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[ "/assign @connor-mccarthy ", "@rahuja23, I'm not sure I understand what you mean by optional flag. Can you explain? If possible, can you create a minimal reproducible example of the behavior you suspect is a bug?", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-21T12:42:50"

"2023-08-26T07:42:15"

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[ "@RansSelected, as a short term fix, I suggest you either (1) fork the component and change the code yourself or (2) modify the object in-memory to override the image tag.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-20T14:31:57"

"2023-08-26T07:42:17"

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[]

[ "Hi @anifort!\r\nTo resolve it, please upgrade the `kfp` package to 2.0.0-b12" ]

"2023-02-20T13:04:36"

"2023-02-24T00:00:28"

"2023-02-24T00:00:28"

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[]

[ "Any updates on this ?\r\n", "This is not planned for KFPv2. Instead of the above approach, you can use Scalar metrics https://www.kubeflow.org/docs/components/pipelines/v1/sdk/output-viewer/#scalar-metrics to achieve the same goal. You can define any amount of metrics with any value.", "I would very much support the integration of scalar metrics in the experimental overview table just as it was done in v1. If you optimize a perticular metrics it helps a lot to see it directly in the table. Especially because the metric comparison view is arranged horizontally which reduces the number of visible run greatly for a large number of runs." ]

"2023-02-20T07:23:45"

"2023-08-03T10:19:30"

