Hi , we are not moving to 3.1.1 because some open ticket are there I have mentioned below. https://issues.apache.org/jira/browse/SPARK-30536
https://issues.apache.org/jira/browse/SPARK-35066 please refer attached mail for spark 35066. Thanks. ________________________________ From: Mich Talebzadeh <mich.talebza...@gmail.com> Sent: Monday, August 30, 2021 1:15:07 PM To: Sharma, Prakash (Nokia - IN/Bangalore) <prakash.sha...@nokia.com> Cc: user@spark.apache.org <user@spark.apache.org> Subject: Re: Performance Degradation in Spark 3.0.2 compared to Spark 3.0.1 Hi, Any particular reason why you are not using 3.1.1 on Kubernetes? [https://docs.google.com/uc?export=download&id=1-q7RFGRfLMObPuQPWSd9sl_H1UPNFaIZ&revid=0B1BiUVX33unjMWtVUWpINWFCd0ZQTlhTRHpGckh4Wlg4RG80PQ] view my Linkedin profile<https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> Disclaimer: Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from relying on this email's technical content is explicitly disclaimed. The author will in no case be liable for any monetary damages arising from such loss, damage or destruction. On Mon, 30 Aug 2021 at 06:10, Sharma, Prakash (Nokia - IN/Bangalore) <prakash.sha...@nokia.com<mailto:prakash.sha...@nokia.com>> wrote: Sessional Greetings , We're doing tpc-ds query tests using Spark 3.0.2 on kubernetes with data on HDFS and we're observing delays in query execution time when compared to Spark 3.0.1 on same environment. We've observed that some stages fail, but looks like it is taking some time to realise this failure and re-trigger these stages. I am attaching the configuration also which we used for the spark driver . We observe the same behaviour with sapark 3.0.3 also. Please let us know if anyone has observed similar issues. Configuration which we use for spark driver: spark.io.compression.codec=snappy spark.sql.parquet.filterPushdown=true spark.sql.inMemoryColumnarStorage.batchSize=15000 spark.shuffle.file.buffer=1024k spark.ui.retainedStages=10000 spark.kerberos.keytab=<keytab loacation> spark.speculation=false spark.submit.deployMode=cluster spark.kubernetes.driver.label.sparkoperator.k8s.io/launched-by-spark-operator=true<http://spark.kubernetes.driver.label.sparkoperator.k8s.io/launched-by-spark-operator=true> spark.sql.orc.filterPushdown=true spark.serializer=org.apache.spark.serializer.KryoSerializer spark.sql.crossJoin.enabled=true spark.kubernetes.kerberos.keytab=<key-tab location> spark.sql.adaptive.enabled=true spark.kryo.unsafe=true spark.kubernetes.driver.label.sparkoperator.k8s.io/submission-id=<http://spark.kubernetes.driver.label.sparkoperator.k8s.io/submission-id=><operator label> spark.executor.cores=2 spark.ui.retainedTasks=200000 spark.network.timeout=2400 spark.rdd.compress=true spark.executor.memoryoverhead=3G spark.master=k8s\:<master ip> spark.kubernetes.driver.label.sparkoperator.k8s.io/app-name=<http://spark.kubernetes.driver.label.sparkoperator.k8s.io/app-name=><label app name> spark.kubernetes.driver.limit.cores=6144m spark.kubernetes.submission.waitAppCompletion=false spark.kerberos.principal=<principal> spark.kubernetes.kerberos.enabled=true spark.kubernetes.allocation.batch.size=5 spark.kubernetes.authenticate.driver.serviceAccountName=<serviceAccount name> spark.kubernetes.executor.label.sparkoperator.k8s.io/launched-by-spark-operator=true<http://spark.kubernetes.executor.label.sparkoperator.k8s.io/launched-by-spark-operator=true> spark.reducer.maxSizeInFlight=1024m spark.storage.memoryFraction=0.25 spark.kubernetes.namespace=<namespace name> spark.kubernetes.executor.label.sparkoperator.k8s.io/app-name=<http://spark.kubernetes.executor.label.sparkoperator.k8s.io/app-name=><executor label> spark.rpc.numRetries=5 spark.shuffle.consolidateFiles=true spark.sql.shuffle.partitions=400 spark.kubernetes.kerberos.krb5.path=/<file path> spark.sql.codegen=true spark.ui.strictTransportSecurity=max-age\=31557600 spark.ui.retainedJobs=10000 spark.driver.port=7078 spark.shuffle.io.backLog=256 spark.ssl.ui.enabled=true spark.kubernetes.memoryOverheadFactor=0.1 spark.driver.blockManager.port=7079 spark.kubernetes.executor.limit.cores=4096m spark.submit.pyFiles= spark.kubernetes.container.image=<image name> spark.shuffle.io.numConnectionsPerPeer=10 spark.sql.broadcastTimeout=7200 spark.driver.cores=3 spark.executor.memory=9g spark.kubernetes.executor.label.sparkoperator.k8s.io/submission-id=dfbd9c75-3771-4392-928e-10bf28d94099<http://spark.kubernetes.executor.label.sparkoperator.k8s.io/submission-id=dfbd9c75-3771-4392-928e-10bf28d94099> spark.driver.maxResultSize=4g spark.sql.parquet.mergeSchema=false spark.sql.inMemoryColumnarStorage.compressed=true spark.rpc.retry.wait=5 spark.hadoop.parquet.enable.summary-metadata=false spark.kubernetes.allocation.batch.delay=9 spark.driver.memory=16g spark.sql.starJoinOptimization=true spark.kubernetes.submitInDriver=true spark.shuffle.compress=true spark.memory.useLegacyMode=true spark.jars= spark.kubernetes.resource.type=java spark.locality.wait=0s spark.kubernetes.driver.ui.svc.port=4040 spark.sql.orc.splits.include.file.footer=true spark.kubernetes.kerberos.principal=<principle> spark.sql.orc.cache.stripe.details.size=10000 spark.executor.instances=22 spark.hadoop.fs.hdfs.impl.disable.cache=true spark.sql.hive.metastorePartitionPruning=true Thanks and Regards Prakash
FW_ Why is Spark 3.0.x faster than Spark 3.1.x (1).eml
Description: FW_ Why is Spark 3.0.x faster than Spark 3.1.x (1).eml
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