Apache Hudi Lakehouse

Overview

Use this skill when Apache Hudi is the primary table layer for incremental lakehouse workloads. It helps agents reason about mutation-heavy patterns, table type selection, compaction behavior, timeline safety, and consumer expectations across read-optimized and real-time query paths.

When to Use

• choosing or operating Apache Hudi for lakehouse tables
• building record-level upsert or delete pipelines
• managing compaction, clustering, and incremental consumption
• supporting lakehouse tables with heavy mutations (CDC sinks, slowly changing dimensions)
• planning multi-engine access (Spark, Presto, Trino, Athena, Hive)

Do not use this when the workload is append-only with no mutation requirements and simpler formats like Parquet or Iceberg would suffice.

Workflow