Comments (5)
/assign
from milvus.
@XuanYang-cn could be a bug injected by #32326, which was reverted in v2.4.1
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The choosing of the same segments making datanode Lock Segment twice, and block forever.
[...] ["...compaction"] [... ["segment IDs"="[449420485790442035,449420485790443250,449420485790443250]"]
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@ThreadDao Please help verify master branch, THX
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/assign @ThreadDao
/unassign
should be fixed, please help verify
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Related Issues (20)
- [Bug]: Drop a collection using ImportV2 may send huge request into meta storage. HOT 2
- [Bug]: Slow query on first load of partition in Milvus v2.4.3 HOT 12
- [Feature]: When importing binlog, ensure that the restored entities' TS order is consistent with the previous TS order. HOT 3
- [Bug]: loaded entity number metrics of querynode is inaccurate HOT 1
- [Bug]: Unable to create milvus image from docker dev container HOT 11
- [Bug]: [configuration] cannot change the localStorage path if milvus is deployed by helm HOT 1
- [Bug]: Using Milvus Docker Compose, in /var/lib/milvus, there is no data. HOT 2
- [Enhancement]: scalar memory optimization
- [Enhancement]: Milvus String Scalar filter is very slow HOT 1
- [Bug]: Metric `RootCoordQuotaStates` never reset
- [Bug]: flush all failed after milvus already gets back from many chaos test HOT 1
- [Bug]: [benchmark] Inserting data using upsert, datanode memory keeps growing HOT 1
- [Feature]: Support Squence Query Iterator HOT 1
- [Bug]: It's been a long time since Milvus recovered from the standalone pod kill chaos test, but the client still can't connect.
- [Feature]: Enable GroupBy with group size function HOT 1
- [Bug]: Milvus panic when the disk has no free space HOT 1
- [Enhancement]: Remove compaction plans on the datanode HOT 1
- [Bug]: L0 compaction not control parallel count causing DN OOM HOT 1
- [Bug]: [benchmark][cluster] search raises error `fail to search on QueryNode 7: distribution is not servcieable: channel not available` in concurrent dql and dml(multi-partition) scene
- [Bug]: [benchmark][cluster] flush 180s timeout in concurrent DML and DQL scenario
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