Comments (11)
The title and description of this issue contains Chinese. Please use English to describe your issue.
from milvus.
Referring to the Sizing Tools, allocate Data Nodes with 2 cores of 8 GB x 2 pods.
However, during actual operation, the Data Nodes was an OOM, and after expansion, the memory usage reached 40G.
from milvus.
datanode log:
from milvus.
@yesyue please share more info about how you using milvus, e.g. what kinds of requests did you call to milvus, how many, and how frequency of them? also please help all the milvus pods logs for invesgitaion.
/assign @yesyue
/unassign
from milvus.
100 Million/day entites write to milvus
from milvus.
100 Million/day entites write to milvus
after I inserted 10M entites total, then milvus docker stop and crash. I use IVF_SQ8 index, installed milvus with gpu.
I use batch insert 10000 (only insert if enough 10000 entities.
after crash I can't connect to connection again and can't use anything. Any solution?
from milvus.
- seems that flush can not catch up the read.
- how many partitions do you have? if you have many partitions or collections, the flush and memory consumption will be larger than estimation.
- there is bunch of configs to tune, like concurrent flush number -> dataNode.dataSync.maxParallelSyncMgrTasks (for 2.4)
memory used for growing segment
from milvus.
100 Million/day entites write to milvus
after I inserted 10M entites total, then milvus docker stop and crash. I use IVF_SQ8 index, installed milvus with gpu. I use batch insert 10000 (only insert if enough 10000 entities.
after crash I can't connect to connection again and can't use anything. Any solution?
how much gpu memory do you have?
please open another issue with detailed logs so we can help
from milvus.
from milvus.
1.could you offer log for datanode?
2. it would be great if you have a datanode pprof, so you know which part takes of your memory. Most likely it's insert buffer takes the memory and you can tune the flush parameter
from milvus.
I saw you in many issues and we'd like to offer help.
feel free to contact me at [email protected] if necessary
from milvus.
Related Issues (20)
- [Bug]: Unable to create milvus image from docker dev container HOT 14
- [Bug]: [configuration] cannot change the localStorage path if milvus is deployed by helm HOT 8
- [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 4
- [Bug]: Metric `RootCoordQuotaStates` never reset
- [Bug]: flush all failed after milvus already gets back from many chaos test HOT 11
- [Bug]: [benchmark] Inserting data using upsert, datanode memory keeps growing HOT 3
- [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. HOT 1
- [Feature]: Enable GroupBy with group size function HOT 1
- [Bug]: Milvus panic when the disk has no free space HOT 2
- [Enhancement]: Remove compaction plans on the datanode HOT 1
- [Bug]: L0 compaction not control parallel count causing DN OOM HOT 2
- [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 HOT 1
- [Bug]: [benchmark][cluster] flush 180s timeout in concurrent DML and DQL scenario HOT 2
- [Feature]: Adding a generic virtual resource allocator to orchestrate usage of memory, CPU, and disk, across different components
- [Enhancement]: Pre-allocate space for datanode insert buffer preventing frequent grow slice
- [Enhancement]: Support access log print consistency level
- [Bug]: read source yaml failed: error converting YAML to JSON: yaml: line 22: block sequence entries are not allowed in this context HOT 1
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from milvus.