Apache Arrow and Parquet — Columnar Data for Analytics
Understand columnar data formats for analytics workloads — why CSV is dying, how Parquet stores data, and how Arrow enables zero-copy data exchange.
CSV has been the universal language of data exchange for decades. Export to CSV, email it around, import it somewhere else. Simple. Universal. And increasingly inadequate.
CSV files have no types (is "42" a number or a string?), no compression (a million rows of data is a million rows of text), no schema enforcement, and terrible query performance. When your data grows beyond what fits in a spreadsheet, CSV becomes a bottleneck.
Apache Parquet and Apache Arrow represent the modern approach to data storage and exchange. Parquet stores data on disk in a compressed, columnar format. Arrow provides an in-memory representation for lightning-fast data processing. Together, they're replacing CSV in analytics, data engineering, and increasingly in application development.
Row vs. Co
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