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milvus/tests/milvus_benchmark
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del-zhenwu 2b481563a8
Bench scripts for 2.0 (#6263) 
* [skip ci] update benchmark scripts for 2.0

Signed-off-by: del-zhenwu <zhenxiang.li@zilliz.com>

* [skip ci] Update README.md

Signed-off-by: del-zhenwu <zhenxiang.li@zilliz.com>

* [skip ci] Update mergify.yml for bench scripts

Signed-off-by: zhenwu <zhenwu@milvus.io>

Co-authored-by: zhenwu <zhenwu@milvus.io>
2021-07-02 11:40:16 +08:00
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Bench scripts for 2.0 (#6263)
2021-07-02 11:40:16 +08:00
milvus_benchmark
Bench scripts for 2.0 (#6263)
2021-07-02 11:40:16 +08:00
.gitignore
Bench scripts for 2.0 (#6263)
2021-07-02 11:40:16 +08:00
README.md
Bench scripts for 2.0 (#6263)
2021-07-02 11:40:16 +08:00
requirements.txt
Bench scripts for 2.0 (#6263)
2021-07-02 11:40:16 +08:00

README.md

Quick start

Description：

  • Test suites can be organized with yaml
  • Test can run with local mode or argo/jenkins mode, that manage the server env in argo/jenkins step or stages

Demos：

  1. Using argo pipeline： Run test suites(1.x, 2.x version) in argo workflows, innernal argo url: argo-test.zilliz.cc

  2. Local test： Run test with the local server

    1. set python path

      export PYTHONPATH=/yourmilvusprojectpath/tests/milvus_benchmark

    2. (optional, for sift/glove open dataset) mount NAS or update *_DATA_DIR in runner.py

      sudo mount -t cifs -o username=test,vers=1.0 //172.16.70.249/test /test

    3. run test

      cd milvus-benchmark/

      python3 main.py --local --host=*.* --port=19530 --suite=suites/2_insert_data.yaml

Definitions of test suites：

Testers need to write test suite config if adding a customized test into the current test framework

The following are the searching performance test suite：

  1. insert_search_performance: the test type，also we have:

    search_performance,build_performance,insert_performance,accuracy,stability,search_stability

  2. collections: list of test cases

  3. The following fields are in the collection field：

    • milvus: milvus config
    • collection_name: currently support one table
    • ni_per: per count of insert
    • index_type: index type
    • index_param: param of index
    • run_count: search count
    • search_params: params of search_vectors
    • top_ks: top_k of search
    • nqs: nq of search

Test result：

Test result will be uploaded, which will be used to tell if the test run pass or failed