390)
>  at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$
> Dataset$$collect$1.apply(Dataset.scala:2390)
>  at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2801)
>  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$
> collect(Dataset.scala:2390)
>  at org.apache.spark.sql.Dataset.collect(Dataset.scala:2366)
>  at org.graphframes.lib.ConnectedComponents$.skewedJoin(
> ConnectedComponents.scala:239)
>  at org.graphframes.lib.ConnectedComponents$.org$graphframes$lib$
> ConnectedComponents$$run(ConnectedComponents.scala:308)
>  at org.graphframes.lib.ConnectedComponents.run(
> ConnectedComponents.scala:139)
>
> GraphFrame version is 0.5.0 and Spark version is 2.1.1
>
> regards,
> Imran
>
> --
> I.R
>

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