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What determines the maximum parallelism achievable in Databricks?

Spark/Big Datamedium0.4 min readPremium
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TCS
Key Concepts Tested
partitionsparksql
Expert AnswerPremium
85 wordsInterview-ready
**Factors**: (1) **Total cores**—executors × cores per executor. (2) **Input partitions**—spark.sql.files.maxPartitionBytes (default 128MB); 1TB = ~8K partitions max. (3) **Shuffle partitions**—spark.sql.shuffle.partitions (default 200). (4) **Cluster size**—autoscale min/max. (5) **External**—Kafka partitions, source parallelism. **Formula**: Effective parallelism = min(partition_count, total_cores). Bounded by slowest stage. **Why It Matters**: Over-provisioning cores = waste....
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