749 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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Page 18 of 125
  1. 01The Jackson 3 Problem in Apache Iceberg, and What It Means for Your CodeJackson 3 changes everything: package names, unchecked exceptions, flipped defaults. Here's what breaks, why the engines are fine and your service isn't, and how to migrate safely.
  2. 02Wiring an AI Agent to Apache Polaris with the Model Context ProtocolThe catalog is the right attachment point for AI agents working against a lakehouse. Here's how to wire the official Polaris MCP Server and add the read path it deliberately leaves out.
  3. 03Governing Iceberg Tables Across Regions Without Three Sets of PermissionsCatalog federation gives you one authorization model and one audit point across regions. Here's what it solves, what it doesn't, and how to build a topology you can actually govern.
  4. 04Federating Oracle With an Open Lakehouse Instead of Migrating ItFederate first so analytics work now, migrate what benefits from migrating, and leave the rest where it is indefinitely. Here's how pushdown and view layers make it work.
  5. 05The Parquet Versioning Problem, and Why Iceberg Cares About ItParquet files have a version field that doesn't reliably signal feature requirements. A new versioning discipline is coming, borrowing from Iceberg's format version model.
  6. 06Building Iceberg Pipelines in Python Without Standing Up SparkA large share of production transformations fit comfortably on one machine. PyIceberg, DuckDB, and branch isolation give you a production path that debugs in an IDE.