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Improve performance for roundrobin shuffle writes for nested schemas #5397

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Description

@comphead

What is the problem the feature request solves?

Noticed dramatic slowdown for tasks with shuffle writes for RR repartition comparing to Spark, 2-3x to be more precise.

Specifically for the nested schemas, there is some inefficiency when native shuffle deals with wide/complex fields. its invisible for TPC-* benchmarks because of historical flat schema. But in real user world this is pretty much downside.

Describe the potential solution

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Activity

  1. self-assigned this
    on Aug 20, 2026
  2. comphead commented on Aug 20, 2026

    @comphead
    ContributorAuthor

    MIght be related to obtain correct shuffle metrics #5370

  3. comphead commented on Aug 21, 2026

    @comphead
    ContributorAuthor

    Spark

    Image

    Comet

    Image

    With vectorized shuffle

    Image
  4. changed the title [-]Improve performance for shuffle writes for nested schemas[/-] [+]Improve performance for roundrobin shuffle writes for nested schemas[/+] on Aug 22, 2026
  5. comphead commented on Aug 22, 2026

    @comphead
    ContributorAuthor

    I'm experimenting with

    • xxhash-rust, as looks like hashing tooks lots of time and we have to hash the entire heavyweight row
    • vectorized shuffle, when counter based distribution not by row, but by arrow batch
  6. comphead commented on Aug 22, 2026

    @comphead
    ContributorAuthor

    with vectorized shuffle pretty good results

    Image

    UPD: This was another dataset experiment, and originally Comet took 21 mins to complete, now 10. It is still experimenting

  7. comphead commented on Aug 24, 2026

    @comphead
    ContributorAuthor

    xxhash-rust experiment, takes much longer

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