Conference paper (in proceedings)
Towards dynamic SQL compilation in Apache Spark
Published in:
- Companion Proceedings of the 4th International Conference on the Art, Science, and Engineering of Programming (<Programming’20> Companion), March 23–26, 2020, Porto, Portugal. - 2020, p. 4 p.
English
Big-data systems have gained significant momentum, and Apache Spark is becoming a de-facto standard for modern data analytics. Spark relies on code generation to optimize the execution performance of SQL queries on a variety of data sources. Despite its already efficient runtime, Spark’s code generation suffers from significant runtime overheads related to data de-serialization during query execution. Such performance penalty can be significant, especially when applications operate on human-readable data formats such as CSV or JSON.
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Computer science and technology
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License undefined
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green
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https://n2t.net/ark:/12658/srd1324935
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