Storage & file formats — Parquet, Avro, ORC internals, and S3 layout¶
Every analytics query, every Spark job, every training-data load ultimately does one thing: it reads bytes from storage. How those bytes are arranged — row by row or column by column, in one file or a million, sorted or shuffled, compressed with which codec, described by which metadata — routinely makes a 10× to 1000× difference in scan time and dollar cost, before you touch a single line of query logic. …
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