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[ "@MatthewRalston: The label(s) `area/component` cannot be applied, because the repository doesn't have them.\n\n<details>\n\nIn response to [this](https://github.com/kubeflow/pipelines/issues/8868):\n\n>### Environment\r\n>\r\n>\r\n>Minikube v1.28.0\r\n>kubernetes 1.22.2\r\n>Kustomize v3.2.0\r\n>kubectl v1.25.5\r\n>Manifests v1.6.1\r\n>\r\n> KFP SDK version:\r\n>\r\n> All dependencies version:\r\n>\r\n>kfp 2.0.0b9\r\n>kfp-pipeline-spec 0.1.16\r\n>kfp-server-api 2.0.0a6\r\n>\r\n>### Steps to reproduce\r\n>\r\n>From arch Linux\r\n>\r\n>```bash\r\n>yay -S minikube docker containerd minio\r\n>```\r\n>\r\n>\r\n>\r\n>* `/etc/docker/daemon.json`\r\n>```json\r\n>{\r\n> \"exec-opts\": [\"native.cgroupdriver=systemd\"],\r\n> \"log-driver\": \"json-file\",\r\n> \"log-opts\": {\r\n>\t\"max-size\": \"100m\"\r\n> },\r\n> \"data-root\": \"/var/lib/docker\",\r\n> \"storage-driver\": \"overlay2\",\r\n> \"rootless\": false\r\n>}\r\n>```\r\n>\r\n>* Default configurations otherwise, except Minio service paths/users\r\n>\r\n>1. Launch minikube\r\n>2. Enable istio\r\n>3. `istioctl install --set revision=canary`\r\n>4. Use Kustomize to install Kubeflow 1.6 manifests\r\n>5. Port-fowarding \r\n>6. Use Kubeflow/pipelines dashboard to invoke a python kfp pipeline.\r\n>\r\n>\r\n>* `components/gunzip.yaml`\r\n>```yaml\r\n>name: gunzip\r\n>description: Gunzips an Input file to an Ouput filepath\r\n>inputs:\r\n>- {name: infile, type: String, description: 'Data for gzip decompression'}\r\n>outputs:\r\n>- {name: Output, type: String, description: 'Output decompressed plaintext'}\r\n>implementation:\r\n> container:\r\n> image: alpine:latest\r\n> # command is a list of strings (command-line arguments). \r\n> # The YAML language has two syntaxes for lists and you can use either of them. \r\n> # Here we use the \"flow syntax\" - comma-separated strings inside square brackets.\r\n> command: [\r\n> sh,\r\n> -c,\r\n> zcat,\r\n> {inputPath: infile},\r\n> '>',\r\n> {outputPath: Output}\r\n> ]\r\n>\r\n>```\r\n>\r\n>* `pipeline.py`\r\n>```python\r\n>#!/bin/env python\r\n>\r\n>import os\r\n>import sys\r\n>import argparse\r\n>\r\n>import kfp.dsl as dsl\r\n>import kfp.components as comp\r\n>import kfp\r\n>\r\n>\r\n>\r\n>import logging\r\n>global logger\r\n>logger = None\r\n>\r\n>def get_root_logger(level):\r\n> levels=[logging.WARNING, logging.INFO, logging.DEBUG]\r\n> if level < 0 or level > 2:\r\n> raise TypeError(\"{0}.get_root_logger expects a verbosity between 0-2\".format(__file__))\r\n> logging.basicConfig(level=levels[level], format=\"%(levelname)s: %(asctime)s %(funcName)s L%(lineno)s| %(message)s\", datefmt=\"%Y/%m/%d %I:%M:%S\")\r\n> root_logger = logging.getLogger()\r\n> return root_logger\r\n>\r\n>\r\n>\r\n>components_dir = os.path.join(os.path.dirname(__file__), \"components\")\r\n>\r\n>gunzip = comp.load_component_from_file(os.path.join(components_dir, \"gunzip.yaml\"))\r\n>echo = comp.load_component_from_file(os.path.join(components_dir, \"echo.yaml\"))\r\n>\r\n>is_unzip_needed = comp.load_component_from_file(os.path.join(components_dir, \"is_unzip_needed.yaml\"))\r\n>\r\n>\r\n>@dsl.pipeline(\r\n> name='kubeflow-barebone-demo',\r\n> description='kubeflow demo with minimal setup'\r\n>)\r\n>def rnaseq_pipeline(fastq1:str):\r\n> # Step 1: training component\r\n>\r\n> echo1 = echo(infile=fastq1).set_cpu_request('1').set_cpu_limit('1').set_memory_request('512Mi').set_memory_limit('512Mi')\r\n> #gunzip1 = gunzip(infile=fastq1).set_cpu_request('1').set_cpu_limit('1').set_memory_request('512Mi').set_memory_limit('512Mi')\r\n>\r\n>\r\n> \r\n>\r\n>if __name__ == \"__main__\":\r\n> logger = get_root_logger(2)\r\n> \r\n> kfp.compiler.Compiler().compile(rnaseq_pipeline, 'pipeline.yaml')\r\n>\r\n>```\r\n>\r\n>\r\n>\r\n>\r\n>\r\n>\r\n>\r\n>\r\n>### Expected result\r\n>\r\n>Expected behavior should be that Kubeflow + manifests handles the creation of output `tmp` directories. I did not get an appropriate answer from [issue](https://github.com/kubeflow/pipelines/issues/8782). Either the requirement for users to create their own directories (as @chensun suggested) should be a documented *feature* of Kubeflow, or the correct way to handle file outputs with MinIO should be well documented. I'm a fairly tech savvy average user of Kubeflow, and with about 8+ hours in the documentation, I'm running into a crippling bug for my small business. Namely, the correct way to pass data from one step to antother, saving the output in the `/tmp/Output/output` directory. If that's where Kubeflow wants to put output datasets:\r\n>\r\n>* why can't it also manage the creation of such a directory?\r\n>* Is this a kubeflow or manifests issue?\r\n>* What would be the proper way to produce/retrieve kfp outputs using 1.8 kfp syntax?\r\n>\r\n>### Materials and reference\r\n>\r\n>\r\n>\r\n>\r\n>### Labels\r\n>\r\n>\r\n>\r\n>/area backend\r\n>/area sdk\r\n>/area testing\r\n>\r\n>/area component\r\n>\r\n>---\r\n>\r\n>\r\n>Impacted by this bug? Give it a 👍. \n\n\nInstructions for interacting with me using PR comments are available [here](https://git.k8s.io/community/contributors/guide/pull-requests.md). If you have questions or suggestions related to my behavior, please file an issue against the [kubernetes/test-infra](https://github.com/kubernetes/test-infra/issues/new?title=Prow%20issue:) repository.\n</details>", "> Either the requirement for users to create their own directories (as @chensun suggested) should be a documented feature of Kubeflow, or the correct way to handle file outputs with MinIO should be well documented.\r\n\r\nAgree that we could have done a better job on documentation, but the need of `mkdir` was indeed show cased in the [documentation](https://www.kubeflow.org/docs/components/pipelines/v1/sdk/component-development/) as well as [numerous component samples](https://github.com/kubeflow/pipelines/search?q=%22mkdir+-p%22).\r\n(Note: above is for KFP v1, v2 has a different syntax I'll explain shortly)\r\n\r\n> why can't it also manage the creation of such a directory?\r\n\r\nThis is by design for KFP v1, while I don't know the full history or limitation, my understanding is a component that runs as a container is fully responsible for the file i/o happened within the container, the orchestration engine (Argo) only picks up artifacts and persists them in object store (Minio) post execution. \r\n\r\n> Is this a kubeflow or manifests issue?\r\n\r\nNeither, (as explained above)\r\n\r\n> What would be the proper way to produce/retrieve kfp outputs using 1.8 kfp syntax?\r\n\r\nAssuming you refer to KFP SDK 1.8 and import from `kfp` namespace (instead of `kfp.v2` namespace), user code needs to make directories of output paths. \r\nIf you're importing from `kfp.v2` namespace in KFP SDK 1.8, or if you are using KFP SDK 2.0, for Python-function component (created via `@component` decorator), you don't need to make directories--that's handled by our injected executor code that runs in the same container prior to the execution of user code. For more details about v2 syntax, please check: https://www.kubeflow.org/docs/components/pipelines/v2/author-a-pipeline/component-io/\r\n\r\nHope this clarifies.", "Thank you, this clarifies quite a bit. I will visit this during the week and close if I cannot manage the syntax issues between v1.8 (which I am using) or the v2 SDK.", "First of all @chensun , I noticed that the documentation needs revision. Here is my minimal example:\r\n\r\n\r\nhttps://www.kubeflow.org/docs/components/pipelines/v1/sdk/component-development/\r\nStraight from the documentation:\r\n\r\n```\r\ndef gunzip_func(ifile, ofile):\r\n for line in ifile:\r\n ofile.write(line)\r\n\r\n logger.info(\"Decompression completed...\")\r\n\r\n return\r\n\r\n\r\n\r\n\r\n\r\n@dsl.pipeline(\r\n name='kubeflow-barebone-demo',\r\n description='kubeflow demo with minimal setup'\r\n)\r\ndef rnaseq_pipeline(fastq1:str, decompressed_fastq1:str):\r\n Path(str(decompressed_fastq1)).parent.mkdir(parents=True, exist_ok=True)\r\n\r\n\r\n with gzip.open(fastq1) as ifile:\r\n with open(decompressed_fastq1, 'w') as ofile:\r\n gunzip_func(ifile, ofile)\r\n\r\nif __name__ == \"__main__\":\r\n logger = get_root_logger(2)\r\n \r\n kfp.compiler.Compiler().compile(rnaseq_pipeline, 'pipeline.yaml')\r\n\r\n```\r\n\r\n\r\n\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"./pipeline.py\", line 73, in <module>\r\n kfp.compiler.Compiler().compile(rnaseq_pipeline, 'pipeline.yaml')\r\n File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/site-packages/kfp/compiler/compiler.py\", line 1178, in compile\r\n package_path=package_path)\r\n File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/site-packages/kfp/compiler/compiler.py\", line 1229, in _create_and_write_workflow\r\n pipeline_conf)\r\n File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/site-packages/kfp/compiler/compiler.py\", line 1005, in _create_workflow\r\n pipeline_func(*args_list, **kwargs_dict)\r\n File \"./pipeline.py\", line 62, in rnaseq_pipeline\r\n with gzip.open(fastq1) as ifile:\r\n File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/gzip.py\", line 57, in open\r\n raise TypeError(\"filename must be a str or bytes object, or a file\")\r\nTypeError: filename must be a str or bytes object, or a file\r\n```\r\n\r\n\r\n", "It seems like the example produces a wrapper (PipelineParam), which I'm assuming implements its own `open` interface). This is not compatible with gzip. No matter what I try, I cannot use either Python or the following container interface to decompress a file. \r\n\r\n```yaml\r\nname: gunzip\r\ndescription: Gunzips an Input file to an Ouput filepath\r\ninputs:\r\n- {name: infile, type: String, description: 'Data for gzip decompression'}\r\noutputs:\r\n- {name: Output, type: String, description: 'Output decompressed plaintext'}\r\nimplementation:\r\n container:\r\n image: alpine:latest\r\n # command is a list of strings (command-line arguments). \r\n # The YAML language has two syntaxes for lists and you can use either of them. \r\n # Here we use the \"flow syntax\" - comma-separated strings inside square brackets.\r\n command: [\r\n sh,\r\n -c,\r\n mkdir,\r\n --parents,\r\n '$(dirname ',\r\n {outputPath: Output},\r\n ')',\r\n '&&',\r\n zcat,\r\n {inputPath: infile},\r\n '>',\r\n {outputPath: Output}\r\n ]\r\n```\r\n\r\n\r\nAGAIN the real issue is that kfp, as you stated above, requires the following directory to be created *INDEPENEDENTLY OF THE DATASET HANDLING*. It's a smell.\r\n\r\n```\r\n/tmp/outputs/Output/\r\n```\r\n\r\nAs you can see, the directory should be created in the container code above, but it fails with the following:\r\n\r\n```\r\ntime=\"2023-03-01T14:41:04.951Z\" level=error msg=\"cannot save artifact /tmp/outputs/Output/data\" argo=true error=\"stat /tmp/outputs/Output/data: no such file or directory\"\r\n```\r\n\r\nInstead it fails *before* the zcat command on the mkdir command. THe mkdir command :\r\n\r\n\r\n```yaml\r\n 'mkdir -p $(dirname ',\r\n {outputPath: Output}\r\n ')'\r\n```\r\n\r\n\r\nHere is the containerspec from the logs\r\n```\r\n {\"description\": \"Gunzips an Input file to an Ouput filepath\",\r\n \"implementation\": {\"container\": {\"command\": [\"sh\", \"-c\", \"echo 'mkdir\r\n --parents \\\\$(dirname $output) && zcat $input '\", {\"outputPath\":\r\n \"Output\"}, \"&&\", \"mkdir --parents $(dirname \", {\"outputPath\": \"Output\"},\r\n \")\", \"&&\", \"zcat\", {\"inputPath\": \"infile\"}, \">\", {\"outputPath\":\r\n \"Output\"}], \"image\": \"alpine:latest\"}}, \"inputs\": [{\"description\": \"Data\r\n for gzip decompression\", \"name\": \"infile\", \"type\": \"String\"}], \"name\":\r\n \"gunzip\", \"outputs\": [{\"description\": \"Output decompressed plaintext\",\r\n \"name\": \"Output\", \"type\": \"String\"}]}\r\n```", "[Full script] (https://gist.github.com/MatthewRalston/b6049e34812d36cfa554036f05ae1d3b)", "Is this related to the jsonification of the command into a shell command?", "@chensun is there anything else I can do here? Do I need to instantiate my own volume or something?", "> First of all @chensun , I noticed that the documentation needs revision. Here is my minimal example:\r\n> \r\n> https://www.kubeflow.org/docs/components/pipelines/v1/sdk/component-development/ Straight from the documentation:\r\n> \r\n> ```\r\n> def gunzip_func(ifile, ofile):\r\n> for line in ifile:\r\n> ofile.write(line)\r\n> \r\n> logger.info(\"Decompression completed...\")\r\n> \r\n> return\r\n> \r\n> \r\n> \r\n> \r\n> \r\n> @dsl.pipeline(\r\n> name='kubeflow-barebone-demo',\r\n> description='kubeflow demo with minimal setup'\r\n> )\r\n> def rnaseq_pipeline(fastq1:str, decompressed_fastq1:str):\r\n> Path(str(decompressed_fastq1)).parent.mkdir(parents=True, exist_ok=True)\r\n> \r\n> \r\n> with gzip.open(fastq1) as ifile:\r\n> with open(decompressed_fastq1, 'w') as ofile:\r\n> gunzip_func(ifile, ofile)\r\n> \r\n> if __name__ == \"__main__\":\r\n> logger = get_root_logger(2)\r\n> \r\n> kfp.compiler.Compiler().compile(rnaseq_pipeline, 'pipeline.yaml')\r\n> ```\r\n> \r\n> ```\r\n> Traceback (most recent call last):\r\n> File \"./pipeline.py\", line 73, in <module>\r\n> kfp.compiler.Compiler().compile(rnaseq_pipeline, 'pipeline.yaml')\r\n> File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/site-packages/kfp/compiler/compiler.py\", line 1178, in compile\r\n> package_path=package_path)\r\n> File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/site-packages/kfp/compiler/compiler.py\", line 1229, in _create_and_write_workflow\r\n> pipeline_conf)\r\n> File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/site-packages/kfp/compiler/compiler.py\", line 1005, in _create_workflow\r\n> pipeline_func(*args_list, **kwargs_dict)\r\n> File \"./pipeline.py\", line 62, in rnaseq_pipeline\r\n> with gzip.open(fastq1) as ifile:\r\n> File \"/home/matt/.pyenv/versions/miniconda3-4.7.12/lib/python3.7/gzip.py\", line 57, in open\r\n> raise TypeError(\"filename must be a str or bytes object, or a file\")\r\n> TypeError: filename must be a str or bytes object, or a file\r\n> ```\r\n\r\nPlease go through the documentation you referenced again. This code is not straight from the doc, and you missed a key point that a component is a containerized app and a basic building block for pipelines. A pipeline may consists of only components and kfp.dsl syntax, but not arbitrary Python code like you had. Those Python code would be executed at compilation time, while the pipeline and components are meant to be executed at pipeline runtime (when submitted to the backend system).", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-19T03:53:47"

