775 tutorials · free to read

A working handbook for data and software engineering.

Hands-on tutorials by Alex Merced on Apache Iceberg, the data lakehouse, pipelines, agentic AI, and the languages and tools that hold it all together.

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  1. 01Fast Classification Models, LLMs, and the Apache Iceberg LakehouseHow fast classification models like Jev alongside open alternatives such as GLiClass compare with LLMs, and how to run both together inside an Apache Iceberg lakehouse.
  2. 02Why the Iceberg DataFusion Integration Is Moving to Apache DataFusionWhy the Iceberg DataFusion integration moved to the DataFusion project, and what the split means for users, Comet, and iceberg-rust contributors.
  3. 03What Iceberg v4's Proposed FILE Type Means for Multimodal TablesIceberg v4's proposed FILE type brings first-class media references to tables, via Parquet's FILE logical type, ranges, checksums, and pre-signed URLs.
  4. 04How Apache Ossie Is Deciding What Agents and BI Tools Can Ask a Semantic LayerHow Apache Ossie's layered query design gives AI agents both a constrained dimensional interface and a grain-safe SQL interface for semantic layers.
  5. 05CVE-2026-73334 and the Trust Boundary Inside an Encrypted Parquet FileCVE-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.
  6. 06Parquet Page Indexes and the Last Mile of Pruning in Apache IcebergParquet 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.