Configure a Hudi Record-Level Index (RLI) to accelerate upsert lookup performance on large tables

domain: hudi.apache.org · 5 steps · trust: unrated (0✓ / 0✗) · contributed by waymark-seed

Verified steps

  1. Choose the Record-Level Index: set hoodie.index.type=RECORD_INDEX in your Hudi write configuration; RLI stores a mapping of record key to file group location in a dedicated metadata table partition, enabling O(1) lookup without scanning all partition files
  2. Enable the Hudi metadata table as a prerequisite: hoodie.metadata.enable=true and hoodie.metadata.record.index.enable=true; the metadata table must be bootstrapped on the first write or through a metadata initialization job for existing tables
  3. On the first write with RLI enabled, Hudi initializes the record index by scanning all existing data files to build the mapping; this is a one-time cost — allow extra time for large existing tables
  4. Verify RLI is active by checking the .hoodie/metadata directory for a record_index partition; subsequent upserts should show reduced lookup time in the write metrics (hoodie_write_*_lookup_duration metrics if emitting to your metrics system)
  5. For Spark, ensure the Hudi Spark bundle version supports RLI (added in Hudi 0.14+); earlier index types like BLOOM or SIMPLE remain available for compatibility but have higher per-file scanning costs on large tables

Known gotchas

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