1. taskQueueCapacity 256 is too small for production when we want to
re-write the entire collection
2. tasks should be cleaned when unable to recover, or the meta will
remain in etcd forever later.
Signed-off-by: yangxuan <xuan.yang@zilliz.com>
issue: #33550
balance segment and balance segment execute at same time, which will
cause bounch of corner case.
This PR disable simultaneous balance of segments and channels
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
issue : https://github.com/milvus-io/milvus/issues/36864
I have a few questions regarding my approach.I will consolidate them
here for feedback and review.Thanks
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Signed-off-by: Nischay Yadav <nischay.yadav@ibm.com>
Signed-off-by: Nischay <Nischay.Yadav@ibm.com>
Limit the maximum concurrency of channel tasks for each DataNode to
prevent excessive subscriptions from causing DataNode OOM.
issue: https://github.com/milvus-io/milvus/issues/37665
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
Timeout is a bad design for long running tasks, especially using a
static timeout config. We should monitor execution progress and fail the
task if the progress has been stale for a long time.
This pr is a small patch to stop DC from marking compaction tasks
timeout, while still waiting for DN to finish. The design is
self-conflicted. After this pr, mix and L0 compaction are no longer
controlled by DC timeout, but clustering is still under timeout control.
The compaction queue capacity grows larger for priority calc, hence
timeout compactions appears more often, and when timeout, the queuing
tasks will be timeout too, no compaction will success after.
See also: #37108, #37015
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Signed-off-by: yangxuan <xuan.yang@zilliz.com>
This PR splits sealed segment to chunked data to avoid unnecessary
memory copy and save memory usage when loading segments so that loading
can be accelerated.
To support rollback to previous version, we add an option
`multipleChunkedEnable` which is false by default.
Signed-off-by: sunby <sunbingyi1992@gmail.com>
See #36550
This PR made 2 changes:
1. Introducing a prioritization mechanism, if
`dataCoord.compaction.taskPrioritizer` is set to `level`, compaction
tasks are always executed as the priority of L0>Mix>Clustering
2. `dataCoord.compaction.maxParallelTaskNum` now controls the
parallelism of executing tasks, not the task number of queue +
executing.
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Signed-off-by: Ted Xu <ted.xu@zilliz.com>
5 percent of free memory is too less for l0 compaction. This pr will
raise it to 50 percent.
See also: #36614
Signed-off-by: yangxuan <xuan.yang@zilliz.com>
1. Optimize import scheduling strategic:
a. Revise slot weights, calculating them based on the number of files
and segments for both import and pre-import tasks.
b. Ensure that the DN executes tasks in ascending order of task ID.
2. Add time cost metric and log.
issue: https://github.com/milvus-io/milvus/issues/36600,
https://github.com/milvus-io/milvus/issues/36518
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Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
Native support for Google cloud storage using the Google Cloud Storage
libraries. Authentication is performed using GCS service account
credentials JSON.
Currently, Milvus supports Google Cloud Storage using S3-compatible APIs
via the AWS SDK. This approach has the following limitations:
1. Overhead: Translating requests between S3-compatible APIs and GCS can
introduce additional overhead.
2. Compatibility Limitations: Some features of the original S3 API may
not fully translate or work as expected with GCS.
To address these limitations, This enhancement is needed.
Related Issue: #36212
Related to #35303
This PR add a param item to support change l0 forward behavior from bf
filtering and forward to remote load.
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Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #33285
- using streaming service in insert/upsert/flush/delete/querynode
- fixup flusher bugs and refactor the flush operation
- enable streaming service for dml and ddl
- pass the e2e when enabling streaming service
- pass the integration tst when enabling streaming service
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Signed-off-by: chyezh <chyezh@outlook.com>
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>