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https://github.com/vale981/ray
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b5b11b2d06
Please review **e2e.py and test_suite belonging to your team**! This is the first part of https://docs.google.com/document/d/16IrwerYi2oJugnRf5hvzukgpJ6FAVEpB6stH_CiNMjY/edit# This PR adds a team name to each test suite. If the name is not specified, it will be reported as unspecified. If you are running a local test, and if the new test suite doesn't have a team name specified, it will raise an exception (in this way, we can avoid missing team names in the future). Note that we will aggregate all of test config into a single file, nightly_test.yaml.
66 lines
2.1 KiB
YAML
66 lines
2.1 KiB
YAML
#
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# Chaos tests.
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#
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# Run the test that invokes many tasks without object store usage.
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- name: chaos_many_tasks_no_object_store
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team: core
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cluster:
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app_config: chaos_test/app_config.yaml
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compute_template: chaos_test/compute_template.yaml
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run:
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timeout: 3600
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prepare: python wait_cluster.py 10 600; python setup_chaos.py --no-start
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script: python chaos_test/test_chaos_basic.py --workload=tasks
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- name: chaos_many_actors
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team: core
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cluster:
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app_config: chaos_test/app_config.yaml
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compute_template: chaos_test/compute_template.yaml
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run:
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timeout: 3600
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prepare: python wait_cluster.py 10 600; python setup_chaos.py --no-start
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script: python chaos_test/test_chaos_basic.py --workload=actors
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- name: chaos_dask_on_ray_large_scale_test_no_spilling
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team: core
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cluster:
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app_config: chaos_test/dask_on_ray_app_config_reconstruction.yaml
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compute_template: dask_on_ray/dask_on_ray_stress_compute.yaml
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run:
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timeout: 7200
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prepare: python wait_cluster.py 21 600
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script: python dask_on_ray/large_scale_test.py --num_workers 20 --worker_obj_store_size_in_gb 20 --error_rate 0 --data_save_path /tmp/ray
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stable: false
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# Test large scale dask on ray test with spilling.
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- name: chaos_dask_on_ray_large_scale_test_spilling
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team: core
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cluster:
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app_config: chaos_test/dask_on_ray_app_config_reconstruction.yaml
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compute_template: dask_on_ray/dask_on_ray_stress_compute.yaml
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run:
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timeout: 7200
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prepare: python wait_cluster.py 21 600
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script: python dask_on_ray/large_scale_test.py --num_workers 150 --worker_obj_store_size_in_gb 70 --error_rate 0 --data_save_path /tmp/ray
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stable: false
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- name: chaos_pipelined_ingestion_1500_gb_15_windows
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team: core
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cluster:
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app_config: dataset/pipelined_ingestion_app.yaml
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compute_template: dataset/pipelined_ingestion_compute.yaml
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run:
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timeout: 7200
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prepare: python wait_cluster.py 21 2400; python setup_chaos.py --node-kill-interval 300
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script: python dataset/pipelined_training.py --epochs 1 --num-windows 15 --num-files 915 --debug
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stable: false
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