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How to find metrics

Job metrics can be found in the Geneva Console UI, by clicking on a job’s ID to get to the “Job details” page.

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Core diagnostic metrics

MetricWhat it meansCommon signal
rows_checkpointedRows finished by read/UDF/checkpoint stage.High value means upstream compute is progressing.
rows_ready_for_commitRows ready for atomic commit (becoming visible to other DB connections).If much lower than rows_checkpointed, writer path is likely bottlenecked.
rows_committedRows already visible to other DB connections.If lagging far behind rows_ready_for_commit, commit stage may be bottlenecked.
cnt_geneva_workers_activeCurrent parallel UDF executors.Lower than expected means reduced effective parallelism.
cnt_geneva_workers_pendingDeficit from desired parallelism.Persistently high value usually means scheduling/resource pressure.
read_io_time_msCumulative read IO time.Dominant value suggests storage/read bottleneck.
udf_processing_timeCumulative UDF execution time.Dominant value suggests compute/UDF bottleneck.
batch_checkpointing_timeCumulative batch checkpoint overhead.High value suggests checkpoint overhead is expensive.
writer_write_timeCumulative writer output time.High value often points to object storage throughput/throttling issues.
writer_queue_wait_time_msCumulative writer queue wait time.High value can indicate writer starvation/backpressure.
commit_time_msCumulative commit time.High value means commit itself is expensive.
commit_conflict_retriesCommit retries due to version conflicts.Non-trivial counts indicate commit contention.
commit_backoff_time_msTime spent backing off during commit retries.High value indicates contention/retry pressure.
commit_concurrent_writer_retriesRetries from “Too many concurrent writers”.High value indicates writer concurrency contention.

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Quick diagnosis workflow

  1. Check rows_checkpointed vs rows_ready_for_commit.
    • If rows_checkpointed is high but rows_ready_for_commit is low, fragment writer is usually the bottleneck.
    • This often indicates object storage read/write pressure (for example S3).
  2. Compare read, UDF, and checkpoint timing.
    • High read_io_time_ms: storage or scan bottleneck.
    • High udf_processing_time: UDF compute bottleneck.
    • High batch_checkpointing_time: checkpoint overhead bottleneck.
    • Typical mitigations: increase checkpoint_size, increase max_checkpoint_size, or compact the table to produce larger fragments.
  3. Check writer timing.
    • High writer_write_time is commonly object storage throttling/throughput limit.
    • Typical mitigations: use higher network-bandwidth node types, and keep object storage and compute nodes in the same region.
  4. Check commit pressure.
    • High commit_conflict_retries, commit_backoff_time_ms, or commit_concurrent_writer_retries indicates commit contention.
  5. Check parallelism deficit.
    • If cnt_geneva_workers_pending stays high while cnt_geneva_workers_active stays low, the job is running below desired parallelism due to cluster/resource constraints.

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Notes

  • Timing metrics are cumulative and may overlap; do not sum them as exact wall time.
  • For completed jobs, row counters should settle to stable final values.