"2023-08-26T07:42:19"

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-18T00:19:10"

"2023-08-26T07:42:21"

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[ "Any updates on this ?", "/cc @connor-mccarthy to investigate more.", "/assign @chensun ", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-17T07:07:00"

"2023-08-26T07:42:23"

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-15T19:28:56"

"2023-08-26T07:42:26"

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{ "url": "https://api.github.com/repos/kubeflow/pipelines/milestones/8", "html_url": "https://github.com/kubeflow/pipelines/milestone/8", "labels_url": "https://api.github.com/repos/kubeflow/pipelines/milestones/8/labels", "id": 9154572, "node_id": "MI_kwDOB-71UM4Ai7AM", "number": 8, "title": "KFP 2.0.0-beta.2", "description": null, "creator": { "login": "chensun", "id": 2043310, "node_id": "MDQ6VXNlcjIwNDMzMTA=", "avatar_url": "https://avatars.githubusercontent.com/u/2043310?v=4", "gravatar_id": "", "url": "https://api.github.com/users/chensun", "html_url": "https://github.com/chensun", "followers_url": "https://api.github.com/users/chensun/followers", "following_url": "https://api.github.com/users/chensun/following{/other_user}", "gists_url": "https://api.github.com/users/chensun/gists{/gist_id}", "starred_url": "https://api.github.com/users/chensun/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/chensun/subscriptions", "organizations_url": "https://api.github.com/users/chensun/orgs", "repos_url": "https://api.github.com/users/chensun/repos", "events_url": "https://api.github.com/users/chensun/events{/privacy}", "received_events_url": "https://api.github.com/users/chensun/received_events", "type": "User", "site_admin": false }, "open_issues": 0, "closed_issues": 13, "state": "open", "created_at": "2023-03-13T20:54:38", "updated_at": "2023-06-06T17:36:22", "due_on": null, "closed_at": null }

[ "Same Issue on listing kubeflow pipelines thought UI. I was forced to update to 2.0.0-beta.0 because of AWS S3 IRSA support introduced in this update but now I'm totally blocked by this issue", "I had the listing issue as well, I guess that for this the fix will come eventually from manifests, but I could fix it with creating a cluster role binding like this:\r\n```shell\r\nkubectl create clusterrolebinding my-kubeflow-pipelines-edit --clusterrole=kubeflow-pipelines-edit --user=user@example.com\r\n```\r\nCluster-role `kubeflow-pipelines-edit` is already there from manifests (I guess `kubeflow-pipelines-view`) would suffice.", "I solved it for now by downgrading back to alpha.6. But thanks for the great idea!", "@gkcalat Looks like this bug was introduced by https://github.com/kubeflow/pipelines/pull/8633 PR. Can you look on it?", "> I had the listing issue as well, I guess that for this the fix will come eventually from manifests, but I could fix it with creating a cluster role binding like this:\r\n> \r\n> ```shell\r\n> kubectl create clusterrolebinding my-kubeflow-pipelines-edit --clusterrole=kubeflow-pipelines-edit --user=user@example.com\r\n> ```\r\n> \r\n> Cluster-role `kubeflow-pipelines-edit` is already there from manifests (I guess `kubeflow-pipelines-view`) would suffice.\r\n\r\nThat didn't work for me", "> @gkcalat Looks like this bug was introduced by #8633 PR. Can you look on it?\r\n\r\n@sergeyshevch, thanks for pointing this out. This change has been reverted and the fix will be included in the next 2.0.0-beta.2 release, which is going to happen by the end of this week. This particular issue, however, seems to be unrelated.\r\n\r\n@b4sus, @amybachir , the original error suggests that `user@example.com` doesn't have access to `kubeflow-user-example-com`. Perhaps, you were running a default sample (the provided link is broken) as these names are used as default placeholders? \r\n\r\nIn full Kubeflow (multi-user) mode, KFP assumes that a user has access to a k8s namespace. It is created when you open the dashboard UI for the first time. For example, creating a run sends a POST request to the backend with authentication header that carries information required to authorize.\r\n\r\nPlease, test out the next release and reopen this issue if it persists. Thank you!", "Tested on beta.2 - issue still happens - PR submitted #9365 " ]

"2023-02-15T13:50:33"

"2023-05-09T06:28:32"

"2023-05-04T23:53:27"

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[ "This has been fixed by #8850 and #8926. Reopen it if you encounter the same issue.\r\n\r\n/CC @chensun " ]

"2023-02-15T03:30:46"

"2023-03-10T00:27:49"

"2023-03-10T00:27:49"

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[ "Closed and see more info at #9859" ]

"2023-02-15T03:06:56"

"2023-08-28T20:57:30"

"2023-08-28T20:57:29"

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[]

"2023-02-15T02:42:34"

"2023-04-27T20:21:03"

"2023-04-27T20:21:03"

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[ "fixed by #8860 " ]

"2023-02-13T19:22:46"

"2023-02-24T20:35:12"

"2023-02-24T20:35:12"

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[]

"2023-02-13T19:17:31"

"2023-02-16T21:22:42"

"2023-02-16T21:22:42"

