DuckDB Analytics: Local OLAP, Extensions, and Embedded Data Apps

"DuckDB Analytics: Local OLAP, Extensions, and Embedded Data Apps"

DuckDB has changed what “analytics” can look like when the database lives inside your process, ships with your application, and queries files as naturally as tables. This book is written for experienced data engineers, analytics engineers, and software developers who want a rigorous mental model of DuckDB as a local OLAP engine—one that favors fast iteration, disciplined performance, and pragmatic architecture over warehouse ceremony.

You’ll learn to design analytical SQL that stays correct and fast under scale, interpret execution plans, and place materialization boundaries intentionally using CTAS, COPY, and layered persistence. The book goes deep on file-centric analytics: Parquet layout and partitioning, schema evolution, and remote object storage via `httpfs`, including latency budgets and pushdown strategies. It also treats extensions as a first-class capability system, covering how to evaluate, pin, and operate extensions safely—especially for Iceberg and Delta lakehouse workflows with real-world limitations.

Along the way, you’ll build embedded data application instincts: API and connection lifecycle patterns across language bindings, Arrow/DataFrame zero-copy interoperability, packaging datasets for distribution, and enforcing safety boundaries for user-driven querying. Familiarity with SQL, data formats, and production-grade engineering practices is assumed; the payoff is an end-to-end playbook for making DuckDB a reliable analytics component in both local workflows and shipped products.

© 2026 NobleTrex Press (전자책): 6610001179137

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전자책: 2026년 3월 9일