Reputation: 168
I am using Spark Standalone cluster mode and use "spark.driver.cores"
to set number of cores for the driver. But every time the UI shows it "0" as shown in the picture
Even setting up this value in the code
.set("spark.driver.cores","14")
does not seem to work. How should this value be set in the standalone cluster mode ?
Thanks ===UPDATE=== Here is the spark-submit command
spark-submit --jars "file:///<path to jar>" --master spark://$MASTER:7077 --conf "spark.cores.max=330"
--conf "spark.executor.core=5"
--conf "spark.sql.broadcastTimeout=10000000"
--conf "spark.sql.shuffle.partitions=1000"
--conf "spark.default.parallelism=1000"
--conf "spark.executor.memory=40g"
--conf "spark.driver.memory=40g"
--conf "spark.driver.extraJavaOptions=-XX:+UseCompressedOops -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps"
--conf "spark.driver.maxResultSize=40g"
--conf "spark.network.timeout=10000000"
--class "<my class>" "<path to jar>" <other parameters>....
Each of the node in the cluster has 24 core and 64GB memory. I hope this helps. Thanks for your help.
Upvotes: 2
Views: 12371
Reputation: 29155
`--conf "spark.executor.core=5"` is wrong
should be (s is missing)
--conf "spark.executor.cores=5"
second thing is if you are not setting spark.driver.cores
is spark-submit.
your .set("spark.driver.cores","14")
should be like
val sparkConf = new SparkConf()
.set("spark.driver.cores", "2")
.setAppName(this.getClass.getSimpleName)
.setMaster("local[*]")
val spark: SparkSession = SparkSession.builder().config(sparkConf).appName(this.getClass.getName)
.master("local[*]").getOrCreate()
Tip : To Verify what cofigurations you are applying :
spark.sparkContext.getConf.getAll.foreach(println)
will print all the configurations applied to create the spark session.
In the above example :
(spark.app.name,com.examples.DataFrameCSVExample$)
(spark.app.id,local-1558579973832)
(spark.driver.cores,2)
(spark.master,local[*])
(spark.executor.id,driver)
(spark.driver.host,192.168.19.1)
(spark.driver.port,53962)
If you are able to see here, spark-ui should show the same...
Hope you understood!!!
Upvotes: 4