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[ "Hi @ReggieCarey!\r\n\r\nCould you please check if you can retrieve logs from the `mysql` pod?", "The same issue, mysql pod logs\r\n```\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:17.569Z] \"- - -\" 0 - - - \"-\" 10362 21332 29 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:58857 10.128.48.144:3306 10.128.47.216:47612 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:17.813Z] \"- - -\" 0 - - - \"-\" 15446 357776 36 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:35527 10.128.48.144:3306 10.128.47.216:47628 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.161Z] \"- - -\" 0 - - - \"-\" 8378 17469 33 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:48867 10.128.48.144:3306 10.128.47.216:47672 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.160Z] \"- - -\" 0 - - - \"-\" 8378 17469 34 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:43887 10.128.48.144:3306 10.128.47.216:47638 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.162Z] \"- - -\" 0 - - - \"-\" 8378 17470 33 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:54319 10.128.48.144:3306 10.128.47.216:47680 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.160Z] \"- - -\" 0 - - - \"-\" 8378 17469 35 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:60221 10.128.48.144:3306 10.128.47.216:47658 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.160Z] \"- - -\" 0 - - - \"-\" 8378 17469 36 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:57623 10.128.48.144:3306 10.128.47.216:47644 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.690Z] \"- - -\" 0 - - - \"-\" 864 773 12 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:55705 10.128.48.144:3306 10.128.47.216:49048 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.688Z] \"- - -\" 0 - - - \"-\" 864 773 21 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:51761 10.128.48.144:3306 10.128.47.216:49032 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.695Z] \"- - -\" 0 - - - \"-\" 864 773 14 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:42689 10.128.48.144:3306 10.128.47.216:49092 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.695Z] \"- - -\" 0 - - - \"-\" 864 773 19 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:39661 10.128.48.144:3306 10.128.47.216:49084 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.694Z] \"- - -\" 0 - - - \"-\" 864 773 20 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:56179 10.128.48.144:3306 10.128.47.216:49062 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.704Z] \"- - -\" 0 - - - \"-\" 864 773 18 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:35125 10.128.48.144:3306 10.128.47.216:49118 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.704Z] \"- - -\" 0 - - - \"-\" 864 773 19 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:54089 10.128.48.144:3306 10.128.47.216:49108 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.704Z] \"- - -\" 0 - - - \"-\" 864 773 21 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:45305 10.128.48.144:3306 10.128.47.216:49146 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.705Z] \"- - -\" 0 - - - \"-\" 864 773 20 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:36357 10.128.48.144:3306 10.128.47.216:49154 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:19.704Z] \"- - -\" 0 - - - \"-\" 864 773 21 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:60551 10.128.48.144:3306 10.128.47.216:49134 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\n....\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:20.953Z] \"- - -\" 0 - - - \"-\" 8382 17477 505 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:51587 10.128.48.144:3306 10.128.47.216:41668 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:20.870Z] \"- - -\" 0 - - - \"-\" 8382 17474 589 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:54417 10.128.48.144:3306 10.128.47.216:41438 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:20.896Z] \"- - -\" 0 - - - \"-\" 8382 17477 564 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:44675 10.128.48.144:3306 10.128.47.216:41454 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:20.936Z] \"- - -\" 0 - - - \"-\" 8392 17582 524 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:41235 10.128.48.144:3306 10.128.47.216:41594 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:21.027Z] \"- - -\" 0 - - - \"-\" 8382 17477 434 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:35769 10.128.48.144:3306 10.128.47.216:41950 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:21.048Z] \"- - -\" 0 - - - \"-\" 8382 17477 414 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:49419 10.128.48.144:3306 10.128.47.216:42024 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:21.067Z] \"- - -\" 0 - - - \"-\" 8382 17477 395 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:39513 10.128.48.144:3306 10.128.47.216:42086 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\nmysql-55778745b6-lcl8q istio-proxy [2023-02-24T07:15:21.097Z] \"- - -\" 0 - - - \"-\" 8382 17477 368 - \"-\" \"-\" \"-\" \"-\" \"10.128.48.144:3306\" inbound|3306|| 127.0.0.6:40717 10.128.48.144:3306 10.128.47.216:42164 outbound_.3306_._.mysql.kubeflow.svc.cluster.local -\r\n```\r\n\r\nmysql container does't display logs\r\n\r\nAlso tried restarting `metadata-grpc-deployment`.\r\n\r\nIn mysql I was able to get a list of tables. \r\n```\r\n❯ kubectl -it exec mysql-55778745b6-lcl8q -- mysql -D metadb -u root \r\n\r\nType 'help;' or '\\h' for help. Type '\\c' to clear the current input statement.\r\n\r\nmysql> show tables;\r\n+-------------------+\r\n| Tables_in_metadb |\r\n+-------------------+\r\n| Artifact |\r\n| ArtifactProperty |\r\n| Association |\r\n| Attribution |\r\n| Context |\r\n| ContextProperty |\r\n| Event |\r\n| EventPath |\r\n| Execution |\r\n| ExecutionProperty |\r\n| MLMDEnv |\r\n| ParentContext |\r\n| ParentType |\r\n| Type |\r\n| TypeProperty |\r\n+-------------------+\r\n15 rows in set (0.00 sec)\r\n```\r\n\r\nIt's like there is no problem here. \r\n\r\nThe problem seems to be the same as in [#6579](https://github.com/kubeflow/kubeflow/issues/6579) issue\r\n\r\n\r\nUPD: I tried changing mysql `max_connections` to 500 from default 151 and it actually worked. ", "Here is my mysql log\r\n```\r\n2023-03-08 15:43:23+00:00 [Note] [Entrypoint]: Entrypoint script for MySQL Server 5.7.38-1debian10 started.\r\n2023-03-08 15:43:23+00:00 [Note] [Entrypoint]: Switching to dedicated user 'mysql'\r\n2023-03-08 15:43:23+00:00 [Note] [Entrypoint]: Entrypoint script for MySQL Server 5.7.38-1debian10 started.\r\n2023-03-08T15:43:23.923581Z 0 [Warning] TIMESTAMP with implicit DEFAULT value is deprecated. Please use --explicit_defaults_for_timestamp server option (see documentation for more details).\r\n2023-03-08T15:43:23.924540Z 0 [Note] mysqld (mysqld 5.7.38) starting as process 1 ...\r\n2023-03-08T15:43:23.926535Z 0 [Note] InnoDB: PUNCH HOLE support available\r\n2023-03-08T15:43:23.926547Z 0 [Note] InnoDB: Mutexes and rw_locks use GCC atomic builtins\r\n2023-03-08T15:43:23.926550Z 0 [Note] InnoDB: Uses event mutexes\r\n2023-03-08T15:43:23.926552Z 0 [Note] InnoDB: GCC builtin __atomic_thread_fence() is used for memory barrier\r\n2023-03-08T15:43:23.926554Z 0 [Note] InnoDB: Compressed tables use zlib 1.2.11\r\n2023-03-08T15:43:23.926556Z 0 [Note] InnoDB: Using Linux native AIO\r\n2023-03-08T15:43:23.926708Z 0 [Note] InnoDB: Number of pools: 1\r\n2023-03-08T15:43:23.926784Z 0 [Note] InnoDB: Using CPU crc32 instructions\r\n2023-03-08T15:43:23.927965Z 0 [Note] InnoDB: Initializing buffer pool, total size = 128M, instances = 1, chunk size = 128M\r\n2023-03-08T15:43:23.933643Z 0 [Note] InnoDB: Completed initialization of buffer pool\r\n2023-03-08T15:43:23.935098Z 0 [Note] InnoDB: If the mysqld execution user is authorized, page cleaner thread priority can be changed. See the man page of setpriority().\r\n2023-03-08T15:43:24.237371Z 0 [Note] InnoDB: Highest supported file format is Barracuda.\r\n2023-03-08T15:43:25.502228Z 0 [Note] InnoDB: Creating shared tablespace for temporary tables\r\n2023-03-08T15:43:25.502284Z 0 [Note] InnoDB: Setting file './ibtmp1' size to 12 MB. Physically writing the file full; Please wait ...\r\n2023-03-08T15:43:27.549138Z 0 [Note] InnoDB: File './ibtmp1' size is now 12 MB.\r\n2023-03-08T15:43:27.550178Z 0 [Note] InnoDB: 96 redo rollback segment(s) found. 96 redo rollback segment(s) are active.\r\n2023-03-08T15:43:27.550190Z 0 [Note] InnoDB: 32 non-redo rollback segment(s) are active.\r\n2023-03-08T15:43:27.550786Z 0 [Note] InnoDB: 5.7.38 started; log sequence number 83960348\r\n2023-03-08T15:43:27.550999Z 0 [Note] InnoDB: Loading buffer pool(s) from /var/lib/mysql/ib_buffer_pool\r\n2023-03-08T15:43:27.551183Z 0 [Note] Plugin 'FEDERATED' is disabled.\r\n2023-03-08T15:43:28.212446Z 0 [Note] Found ca.pem, server-cert.pem and server-key.pem in data directory. Trying to enable SSL support using them.\r\n2023-03-08T15:43:28.212476Z 0 [Note] Skipping generation of SSL certificates as certificate files are present in data directory.\r\n2023-03-08T15:43:28.212482Z 0 [Warning] A deprecated TLS version TLSv1 is enabled. Please use TLSv1.2 or higher.\r\n2023-03-08T15:43:28.212486Z 0 [Warning] A deprecated TLS version TLSv1.1 is enabled. Please use TLSv1.2 or higher.\r\n2023-03-08T15:43:28.296561Z 0 [Warning] CA certificate ca.pem is self signed.\r\n2023-03-08T15:43:28.296641Z 0 [Note] Skipping generation of RSA key pair as key files are present in data directory.\r\n2023-03-08T15:43:28.314437Z 0 [Note] Server hostname (bind-address): '*'; port: 3306\r\n2023-03-08T15:43:28.314669Z 0 [Note] IPv6 is available.\r\n2023-03-08T15:43:28.314692Z 0 [Note] - '::' resolves to '::';\r\n2023-03-08T15:43:28.314725Z 0 [Note] Server socket created on IP: '::'.\r\n2023-03-08T15:43:28.316528Z 0 [Warning] Insecure configuration for --pid-file: Location '/var/run/mysqld' in the path is accessible to all OS users. Consider choosing a different directory.\r\n2023-03-08T15:43:28.934090Z 0 [Note] InnoDB: Buffer pool(s) load completed at 230308 15:43:28\r\n2023-03-08T15:43:30.118955Z 0 [Note] Event Scheduler: Loaded 0 events\r\n2023-03-08T15:43:30.119247Z 0 [Note] mysqld: ready for connections.