Tag:apache parquet
Articles tagged "apache parquet".
- 9 MIN READ•Oct 21, 2024
Parquet Metadata Explained: Footer, Row Groups, Statistics
Parquet metadata lives in the file footer: the schema, row group layout and per-column min/max statistics that let query engines skip data they do not need.
data lakehousedata engineeringapache parquet - 7 MIN READ•Oct 21, 2024
Read and Write Parquet Files in Python (PyArrow, Pandas)
How to read and write Parquet files in Python with PyArrow, FastParquet, and Pandas, including column selection, compression, and partitioned datasets.
data lakehousedata engineeringapache parquet - 9 MIN READ•Oct 21, 2024
Parquet Performance Tuning: 8 Best Practices
Tune Apache Parquet for speed and cost: row group and file sizes, partitioning, Snappy vs ZSTD compression, encodings, sorting, and predicate pushdown.
data lakehousedata engineeringapache parquet - 31 MIN READ•Sep 21, 2026
CVE-2026-73334 and the Trust Boundary Inside an Encrypted Parquet File
CVE-2026-73334 lets a tampered Parquet footer route a reader's KMS token to an attacker. Here's the fix, Iceberg's safe path, and how to audit your lakehouse.
Apache ParquetEncryptionKMS - 31 MIN READ•Sep 21, 2026
Parquet Page Indexes and the Last Mile of Pruning in Apache Iceberg
Parquet page indexes can cut selective Iceberg scans by an order of magnitude on sorted data. How they work, what they cost, and how to lay out tables.
Apache ParquetApache IcebergPruning - 31 MIN READ•Aug 25, 2026
FSST and ALP: The Two Encodings Fixing Parquet's Weakest Compression Cases
ALP and FSST target Parquet's worst cases: floats and high-cardinality strings. How they work and what they change for Iceberg tables.
Apache ParquetencodingsALP - 30 MIN READ•Jul 25, 2026
Iceberg's Next Version Depends on Decisions Being Made in Parquet
The Iceberg and Parquet specifications are co-evolving. Several of the most consequential Iceberg v4 proposals are waiting on Parquet work.
apache icebergapache parquetvariant type - 31 MIN READ•Jul 24, 2026
The Breakdown of the Open Lakehouse in 2026: Iceberg, Arrow, Polaris, Parquet, and Ossie, and How to Actually Build One
A detailed breakdown of the five Apache projects powering the open lakehouse in 2026, Parquet, Iceberg, Polaris, Arrow, and Ossie, and how to build one.
Apache IcebergApache ParquetApache Arrow - 28 MIN READ•Jul 6, 2026
The State of Apache Parquet in 2026: The Quiet Format Enters Its Loudest Decade
Apache Parquet in 2026, variant types, geospatial, ALP encoding, footer redesign, the versioning debate, and how the decade-old format is renovating.
Apache Parquetdata engineeringlakehouse architecture - 4 MIN READ•Mar 7, 2026
Agentic Analytics on the Apache Lakehouse
Why LLMs fail on raw Parquet in S3, and how a semantic layer, autonomous reflections, text-to-SQL, and AI SQL functions enable agentic analytics on a lakehouse.
data lakehouseapache icebergapache parquet - 4 MIN READ•Mar 7, 2026
What is Apache Arrow? Erasing the Serialization Tax
Apache Arrow removes the serialization tax with a standard in-memory columnar format, zero-copy sharing, and Arrow Flight for fast transfer across the network.
data lakehouseapache icebergapache parquet - 5 MIN READ•Mar 7, 2026
What is Apache Iceberg? The Table Format Revolution
How Apache Iceberg turns piles of Parquet files into reliable tables: its metadata tree, schema and partition evolution, time travel, and atomic snapshots.
data lakehouseapache icebergapache parquet