Tag: #parquet
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 5 posts
Parquet 2.13.0 Adds nan_count and IEEE 754 Total Order — How Float Statistics Got Fixed After 3 Years and 3 Months
Parquet's min/max statistics are the mechanism that lets query engines skip data. But on floating-point columns, this mechanism has been subtly broken for over 10 years — NaN returns false in every comparison, so it gets
2026-07-16 · 17 min read #data-engineering#parquet#columnar-storage#apache-arrowInfluxDB 3 Core's 72-Hour Limit Is Actually a 432-File Limit — The Bill Left by Rewriting Parquet
InfluxDB 3 rewrote its entire engine in Rust and put the storage layer on Apache Arrow and Parquet. It is commonly claimed that Core only queries the last 72 hours, but reading the source shows no such code. What actuall
2026-07-16 · 18 min read #database#influxdb#time-series#parquet#storage-engineDuckDB in Practice — The Era of Embedded Analytics That Ends on Your Laptop
Why is DuckDB, often called the SQLite of OLAP, so loved? We start from the architecture and cover direct Parquet querying, hands-on examples of window functions, PIVOT, and ASOF JOIN, zero-copy integration with pandas,
2026-06-12 · 14 min read #duckdb#database#olap#analytics#parquetColumnar Storage Deep Dive 2025: Parquet, ORC, Apache Arrow, Dremel — Why Analytics DBs Are 10,000x Faster
How Snowflake, BigQuery, and Spark query terabytes in seconds. A complete tour of Parquet Dremel structure, ORC, Apache Arrow in-memory format, RLE/Dictionary compression, and vectorized execution.
2026-04-15 · 13 min read #columnar-storage#parquet#orc#apache-arrow#dremelDuckDB OLAP Analytics and Data Lake Guide
A guide to using DuckDB for OLAP analytics and data lake querying, covering in-process analytics, Parquet integration, and performance optimization.
2026-03-08 · 22 min read #database#duckdb#olap#analytics#data-lake