spark.shuffle.spill

Spark.shuffle.spill is a configuration parameter in Apache Spark that specifies the amount of memory that can be used by the shuffle operations before spilling data to disk.

Shuffle is a process in Spark where data is grouped, sorted, and aggregated across the nodes in a cluster. When the amount of data is too large to fit in memory, Spark spills the data to disk. This can cause a significant performance impact as disk I/O is much slower than memory operations.

The spark.shuffle.spill parameter sets the maximum amount of memory that can be used for shuffle operations before spilling to disk. This value should be set based on the available memory in the cluster and the size of the data being processed. Setting this value too high can lead to excessive memory usage and out-of-memory errors, while setting it too low can result in frequent disk spills and reduced performance.

By default, spark.shuffle.spill is set to 200 MB. It can be adjusted in the Spark configuration file or using the SparkConf object in a Spark application.