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pg_diskann PQ mode causes TOAST corruption during vector insert (possibly after deleting items and index rebuild doesnt work correctly)

Geoff Fletcher 0 Reputation points
2026-04-04T23:18:25.3533333+00:00

During vector ingestion with pg_diskann Product Quantization (PQ) enabled, multiple TOAST values become corrupted in pg_toast_27911. Error:

Failed to store final vector batch: missing chunk number 0 for toast value 469475 in pg_toast_27911

Affected toast values: 460018, 460020, 460023, 469475. Corruption consistently hits the final batch of each ingestion run. Disabling PQ resolves the issue — ingestion completes without TOAST errors.

This seems to happen after deleting docs and the vector index is rebuilt incorrectly. Then adding new vectors gets the TOAST error.

Rebuilding the index fixes it, but then it will break again after some time.

Azure Database for PostgreSQL

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  1. Q&A Assist
    2026-04-04T23:18:36.17+00:00
    AI generated content. This question contains an answer created with AI from Q&A Assist. Learn more

    The described TOAST corruption during inserts with pg_diskann Product Quantization (PQ) enabled is not covered in the provided documentation, and no specific fix or known issue is documented in the context.

    The available guidance for pg_diskann with PQ is limited to:

    1. PQ must be enabled explicitly on the index:
         CREATE INDEX demo_embedding_diskann_idx ON demo USING diskann(embedding vector_cosine_ops) 
         WITH(
             product_quantized=true
         );
      
    2. PQ is supported starting from pg_diskann v0.6 and above.
    3. For high-dimensional embeddings (up to 16,000 dimensions), PQ must be turned on and recommended settings are:
      • product_quantized = true
      • pq_param_num_chunks = embedding_dimension / 3
      • pq_param_training_samples is auto-determined unless explicitly set.
    4. To improve accuracy with PQ, use a two-step query with approximate search followed by full-vector reranking.
    5. For certain DiskANN index metadata/version errors, the documented recovery is to run REINDEX / REINDEX CONCURRENTLY or rebuild/upgrade the index, but there is no mention of TOAST corruption or a related bug.

    Given the context, only the following supported actions can be recommended:

    1. Ensure pg_diskann version
      • Confirm that pg_diskann is v0.6 or higher, as PQ support is only documented from v0.6 onward.
    2. Rebuild or reindex when index metadata issues occur
      • For index metadata or version issues, the documented recovery pattern is:
             REINDEX INDEX your_index_name;          -- or REINDEX CONCURRENTLY
             -- or
             DROP INDEX your_index_name;
             CREATE INDEX your_index_name ON your_table USING diskann(your_vector_column vector_cosine_ops);
        
      • And, when prompted by a version-upgrade message, using upgrade_diskann_index() to upgrade all DiskANN indexes.
      • Although this pattern is documented for specific DiskANN errors (not TOAST corruption), it is the only supported remediation pattern in the context for index-related issues.
    3. Use PQ with recommended parameters for large/high-dimensional workloads
      • When PQ is enabled, follow the documented recommendations for pq_param_num_chunks and allow pq_param_training_samples to be auto-determined unless there is a specific need to override it.

    Because the context does not document TOAST corruption, a bug, or a configuration workaround for this specific behavior, no further product-specific remediation steps can be provided from the supplied material.


    References:

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