\r\nVersion: '5.7.38' socket: '/var/run/mysqld/mysqld.sock' port: 3306 MySQL Community Server (GPL)\r\n```\r\nHere's the logs from metadata-grpc-deployment:\r\n```\r\nWARNING: Logging before InitGoogleLogging() is written to STDERR\r\nI0308 15:44:01.511389 1 metadata_store_server_main.cc:258] Server listening on 0.0.0.0:8080\r\nW0308 15:45:10.351994 177 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.352021 118 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.352051 185 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.352072 111 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.352154 149 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.352870 188 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.353062 105 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.353082 158 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.361578 99 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.362709 164 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.363934 117 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\nW0308 15:45:10.364862 113 metadata_store_service_impl.cc:432] Failed to connect to the database: mysql_real_connect failed: errno: , error: \r\n```\r\nThis is after restarting both deployments and then asking for artifacts in the UI", "So apparently the following block of code is where the error is reported in ml-metadata from google: https://github.com/google/ml-metadata/blob/418ecea406e540fd10b558197b7fe2fefd2e1033/ml_metadata/metadata_store/metadata_store_service_impl.cc\r\n\r\n```\r\n::grpc::Status MetadataStoreServiceImpl::GetEventsByArtifactIDs(\r\n ::grpc::ServerContext* context,\r\n const GetEventsByArtifactIDsRequest* request,\r\n GetEventsByArtifactIDsResponse* response) {\r\n std::unique_ptr<MetadataStore> metadata_store;\r\n const ::grpc::Status connection_status =\r\n ConnectMetadataStore(connection_config_, &metadata_store);\r\n if (!connection_status.ok()) {\r\n LOG(WARNING) << \"Failed to connect to the database: \"\r\n << connection_status.error_message();\r\n return connection_status;\r\n }\r\n const ::grpc::Status transaction_status =\r\n ToGRPCStatus(metadata_store->GetEventsByArtifactIDs(*request, response));\r\n if (!transaction_status.ok()) {\r\n LOG(WARNING) << \"GetEventsByArtifactIDs failed: \"\r\n << transaction_status.error_message();\r\n }\r\n return transaction_status;\r\n}\r\n```\r\n\r\nThis references ConnectMetadataStore function:\r\n```\r\n// Converts from absl Status to GRPC Status.\r\n::grpc::Status ToGRPCStatus(const ::absl::Status& status) {\r\n // Note: the absl and grpc status codes align with each other.\r\n return ::grpc::Status(static_cast<::grpc::StatusCode>(status.code()),\r\n std::string(status.message()));\r\n}\r\n\r\n// Creates a store on demand. The store created does not handle migration.\r\n::grpc::Status ConnectMetadataStore(\r\n const ConnectionConfig& connection_config,\r\n std::unique_ptr<MetadataStore>* metadata_store) {\r\n return ToGRPCStatus(CreateMetadataStore(connection_config, metadata_store));\r\n}\r\n```\r\n\r\nThis leads to the code:\r\n```\r\nabsl::Status CreateMetadataStore(const ConnectionConfig& config,\r\n const MigrationOptions& options,\r\n std::unique_ptr<MetadataStore>* result) {\r\n switch (config.config_case()) {\r\n case ConnectionConfig::CONFIG_NOT_SET:\r\n // TODO(b/123345695): make this longer when that bug is resolved.\r\n // Must specify a metadata store type.\r\n return absl::InvalidArgumentError(\"Unset\");\r\n case ConnectionConfig::kFakeDatabase:\r\n // Creates an in-memory SQLite database for testing.\r\n return CreateSqliteMetadataStore(SqliteMetadataSourceConfig(), options,\r\n result);\r\n case ConnectionConfig::kMysql:\r\n return CreateMySQLMetadataStore(config.mysql(), options, result);\r\n case ConnectionConfig::kSqlite:\r\n return CreateSqliteMetadataStore(config.sqlite(), options, result);\r\n default:\r\n return absl::UnimplementedError(\"Unknown database type.\");\r\n }\r\n}\r\n\r\nabsl::Status CreateMetadataStore(const ConnectionConfig& config,\r\n std::unique_ptr<MetadataStore>* result) {\r\n return CreateMetadataStore(config, {}, result);\r\n}\r\n```\r\n\r\nAnd the CreateMySQLMetadataStore() function\r\n```\r\n#ifndef _WIN32\r\nabsl::Status CreateMySQLMetadataStore(const MySQLDatabaseConfig& config,\r\n const MigrationOptions& migration_options,\r\n std::unique_ptr<MetadataStore>* result) {\r\n auto metadata_source = std::make_unique<MySqlMetadataSource>(config);\r\n auto transaction_executor =\r\n std::make_unique<RdbmsTransactionExecutor>(metadata_source.get());\r\n MLMD_RETURN_IF_ERROR(MetadataStore::Create(\r\n util::GetMySqlMetadataSourceQueryConfig(), migration_options,\r\n std::move(metadata_source), std::move(transaction_executor), result));\r\n return (*result)->InitMetadataStoreIfNotExists(\r\n migration_options.enable_upgrade_migration());\r\n}\r\n#else\r\nabsl::Status CreateMySQLMetadataStore(\r\n const MySQLDatabaseConfig& config,\r\n const MigrationOptions& migration_options,\r\n std::unique_ptr<MetadataStore>* result) {\r\n return absl::UnimplementedError(\r\n \"MySQL is not supported in Windows yet\");\r\n}\r\n#endif\r\n```\r\n\r\nSo, is the problem in the call to std::make_unique(), or MLMD_RETURN_IF_ERROR(MetadataStore::Create()) or in the reutrn (*result)->InitMetadataStoreIfNotExists(). \r\n\r\nIt appears that since the database already exists, the likely culprit is produced from this snippet of code:\r\n```\r\nMLMD_RETURN_IF_ERROR(MetadataStore::Create(\r\n util::GetMySqlMetadataSourceQueryConfig(), migration_options,\r\n std::move(metadata_source), std::move(transaction_executor), result));\r\n```\r\n\r\nThis feels like a rabbit hole. \r\n\r\nThe one thing I do notice is that in the Kubeflow out of the box configuration (kf 1.6.0 deployed via manifests) is the lack of password associated with the root user for MySQL (EnvVar: DBCONFIG_PASSWORD is blank)\r\n\r\nThe command to launch this metadata_grpc_deployment is apparently:\r\n\r\n```\r\n/bin/metadata_store_server --grpc_port=8080 --mysql_config_database=$(MYSQL_DATABASE) --mysql_config_host=$(MYSQL_HOST) --mysql_config_port=$(MYSQL_PORT) --mysql_config_user=$(DBCONFIG_USER) --mysql_config_password=$(DBCONFIG_PASSWORD) --enable_database_upgrade=true\r\n```\r\n\r\nA view of the isto-proxy for the metadata-grpc-deployment shows that when a request is made in the UI to request the artifacts, many many many connections to MySQL are reported all within 1-2 seconds.\r\n\r\n```\r\n2023-03-08T19:28:20.328466Z\tinfo\tReadiness succeeded in 1.669092606s\r\n2023-03-08T19:28:20.329170Z\tinfo\tEnvoy proxy is ready\r\n[2023-03-08T19:29:47.239Z] \"POST /ml_metadata.MetadataStoreService/GetArtifactTypes HTTP/2\" 200 - via_upstream - \"-\" 5 151 43 42 \"100.64.0.2\" \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36\" \"f7c9bf1b-81fc-97a2-b5ab-6df0b7a168a2\" \"kf.example.com\" \"172.25.90.90:8080\" inbound|8080|| 127.0.0.6:34643 172.25.90.90:8080 100.64.0.2:0 - default\r\n[2023-03-08T19:29:47.244Z] \"- - -\" 0 - - - \"-\" 11214 24350 39 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:38642 172.25.58.141:3306 172.25.90.90:39440 - -\r\n[2023-03-08T19:29:47.456Z] \"- - -\" 0 - - - \"-\" 9702 129705 32 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:38658 172.25.58.141:3306 172.25.90.90:39450 - -\r\n[2023-03-08T19:29:47.439Z] \"POST /ml_metadata.MetadataStoreService/GetArtifacts HTTP/2\" 200 - via_upstream - \"-\" 5 102319 49 48 \"100.64.0.2\" \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36\" \"a55d4e72-669a-950a-b7de-17e5d6681129\" \"kf.example.com\" \"172.25.90.90:8080\" inbound|8080|| 127.0.0.6:34643 172.25.90.90:8080 100.64.0.2:0 - default\r\n[2023-03-08T19:29:47.658Z] \"POST /ml_metadata.MetadataStoreService/GetEventsByArtifactIDs HTTP/2\" 200 - via_upstream - \"-\" 7 62 25 25 \"100.64.0.2\" \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36\" \"8a9c1bdf-9d17-9e0b-bc51-5ef1891fbe1a\" \"kf.example.com\" \"172.25.90.90:8080\" inbound|8080|| 127.0.0.6:34643 172.25.90.90:8080 100.64.0.2:0 - default\r\n[2023-03-08T19:29:47.662Z] \"- - -\" 0 - - - \"-\" 7517 16947 22 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:38662 172.25.58.141:3306 172.25.90.90:39458 - -\r\n[2023-03-08T19:29:47.961Z] \"- - -\" 0 - - - \"-\" 0 27 46 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40150 172.25.58.141:3306 172.25.90.90:41036 - -\r\n[2023-03-08T19:29:47.961Z] \"- - -\" 0 - - - \"-\" 0 27 46 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40184 172.25.58.141:3306 172.25.90.90:41060 - -\r\n[2023-03-08T19:29:47.961Z] \"- - -\" 0 - - - \"-\" 0 27 46 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40196 172.25.58.141:3306 172.25.90.90:41076 - -\r\n[2023-03-08T19:29:47.962Z] \"- - -\" 0 - - - \"-\" 0 27 46 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40272 172.25.58.141:3306 172.25.90.90:41158 - -\r\n[2023-03-08T19:29:47.962Z] \"- - -\" 0 - - - \"-\" 0 27 46 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40280 172.25.58.141:3306 172.25.90.90:41174 - -\r\n[2023-03-08T19:29:47.962Z] \"- - -\" 0 - - - \"-\" 0 27 47 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40264 172.25.58.141:3306 172.25.90.90:41078 - -\r\n[2023-03-08T19:29:47.962Z] \"- - -\" 0 - - - \"-\" 0 27 47 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40238 172.25.58.141:3306 172.25.90.90:41124 - -\r\n[2023-03-08T19:29:47.962Z] \"- - -\" 0 - - - \"-\" 0 27 47 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40248 172.25.58.141:3306 172.25.90.90:41134 - -\r\n[2023-03-08T19:29:47.967Z] \"- - -\" 0 - - - \"-\" 0 27 43 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40298 172.25.58.141:3306 172.25.90.90:41190 - -\r\n[2023-03-08T19:29:47.967Z] \"- - -\" 0 - - - \"-\" 0 27 42 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40352 172.25.58.141:3306 172.25.90.90:41208 - -\r\n[2023-03-08T19:29:47.967Z] \"- - -\" 0 - - - \"-\" 0 27 43 - \"-\" \"-\" \"-\" \"-\" \"172.25.88.107:3306\" outbound|3306||mysql.kubeflow.svc.cluster.local 172.25.90.90:40312 172.25.58.141:3306 172.25.90.90:41198 - -\r\n...\r\n```\r\n\r\nFor a single Click on the Artifacts tab in the Kubeflow Dashboard, I have recorded around 457 connection requests to the mysql database in a span of time from: 2023-03-08T19:29:47.244Z to 2023-03-08T19:29:51.640Z a period of about 4 seconds.\r\n\r\nTHIS IS CLEARLY A BUG. Question is: Is this a bug of configuration (hope so) or a general defect in the code.\r\n\r\nCan someone with more familiarity with the code do some problem analysis?\r\n", "@jlyaoyuli it looks like this has been resolved by https://github.com/kubeflow/pipelines/pull/9370 (planned for inclusion in the final `2.0.0`, and already included in `2.0.0-rc.1`), do you agree?", "@thesuperzapper Thanks for checking! Yes, this issue should be resolved in our latest version!" ]

