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Spark Config Optimizer
Describe your cluster and job and get tuned Apache Spark settings — executor cores and memory, executor count, driver memory, shuffle partitions and overhead — with the reasoning behind them.
Recommended configuration
Your recommended Spark configuration and reasoning will appear here.
Practise it · Spark
Right-size spark.sql.shuffle.partitions
Config is the easy half — read a real job’s stage metrics and pick the partition count it actually needed. Hard · about 15 min · runs in your browser, no signup.
How to Optimize Spark Configuration
Enter Cluster Specs
Tell us your node count, cores per node and memory per node.
Describe the Job
Explain the workload — data sizes, joins, shuffle intensity and output.
Apply the Settings
Get concrete spark-submit / SparkConf values plus the reasoning, then apply and benchmark.
Frequently Asked Questions
Is the Spark config optimizer free?
Yes, it's free and needs no signup. A fair-use rate limit keeps it available for everyone.
What settings does it tune?
Executor cores and memory, number of executors, driver memory, memory overhead, shuffle partitions, and relevant tuning flags — with justification.
Is it a replacement for benchmarking?
No. It gives strong, well-reasoned starting values. Always benchmark on your real data and adjust, since optimal settings depend on your workload.