Need Cloudera CDP Consultant - Spark Job Performance Tuning

[#1]

Looking for help with Cloudera Data Platform Spark job optimization. We're running large-scale ETL jobs that are timing out during the shuffle phase, consuming excessive cluster resources and causing memory spillage.

The jobs process ~500GB datasets but execution times have increased 3x after migrating to CDP. Need someone experienced with Spark tuning on Cloudera and YARN resource management to identify bottlenecks.

Seeking 3-4 hours remote performance analysis to optimize job configuration and cluster settings. Must be resolved by Tuesday for our data pipeline SLA.

[#2]

@Brenda99 Welcome to the Cloudera Community!

To help you get the best possible solution, I have tagged our CDP experts @venkatsambath @abdulpasithali @upadhyayk04 who may be able to assist you further.

Please keep us updated on your post, and we hope you find a satisfactory solution to your query.

[#3]

Hi Brenda,

I have extensive experience optimizing Spark jobs on CDP and dealing with shuffle-heavy workloads.

Your timeout issues during shuffle phase sound like a combination of executor memory settings and partition strategy problems, pretty common after CDP migrations actually.

I can help diagnose the bottlenecks through Spark UI analysis and YARN logs, then tune your spark.sql.shuffle.partitions and executor configurations.

Have successfully reduced similar ETL job runtimes by 60-70% for other clients facing post-migration performance degradation.

You can reach out to me on my email here

Colin

[#4]

Hello @Brenda99, 

The question is very wide, there are many things that can help to improve the performance. 

Some basic recomendations are documented here: 
https://docs.cloudera.com/cdp-private-cloud-base/7.3.1/tuning-spark/topics/spark-admin_spark_tuning.... 
Take a look on the documentation, that could help you. 

Also, it will worth to talk with the team in charge of your account to found deeper performance tuning analysis.