VyomaStack
Spark

Spark Executor Memory Calculator

Calculate Spark executor memory, overhead, and cluster totals. Get AI-powered tuning recommendations for production workloads.

Spark Memory Calculator
Estimate executor overhead, unified memory, and cluster totals using Spark's default memory model. Get AI tuning recommendations.
GB
GB
GB
Dataset (100 GB) may exceed available execution memory (~21.6 GB). Increase executors or memory, or enable spill/disk persistence.

Overhead / executor

819 MB

On-heap / executor

7.20 GB

Execution memory / executor

2.16 GB

Storage memory / executor

2.16 GB

Memory per core

1.80 GB

Total cluster memory

84.00 GB

Suggested spark-submit

spark-submit \
  --executor-memory 8g \
  --executor-cores 4 \
  --num-executors 10 \
  --driver-memory 4g \
  --conf spark.memory.fraction=0.6 \
  your-app.jar
AI Spark Tuning Advisor
Get expert recommendations on executor sizing, memory tuning, and cost optimization based on your configuration. Free tier: ~15 requests/min — wait a few seconds between clicks.
How memory is calculated

Overhead — max(384 MB, 10% of executor memory), reserved off-heap for JVM metaspace and threads.

Unified memory — on-heap × spark.memory.fraction (default 0.6), split 50/50 between execution and storage.

AI Advisor — analyzes your config and suggests production-ready tuning.

Related Tools

Frequently Asked Questions

How does Spark executor memory work?
Spark reserves off-heap overhead (max 384 MB or 10% of executor memory), then splits remaining on-heap memory between user code and unified memory (execution + storage) based on spark.memory.fraction.
What is a good executor memory size?
Most workloads run well with 4–8 GB per executor and 2–5 cores. Larger executors increase GC pressure; smaller ones may spill to disk during shuffles.
Does this include AI recommendations?
Yes. After calculating memory breakdown, use the AI Spark Tuning Advisor for personalized recommendations based on your configuration.
Is this calculator free?
Yes. Memory calculation runs in your browser. AI recommendations require an API key configured by the site operator.