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Brenda99
Brenda99
Bronze ⭐️⭐️⭐️
September 26, 2025
Question

Need Cloudera CDP Consultant - Spark Job Performance Tuning

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.

3 replies

DianaTorres
Community Manager
DianaTorres
Community Manager
September 26, 2025

@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.

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Regards, Diana Torres, Senior Community Moderator
Colin4
Colin4
Silver ⭐️
September 29, 2025

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

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vafs
Gold ⭐️⭐️⭐️
vafs
Gold ⭐️⭐️⭐️
October 6, 2025

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.html 
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. 

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Regards, Andrés Fallas -- Was your question answered? Please take some time to click on "Accept as Solution" below this post. If you find a reply useful, say thanks by clicking on the thumbs-up button.
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