"2023-02-13T19:05:03"

"2023-06-01T21:34:21"

"2023-06-01T20:43:01"

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[ "Hi @ReggieCarey!\r\nThank you for reporting it. This component is not actively developed. If you wish, please create a PR adding the support for non-GCP distributions of kubernetes.", "Thanks for the feedback! Great community. What was diagnose me supposed to do? I'll try to find the code and answer that myself. If it's not actively maintained, should it be removed for marked in some way?", "Thanks, @ReggieCarey. `diagnose_me` was created to programmatically capture a variety of information about a K8s deployment on GCP to help expedite debugging.\r\n\r\nThis tool is best thought of as a helper script for a particular form of deployment. Kubeflow Pipelines has no dependency on GCP.\r\n\r\nSince your inquiry we've been discussing how to handle the `diagnose_me` command for KFP v2.\r\nNo update yet, but you raise good considerations that we're taking into account.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-13T14:38:51"

"2023-08-26T07:42:27"

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[]

[ "Hi @AaronUST!\r\nCould you please check if you have specified a correct input for the component?", "@AaronUST @gkcalat I found the cause of this issue, please see https://github.com/kubeflow/pipelines/issues/8942 for more information.\r\n\r\nI imagine you will be able to fix this by removing `WorkflowTaskResults` RBAC access from your task executor ServiceAccount (which will often be `default-editor` in the profile namespaces).\r\n\r\nHowever, I am not sure if argo-workflows 3.4 supports the old Pod-annotation arpproach, so you may also have to downgrade to argo-workflows 3.3.\r\n\r\nAlso, you might need to try and clear out the broken cache content if you want to try and run these tasks again.", "Thank you, @thesuperzapper!\r\n\r\nClosing this to dedupe the issues." ]

"2023-02-13T11:09:52"

"2023-04-11T16:19:43"

"2023-04-11T16:19:43"

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[]

"2023-02-11T00:29:23"

"2023-02-16T07:31:11"

"2023-02-16T07:31:11"

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[ "I was confused, the healthz response I saw was served by the frontend. So missing v2beta1/healthz is expected, as we haven't migrate frontend to connect to v2 APIs yet.\r\n\r\nhttps://github.com/kubeflow/pipelines/blob/508b6a133ab7a0d8abefe7ac95a4de824461e30b/frontend/server/app.ts#L109-L116", "This is resolved as per @chensun's comment and our discussion." ]

"2023-02-09T22:19:09"

"2023-02-10T22:18:56"

"2023-02-10T22:18:56"

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[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-09T19:20:38"

"2023-08-26T07:42:29"

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[]

"2023-02-09T19:15:05"

"2023-08-15T17:03:57"

"2023-08-15T17:03:57"

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[ "Not sure what was the reason adding a `-iterations` suffix to the loop task name [here](https://github.com/kubeflow/pipelines/blob/2.0.0-beta.0/backend/src/v2/compiler/argocompiler/dag.go#L297), but tested in my Kubeflow deployment, simply removing the suffix would make the compiled Argo workflow passing validation.", "Tested with beta.2, still happening.", "I've encountered the issue in 2.0.0-rc.2 as well" ]

"2023-02-09T09:59:36"

"2023-06-20T17:14:05"

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[]

[ "I've got the same error", "In my environment, upgrading kfp to 2.0.0b12 resolved this issue.", "I will close this issue. Feel free to reopen the issue if there's any more problems.", "> In my environment, upgrading kfp to 2.0.0b12 resolved this issue.\r\n\r\nI tried upgrading to 2.0.0b12, but I have CSV files as input output of the components in my code. So, it gives an error : \"typeerror: artifacts must have both a schema_title and a schema_version, separated by `@`. got: csv\" . Can you suggest something for this?" ]

"2023-02-08T22:46:08"

"2023-06-05T19:58:13"

"2023-02-09T23:40:42"

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[ "@JakeSummers, please see my comment here: https://github.com/kubeflow/pipelines/pull/7451#issuecomment-1423310652", "The issue is lack of py.typed (+ setup.py to preserve py.typed in wheel). kfp uses types internally, but types are not exposed to users because of [pep 560](https://peps.python.org/pep-0560/). An empty place marker file of py.typed at root of package (kfp/ folder) + setup.py include_package_data is needed to resolve this.\r\n\r\nI can confirm using kfp 2.0.1 that this issue still applies and looking at master should be present even if new release was done now." ]

"2023-02-08T21:22:43"

"2023-07-28T08:16:49"

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[]

[ "I do not know if I should report this to the vertex-ai team, but I do not know how.", "I think now with the last release of kfp `v2.0.12.0b` are now running fine." ]

"2023-02-08T19:42:10"

"2023-02-08T21:38:21"

"2023-02-08T21:38:21"

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[]

"2023-02-07T16:17:32"

"2023-03-10T00:55:41"

"2023-02-07T21:57:42"

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[ "I came across the same issue when tried to convert an existing v1 pipeline implementation to v2, which had a downstream task depending on upstream tasks in a `ParallelFor` group. Then I came across this new [commit](https://github.com/kubeflow/pipelines/pull/8631) in kfp pre-release `2.0.0b12`. At least using `dsl.Collected` the compiler was able to build the DAG as expected. But would like to confirm if that was the intended way to achieve this dependency pattern in v2, if so, what was the logics behind it?", "@kakaxilyp \r\nthanks for sharing this. In the previous release `dsl.Collected` was not yet available.\r\nhow do I get around the problem that my parallel for might not have an output but a side effect that I want to wait for? ", "Yeah I had the same question actually, probably better to ask @connor-mccarthy to enlighten us about the thoughts behind this new pattern.\r\n\r\nJust a general workaround I can think of, would be letting the downstream task explicitly retry-check-loop to verify the side effect I guess, though this really should be achieved by DAG dependencies.", "@kakaxilyp @MaxGrtz, the original reason for blocking use of `task_a.after(task_b)` where `task_b` is defined in a loop is that it introduces some runtime behavior ambiguity: should `task_b` run after all `task_a` instances finish? Just one `task_a` finishes? Something else?\r\n\r\nThat being said, this issue has been discussed a few times and I think it's worth revisiting this choice. It seems reasonable to me to just agree on what the `.after` means and support it.\r\n\r\nI will look into this and follow up on this thread. Thank you for bringing this up.", "@connor-mccarthy Thanks for the clarification.\r\nWhat do you think about support of after for task groups? Is is something that might be feasible long term?", "BTW:\r\nI solved this for now basically as @kakaxilyp suggested. I added a dummy output for the inner task (e.g. 0) and created a task for printing a List of int and used `dsl.Collected` to collect the inner task results. \r\nThen the next task can be made dependent on to the print task with `.after` again.", "> What do you think about support of after for task groups? Is is something that might be feasible long term?\r\n\r\nThis definitely is something worth considering, though there are some syntactical challenges with referring to the `TasksGroup` object, particularly with the `dsl.ParallelFor` case. For example, this reads a bit strange:\r\n\r\n```python\r\nwith dsl.ParallelFor([1, 2, 3]) as x:\r\n comp_1(num=x)\r\n\r\ncomp_2(text='hi').after(x)\r\n```\r\n\r\nWhen using the context manager, the `dsl.ParallelFor` instance \"becomes\" the int variable `x`. Referring to it as the `TasksGroup` afterward is slightly abusing it's meaning as an int variable. These little changes in meaning are where some of the complexity in the authoring experience starts to creep in.\r\n\r\n@MaxGrtz and @kakaxilyp, I think maybe the best option here is to wrap the `ParallelFor` sub-DAG in a pipeline, nest the pipeline, and call `.after()` on the inner pipeline. This is fully supported in the current 2.x.x release.\r\n\r\n```python\r\n@dsl.pipeline\r\ndef inner():\r\n with dsl.ParallelFor([1, 2, 3]) as x:\r\n comp(num=x)\r\n\r\n@dsl.pipeline\r\ndef outer():\r\n inner_task = inner()\r\n comp().after(inner_task)\r\n```\r\n\r\n(untested, but this should be approximately correct)", "> though there are some syntactical challenges with referring to the TasksGroup object, particularly with the dsl.ParallelFor case. \r\n\r\n@connor-mccarthy I see. Thats really ambiguous. \r\n\r\nI like the nested pipeline approach you proposed. I tried it and it works like a charm. Thanks!", "BTW we can avoid defining a separate pipeline by assigning the `ParallelFor` to a variable before using it as a context manager.\r\n\r\n```py\r\ninner_task = dsl.ParallelFor([1, 2, 3])\r\nwith inner_task as x:\r\n comp_1(num=x)\r\ncomp_2(text='hi').after(inner_task)\r\n```", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-07T14:29:56"

