sql: improve inverted index validation performance #35742
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@lucy-zhang it's probably worth adding a benchmark so that future changes don't cause a regression in performance. Thanks! |
dt
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May 13, 2019
To compute the expected number of keys in an inverted index, we currently generate every key and count the number of unique keys, since array elements can produce duplicate keys. This PR avoids some of these allocations by doing a simple count for every non-array JSON type. For a 25GB table of random JSON values generated by the workload, I got a ~15% speedup on the `select sum(crdb_internal.json_num_index_entries(v)) from json.j` query. Release note: None
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I added a benchmark for a JSON object containing mostly scalars and few arrays: |
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bors r+ |
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35742: sql: improve inverted index validation performance r=lucy-zhang a=lucy-zhang To compute the expected number of keys in an inverted index, we currently generate every key and count the number of unique keys, since array elements can produce duplicate keys. This PR avoids some of these allocations by doing a simple count for every non-array JSON type. For a 25GB table of random JSON values generated by the workload, I got a ~15% speedup on the `select sum(crdb_internal.json_num_index_entries(v)) from json.j` query. Release note: None Co-authored-by: Lucy Zhang <lucy-zhang@users.noreply.github.com>
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To compute the expected number of keys in an inverted index, we currently
generate every key and count the number of unique keys, since array elements
can produce duplicate keys. This PR avoids some of these allocations by doing a
simple count for every non-array JSON type. For a 25GB table of random JSON
values generated by the workload, I got a ~15% speedup on the
select sum(crdb_internal.json_num_index_entries(v)) from json.jquery.Release note: None