Working with big data can be a challenge, thanks to the performance overhead associated with moving data between different tools and systems as part of the data processing pipeline. Indeed, because programming languages, file formats and network protocols have different ways of representing the same data in memory, the process of serializing and deserializing data into a different representation at potentially each step in a data pipeline makes working with large amounts of data slower and more costly in terms …
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How Apache Arrow speeds big data processing
Nov. 7, 2023, 10 a.m. | Anais Dotis-Georgiou
InfoWorld Analytics www.infoworld.com
analytics apache apache arrow arrow big big data big data processing challenge data data processing indeed languages memory moving network part performance pipeline process processing programming programming languages sql systems tools
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