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Document SUMMARY indexes in Indexing CTables notebook - #729

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prb2 wants to merge 2 commits into
Blosc:mainfrom
prb2:pb/summary-indexes

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@prb2 prb2 commented Sep 30, 2026 •

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Summary

This PR adds a new section to the "Indexing CTables" tutorial notebook to describe SUMMARY indexes and provides an example benchmark to demonstrate the benefit.

Addresses #645.

Testing

  • Ran the new notebook cell and confirmed the results are reasonable.
  • Ran all the notebook cells and confirmed there is no regression.
  • Generated the documentation locally with Sphinx and verified that the rendered notebook looks good.

AI Tool Use

I used Codex to generate the boilerplate code in the Generate the dataset section. I had also used it to generate the Run the benchmark section, but ended up rewriting that code myself.

"id": "d9fa565cab114c0d",
"metadata": {},
"source": [
"## Automatic SUMMARY indexes\n",

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I sourced this text from the PR description of #643 and from the existing info about summary indexes in the Optimization Tips guide

" blosc2.open(str(summary_path), mode=\"r\") as summary_readings,\n",
" blosc2.open(str(no_summary_path), mode=\"r\") as no_summary_readings,\n",
"):\n",
" def predicate(t):\n",

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In this notebook, I only focused on the benefit to where() queries, since the min()/max() benefits were already covered in the Optimization Tips guide. However, I'm happy to add a min/max example here too, if desired.

@prb2
prb2 marked this pull request as ready for review September 30, 2026 19:42

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