PDE Ingesting and Processing the Data Practice Question
You are using Dataproc to run a Spark job that reads data from Cloud Storage, performs aggregations, and writes results back to Cloud Storage. The job is failing with out-of-memory errors on the shuffle. Which optimization should you apply?
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Increase spark.sql.shuffle.partitions
For shuffle-heavy operations, increasing the number of partitions reduces the size of each partition, reducing memory pressure. Alternatively, using DataFrames with optimized serialization (e.g., Kryo) helps.
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