"2023-08-26T07:42:31"

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[]

[ "Thanks, @b4sus. I'd be happy to review your contribution if you'd like to work on this!" ]

"2023-02-07T08:36:16"

"2023-03-01T17:33:03"

"2023-03-01T17:33:03"

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[ "This is a beta release blocker. \r\n\r\n@gkcalat for awareness." ]

"2023-02-07T05:50:06"

"2023-03-10T00:55:51"

"2023-02-07T21:57:32"

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[ "This has been resolved together with #8703 " ]

"2023-02-06T17:27:43"

"2023-04-11T18:33:23"

"2023-04-11T18:33:23"

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[]

"2023-02-06T17:21:18"

"2023-02-07T00:21:33"

"2023-02-07T00:21:33"

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[]

[ "Thanks for raising this, @Roymprog. The Vertex AI Pipelines team is aware of this.\r\n\r\nFor posterity, here is a minimal reproducible example:\r\n\r\n```python\r\nfrom kfp import dsl\r\n\r\n@dsl.component\r\ndef c(a: dsl.Input[dsl.Artifact], b: dsl.Input[dsl.Artifact]):\r\n print(a)\r\n print(b)\r\n\r\n@dsl.pipeline\r\ndef p():\r\n i = dsl.importer(\r\n artifact_uri='gs://ml-pipeline-playground/shakespeare1.txt',\r\n artifact_class=dsl.Dataset)\r\n t = c(a=i.output, b=i.output)\r\n```", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-06T10:09:13"

"2023-08-26T07:42:33"

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[ "@zijianjoy Hello, I would like to hear your thoughts on this feature request, do you think it would be feasible in KFP v2?. \r\nThanks ", "I think this feature is already supported for ROC curve, confusion matrix, and scalar metrics. Can you check if the followings match your need?\r\n\r\nCompare pipeline runs: https://www.kubeflow.org/docs/components/pipelines/v1/sdk-v2/run-comparison/\r\n\r\nHow to create V2 metrics: https://www.kubeflow.org/docs/components/pipelines/v1/sdk/output-viewer/#v2-sdk-use-sdk-visualization-apis", "@zijianjoy thank you for your feedback. \r\nTo the best of my knowledge, I do not think this feature is already supported given the currently available output types. \r\nLet me try to explain why it is not the case for each of them : \r\n- A ROC Curve is meant to be used to asses the trade-off between the true positive rate and false positive rate for a model using tresholds. \r\n - If we take the use case described by this feature request, if we wanted to plot the `train_loss` vs the `val_loss` metrics (which under the hood is just two list of floats), we would not be able to since there is no concept of true positive and false positive in this case.\r\n\r\n - The use case described by the feature request is to be able to plot a list of floats regardless of its underlying semantic, so a list of `train_loss` or `val_loss` is one example, a list of accuracy values (floats) is another example.\r\n \r\nExample: \r\n```python\r\naccuracy_values: list[float] = [] \r\n\r\nfor epoch in range(number_of_epochs):\r\n ...\r\n epoch_accuracy: float = ...\r\n accuracy_values.append(epoch_accuracy) \r\n \r\nmetrics.log_metric(y=accuracy_values)\r\n```\r\n - We could have KFP set the X axis to numeric values from 1 to N by default where N is the number of elements in the list we are asking to plot or the sdk could allow to set the custom X axis values if the default does not suit us eg: `metrics.log_metric(y=accuracy_values, x=numpy.arange(start=1, stop=len(accuracy_values), step=1)` \r\n would be the same as : `metrics.log_metric(y=accuracy_values)` by default. \r\n\r\n- A confusion matrix is meant to be used to represent the performance of a model for various categories of labels. For instance, It can display if a model predicted cat 7/10 times when the true value was cat and 3/10 times when the true value was dog etc.\r\n - It is not meant to display a list of values (eg: list of floats like for `train_loss`, `val_loss`, accuracy value**s** list etc). \r\n - The feature request suggests an approach that can plot arbitrary list of values regardless of the model type (classification, regression etc). We could also extend this to support multiple list of values like matplotlib plot can. For instance if we want to plot the predicted stock price values vs the actual prices, we could do so by calling the `metrics.log_metric` method twice, once with the predicted y and another time with the actual y. \r\nExample : \r\n`my_metrics.log_metric(y=actual_y)`, `my_metrics.log_metric(y=predicted_y)`\r\nThat's just one example, if this would be possible, then by extension this would allow to plot the actual values vs predicted values of various methods/models (multiple predicted y), same principe, we would call the `metrics.log_metric` for the actual values and once for each predicted values list. \r\nExample: \r\n```python \r\nactual_y: list[float] = ...\r\nmy_metrics.log_metric(y=actual_y) \r\n\r\nfor model_index in range(number_of_models):\r\n predicted_y = models[model_index](X)\r\n my_metrics.log_metric(y=predicted_y)\r\n```\r\nHere is an example I have already done in the past, here we have 3 list of floats, one for the actual values (the yellow curve), one for the predicted values of a model without bagging (red curve) and one for a model with bagging (blue curve) : \r\n\r\n- As for the scalar metrics, it is what was described in this feature request as being one approach that is currently possible but does not hit home.\r\n - This approach would not plot the values but rather only show one value or the list of values but would not be presented in a plot making it impossible to reason about. \r\n\r\n - If this output metric type would plot a list of values instead of showing the raw values it would be a first step in the right direction but considering the other usages (like multiple list of values on the same plot), the KFP sdk should check if creating a new output metric type would be easier (I do not know if creating a new type or adapting this one would be easier to implement in the sdk so feel free to correct me).\r\n \r\nHopefully this clarifies the intent of the feature requested here. \r\n \r\nLet me know what you think :) \r\n", "@chensun @connor-mccarthy @Linchin @gkcalat\r\nFeel free to give your feedback as well , curious to know if you guys think it would be possible to implement in the future for KFP v2.", "Thank you for the explanation, if I understand correctly, there is a need for plot drawing metrics, which is generic enough that users can specify the `name of metrics`, `number of metrics`, `Name of x/y axis`, `upper bound and lower bound of x/y axis`, `x/y axis value for each numerical metrics`. \r\n\r\nPlease confirm if this understanding is correct, and whether you think it is valuable to compare two or more of such numerical metrics on UI?", "If you are interested in making contribution, will you be able to start a design doc for this feature? I feel that there can be multiple options to implement this.", "> if I understand correctly, there is a need for plot drawing metrics, which is generic enough that users can specify the name of metrics, number of metrics, Name of x/y axis, upper bound and lower bound of x/y axis, x/y axis value for each numerical metrics.\r\nPlease confirm if this understanding is correct \r\n\r\n@zijianjoy Yes, your understanding is correct this is exactly it. \r\nI think that there are some interesting decisions to make as to what must be provided by the sdk user and what can be inferred and used as default values. \r\n\r\n> whether you think it is valuable to compare two or more of such numerical metrics on UI? \r\n\r\nI think it would be extremely valuable to be able to compare at least two of such numerical metrics on the UI (eg: one from run A and one from run B). Ideally we would have the option to have the two plots merged together when comparing 2 runs. We should also be able to view plot A from run A side-by-side to the plot A' from run A'. For instance, when comparing model accuracies during training we would have 1 list of numerical value per run, in this case the merge view makes more sense, but when comparing the train loss and val loss of one run vs the train loss and val loss of another run, we would end up with 2x2 = 4 lines on the same plot. This is still ok for most cases in the merged view, but if we have 5 runs that's 10 lines on the same plot, it could become hard to visualize all of those lines so in this case, perhaps the user would decide that the side-by-side make more sense now. There could be a toggle button in the UI so that user can decide if it's better to \"merge\" the plots for comparison or to see them \"side-by-side\" for their use case. \r\nFor ease of comparison, we could also make the range of the x and y axis be the min and max of the x and y axis for all logged metrics. \r\nA clear use case of this (but use cases are not limited to this example) would be to compare the same numerical metrics for two models, this is fairly common in experiment tracking solutions : \r\n<img src=\"https://user-images.githubusercontent.com/26939775/217971306-2c2d45a1-1f97-4e46-83f2-9db3a7241ceb.png\" height=\"300\"/> \r\n \r\n> If you are interested in making contribution, will you be able to start a design doc for this feature? I feel that there can be multiple options to implement this. \r\n \r\nYes I am willing to create such document. \r\nI think you are right, there are a lot of options each with their pros and cons. \r\nThis will allow the community to weigh in on some of these options and implementation details that might affect KFP users experience. \r\n\r\n", "@zijianjoy Here is the link to the [design doc](https://bit.ly/3HSK5i9) so far. \r\nI tried adding in some thoughts about SDK design and possible APIs and default values etc. \r\nLet me know what you think and feel free to request access to it so I can grant you editor access. \r\nThis is my first design doc for Kubeflow so please don't hesitate to let me know if I got the structure completely wrong. ", "Hello @zijianjoy , would it be possible to get an update on my latest replies https://docs.google.com/document/d/1mVsV4C02stBlamhQm0bPeBsFDBsXdQXD7gyMJ4l-A6s/edit?usp=drivesdk\r\nIf my understanding of your proposal is correct, it seems like your proposal would greatly reduce the scope and therefore simplify the implementation of the feature.\r\nWhat do you think? Is that right?", "Thank you @AlexandreBrown for the design doc! \r\n\r\nTo answer your question: Yes you captured my suggestion correctly and thanks for adding this point to the design doc.\r\n\r\nAlso, I have brought this to the KFP team for discussion. \r\nWe think that the generic numerical values metrics can be useful, but it might not be able to cover all use cases because:\r\n- The data format for numerical values metrics is an additional workload for users to learn and adopt.\r\n- If users need a different visualization approach, it is hard to adjust existing data format to adopt new requirements.\r\n- We have existing functionality in KFPv1 like Tensorboard which can provide same and more advanced support: https://www.kubeflow.org/docs/components/pipelines/v1/sdk/output-viewer/#tensorboard. \r\n\r\nWould you like to evaluate whether Tensorboard can fulfill your need? If yes, this feature request will be about supporting Tensorboard in KFPv2. And we welcome contributions for this feature.", "@zijianjoy Thanks for the reply and bringing this to the KFP team. \r\nYes I believe Tensorboard would be more than suitable for this as it is a pretty well-rounded solution for metrics comparison, model preview, data preview and more. \r\n \r\nTherefore I will rename this issue to better reflect this realization so that we can track Tensorboard support for KFPv2.", "@zijianjoy \r\nBeing able to have the Tensorboard data for a run and see the run metrics is important and useful as a core feature. \r\n\r\nIn addition to what was possible with v1, I think a nice feature that could be added once Tensorboard support is aded would be to add a way to aggregate the Tensorboard logs of multiple runs to then offer a Tensorboard view with data from multiple runs.\r\n\r\nUnder the hood it could be as straightforward as downloading the data from S3 of multiple runs then create a folder with all runs data. Then once all the data is in one folder we can ask Tensorboard to display logs under this root folder. \r\nTo the best of my knowledge this would be an easy way to compare tensorboard data of multiple runs.\r\n \r\nCurrently we would need to create a notebook, download the Tensorboard logs of multiple runs and then launch Tensorboard on this folder that includes all runs tensorboard data. \r\nThis is possible but a bit tedious, adding this as part of Kubeflow Pipeline compare view would make comparing tensorboard metrics much faster and effective in my opinion. \r\n \r\nLet me know if you think about this, if Kubeflow Pipelines could easily add such feature or not (roughly speaking).", "It would be nice to have Tensorboard gaining direct access to a KFP artifact, which maybe kind of model training log files that Tensorboard can deal with, and the Tensorboard can be tight integrated into visualization section of the KFP components. \r\n\r\nI had also issue to use an on-prem s3 bucket with ssl certificate validation turned off for current Tensorboard, while writing logs to s3 bucket from KFP component is also a lot of template coding. These all may be benefited from an additional `Output[TFLog]` in V2.\r\n\r\nPlease let me know your thoughts on this matter. If you like the idea please give a thumbs up! ", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-03T21:01:53"

