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perf: compact batched FTS DocID outputs#1136

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zhanhongliu2001 wants to merge 156 commits into
oceanbase:vldb_2026from
zhanhongliu2001:codex/perf-compact-batched-fts-docid-outputs
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perf: compact batched FTS DocID outputs#1136
zhanhongliu2001 wants to merge 156 commits into
oceanbase:vldb_2026from
zhanhongliu2001:codex/perf-compact-batched-fts-docid-outputs

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@zhanhongliu2001

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Summary

  • compact batched FTS DocID outputs in the sparse DAAT iterator
  • reduce repeated per-row output handling in the FTS retrieval hot path
  • submit the exact code state at commit 322594223ea35cba11e898ebfc7b92f5fc6bbcf8 for VLDB benchmark evaluation

Validation

  • verified the local branch head exactly matches 322594223ea35cba11e898ebfc7b92f5fc6bbcf8
  • git diff --check 3225942^ 3225942 passes
  • no additional local generated files are included

wangzelin.wzl and others added 30 commits November 4, 2025 19:10
[TABLELOCK] fix the bug of mysql lock table in observer-lite
[MV.BUGFIX] fail to drop index for mv table with renamed index
fix ivf async task generate_aux_table_info_map when schema_version not change
Optimize the bootstrap time of the observer
Fixed oceanbase#21, [Enhancement]: remove old python sdk demo in the Readme
Fixed oceanbase#24, [Enhancement]: Refine Key Features in README.md
Fixed oceanbase#27, [Bug]: update build and run observer part in README.md
refine product comparison table
Added full-text and vector indexes to the articles table for improved search capabilities.
Added full-text and vector indexing to articles table for improved search capabilities.
Signed-off-by: SamYuan1990 <yy19902439@126.com>
zhanhongliu2001 and others added 28 commits July 14, 2026 01:08
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CLAassistant commented Jul 18, 2026

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CLA assistant check
Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.
2 out of 4 committers have signed the CLA.

✅ cao1629
✅ sallyjinx
❌ wangzelin.wzl
❌ zhanhongliu2001


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@LINxiansheng

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Document AI & IK Custom Dictionary Score

Document AI Functions Score
===========================
score: 100.00 / 100
load_file: 50 / 50
ai_split_document: 50 / 50

IK Custom Dictionary Score
==========================
score: 100.00 / 100
ik_custom_dict: 100 / 100

FTS Large Benchmark Score

FTS Large Benchmark Score
=========================
score: 79.85 / 100
mean_improvement: 39.92%
full_score_improvement: 50.00%

build_improvement: 44.11%
  build_ik_all_sec: baseline=35.2836, current=19.799, improvement=43.89%
  build_ik_content_sec: baseline=28.3764, current=15.633, improvement=44.91%
  build_beng_en_sec: baseline=14.7578, current=8.332, improvement=43.54%
tokenize_improvement: -4.67%
  tokenize_ik_avg_ms: baseline=0.76478, current=0.7871, improvement=-2.92%
  tokenize_beng_avg_ms: baseline=0.42262, current=0.4498, improvement=-6.43%
query_improvement: 80.33%
  query_cn_avg_ms: baseline=16.6628, current=3.1315, improvement=81.21%
  query_beng_avg_ms: baseline=24.3042, current=5.9346, improvement=75.58%
  query_mixed_avg_ms: baseline=17.5593, current=4.6886, improvement=73.30%
  query_limit_avg_ms: baseline=16.2334, current=1.4214, improvement=91.24%

FTS Large Benchmark Report

========================================
FTS Large Benchmark Report
========================================
timestamp:              2026-07-18 07:45:46
label:                  vldb-ci-29635160087-1
git_head:               3225942
git_dirty:              0
rows:                   20000
batch:                  500
rounds:                 3000
query_rounds:           200
samples:                3
warmup:                 30
skip_load:              0
----------------------------------------
select1_avg_ms:         0.2678
select1_stdev_ms:       0.0048
raw_load_sec:           1.633
raw_load_rows_per_sec:  12247.4
build_ik_all_sec:       19.799
build_ik_content_sec:   15.633
build_beng_en_sec:      8.332
build_total_sec:        43.782
----------------------------------------
tokenize_ik_avg_ms:     0.7871
tokenize_ik_median_ms:  0.7866
tokenize_ik_stdev_ms:   0.0089
tokenize_beng_avg_ms:   0.4498
tokenize_beng_median_ms:0.4368
tokenize_beng_stdev_ms: 0.0193
----------------------------------------
query_cn_hits:          8001
query_cn_avg_ms:        3.1315
query_cn_stdev_ms:      0.0089
query_beng_hits:        11000
query_beng_avg_ms:      5.9346
query_beng_stdev_ms:    0.0833
query_mixed_hits:       7332
query_mixed_avg_ms:     4.6886
query_mixed_stdev_ms:   0.0676
query_limit_hits:       20
query_limit_avg_ms:     1.4214
query_limit_stdev_ms:   0.0042
========================================

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