Comments (9)
Yes, I just tested and v2.4.2-20240515-b2d83d33
works for me
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After waiting like 10 minutes, I was running another query and noticed the "missing" ID count dropped from 972604 to:
>>> c.query(collection_name='test', filter='id > 0', output_fields=["count(*)"])
[{'count(*)': 701303}]
EDIT: and again:
>>> c.query(collection_name='test', filter='id > 0', output_fields=["count(*)"])
[{'count(*)': 581652}]
```
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reproduced on milvus 2.4.1 with pymilvus 2.4.2 after a few attempt, printed more info in one run
the 1st time at round 104
the final results count
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@congqixia please help to take a look, my cluster
yanliang-241-milvus-standalone-5bc7b96ff6-96vnz 1/1 Running 0 2m58s 10.104.5.184 4am-node12 <none> <none>
/assign @congqixia
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maybe already fixed by #32858
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you are right. not reproduced on v2.4.2-20240515-b2d83d33. @bostrt could you please also try on this build?
maybe already fixed by #32858
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/assign @bostrt
/unassign
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/assign @yanliang567
/unassign
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good to know that. I'd close this issue as Milvus released a new version
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Related Issues (20)
- [Bug]: Search did not return enough result after segment compaction HOT 3
- [Bug]: [GoSDK] Create binary vector collection with invalid dim returns no error HOT 3
- [Bug]: Querynode failed to load index when collection has multi indexes HOT 4
- [Enhancement]: Optimize some hot spot under 10k collections
- [Bug]: Filtering by partition key fails to return results for bulk imported data HOT 7
- [Bug]: Setup a concurrency limit on watch channel HOT 1
- [Bug]: fail to search after upgrade from 2.3.15 to 2.4.1 and roll back to 2.3.15 HOT 1
- [Bug]: the server will not work properly when using a non-existent db HOT 1
- [Bug]: Do not retry infinitely when datanode download binlog HOT 1
- [Bug]: [CI] Deleted data can be queried HOT 3
- [Bug]: Unit test TestCacheWriter_WithAutoFlush may failed with deadlock HOT 2
- [Enhancement]: Optimize datanode cpu usage under large collection number
- [Bug]: test_compact_during_insert failed HOT 1
- [Bug]: The search vector being too far away can lead to inaccurate result sets. HOT 3
- [Bug]: Too many L0 segments caused query node OOM. HOT 2
- [Bug]: Forgetting to set blob memory size when compaction resulted a huge segment being generated HOT 3
- [Enhancement]: Support Log Service in Milvus
- [Bug]: milvus querynode memory crash, how to locate the cause HOT 13
- [Bug]: wrong operate to drop collection/database etc. with prefix in snapshot HOT 11
- [Bug]: Zero Recall Rate, Very Strange for multi-vector search!!!!!!! HOT 20
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