Introducing Project Tungsten

Project Tungsten was touted as the largest change to Spark's execution engine since the project's inception. The motivation for Project Tungsten was the observation that CPU and memory, rather than I/O and network, were the bottlenecks in a majority of Spark workloads.

The CPU is the bottleneck now because of the improvements in hardware (for example, SSDs and striped HDD arrays for storage), optimizations done to Spark's I/O (for example, shuffle and network layer implementations, input data pruning for disk I/O reduction, and so on) and improvements in data formats (for example, columnar formats like Parquet, binary data formats, and so on). In addition, large-scale serialization and hashing tasks in Spark are ...

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