Exception in thread "main" org.apache.spark.sql.AnalysisException: Cannot modify the value of a Spark config: spark.executor.memory;

[sarvesh]

I am trying to read a 16mb excel file and I was getting a gc overhead limit exceeded error to resolve that i tried to increase my executor memory with,

spark.conf.set("spark.executor.memory", "8g")

but i got the following stack :

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties

Exception in thread "main" org.apache.spark.sql.AnalysisException: Cannot modify the value of a Spark config: spark.executor.memory;

at org.apache.spark.sql.RuntimeConfig.requireNonStaticConf(RuntimeConfig.scala:158)

at org.apache.spark.sql.RuntimeConfig.set(RuntimeConfig.scala:42)

at com.sundogsoftware.spark.spaceTrim.trimmer$.delayedEndpoint$com$sundogsoftware$spark$spaceTrim$trimmer$1(trimmer.scala:29)

at com.sundogsoftware.spark.spaceTrim.trimmer$delayedInit$body.apply(trimmer.scala:9)

at scala.Function0.apply$mcV$sp(Function0.scala:39)

at scala.Function0.apply$mcV$sp$(Function0.scala:39)

at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:17)

at scala.App.$anonfun$main$1$adapted(App.scala:80)

at scala.collection.immutable.List.foreach(List.scala:431)

at scala.App.main(App.scala:80)

at scala.App.main$(App.scala:78)

at com.sundogsoftware.spark.spaceTrim.trimmer$.main(trimmer.scala:9)

at com.sundogsoftware.spark.spaceTrim.trimmer.main(trimmer.scala)

my code :-

val spark = SparkSession

.builder

.appName("schemaTest")

.master("local[*]")

.getOrCreate()

spark.conf.set("spark.executor.memory", "8g")

val df = spark.read

.format("com.crealytics.spark.excel").

option("header", "true").

option("inferSchema", "false").

option("treatEmptyValuesAsNulls", "false").

option("addColorColumns", "False").

load("data/12file.xlsx")

[Prabakar]

Hi @sarvesh singh​ Please try setting the value in the cluster spark config tab. It should help.

[Prabakar · Accepted solution]

On the cluster configuration page, go to the advanced options. Click it to expand the field. There you will find the Spark tab and you can set the values there in the "Spark config".

[sarvesh]

Thank you for replying but, for this project i am using intellij and working locally, is there some way with spark session or context to do the same?