"2023-08-26T07:42:35"

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[ "@vikashg, I suspect you are describing a component runtime error for a [Lightweight Python Component](https://www.kubeflow.org/docs/components/pipelines/v2/author-a-pipeline/components/#1-lighweight-python-function-based-components).\r\n\r\nThis is expected behavior; the Lightweight Python Component function only has access to the code/symbols defined within its scope [[ref](https://www.kubeflow.org/docs/components/pipelines/v2/author-a-pipeline/components/#1-lighweight-python-function-based-components:~:text=A%20standalone%20Python%20function%20is%20a%20function%20that%20does%20not%20reference%20any%20symbols%20defined%20outside%20of%20its%20scope.)]. Consider trying [Containerized Python Components](https://www.kubeflow.org/docs/components/pipelines/v2/author-a-pipeline/components/#2-containerized-python-components) to use non-hermetic component functions.", "Thanks @connor-mccarthy " ]

"2023-02-03T16:57:44"

"2023-02-24T03:45:16"

"2023-02-23T23:52:03"

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[ "I've managed to find a workaround for this. The point is that the @component decorator is necessary for `kfp component build ...` and later when compiling/running the pipeline. But the target image and the code in it should not have it (at least not with current sdk version). Steps:\r\n1. run `kfp component build ...` - this will generate few files (ini, Dockerfile, yaml, requirements.txt), build the image and push it. This is the image which contains the decorator and will fail with missing __annotations__\r\n2. comment out the decorator\r\n3. build & push the image directly with docker (Dockerfile and other meta files are already there from step 1) - now image with non-decorated function will be pushed\r\n4. uncomment the decorator\r\n5. compile/run the pipeline using the component", "I'm experiencing the same issue. Is this something that would be easy to fix for the next release?\r\n", "The workaround described by @b4sus worked for me though (https://github.com/kubeflow/pipelines/issues/8791#issuecomment-1419168779)", "Thanks for raising this, @b4sus and @micmarty-deepsense. I am working on a fix.", "Huge thanks @connor-mccarthy! 👏 \r\nI'm gonna try it.", "@micmarty-deepsense, [2.0.0-beta.13](https://pypi.org/project/kfp/2.0.0b13/) contains this fix, so you should be able to try from this version." ]

"2023-02-03T14:34:19"

"2023-02-28T00:57:12"

"2023-02-28T00:42:52"

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[ "@jayaprasadt Thanks for reaching out. Would you mind sharing what type of issue you're trying to fix? If the change is related to pipeline template, it won't start from the failed step by design.\r\n\r\nAt the meantime, we suggest you to try the KFP v2 to see whether the problem exists.", "@jlyaoyuli Thanks for confirming the pipeline won't start from the failed step if the change is related to pipeline template. I'll try KFP v2 and let you know. ", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-03T10:41:41"

"2023-08-26T07:42:37"

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[]

[ "anyone knows this issue?", "@elim19 Thanks for reaching out! The driver task is supported in KFP v2 SDK. https://www.kubeflow.org/docs/components/pipelines/v2/run-a-pipeline/" ]

"2023-02-03T00:29:57"

"2023-02-17T00:00:50"

"2023-02-17T00:00:50"

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[ "We've upgraded golang to 1.20: https://github.com/kubeflow/pipelines/blob/c0640d7a033b6fa2133b92c2a459d9eb3dabee32/backend/Dockerfile#L16\r\n\r\nAlso I can confirm we no longer see this CVE in our latest api-server image (2.0.0-rc.1)" ]

"2023-02-02T18:45:15"

"2023-06-07T20:08:26"

"2023-06-07T20:08:25"

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[ "Does it work for 1.8.5 but not for 1.8.9? Not sure which local deployment methods are you using, and did you get any specific error? \r\nMaybe you've already seen this, but here's our local deployment instruction: https://www.kubeflow.org/docs/components/pipelines/v1/installation/localcluster-deployment/", "Yes It works for 1.8.5 but not for 1.8.9. I am using the same docuemntation for installation => \r\nhttps://www.kubeflow.org/docs/components/pipelines/v1/installation/localcluster-deployment/\r\n", "Sorry, I followed the reported message without checking the facts. We don't have a release tag for 1.8.9. \r\nThe latest is 1.8.5 for deployment.\r\nYou might have been confused by the KFP SDK version?" ]

"2023-02-02T17:19:07"

"2023-02-17T00:05:02"

"2023-02-17T00:05:01"

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[ "Hi, @AlbertCintas. If you're using KFP v2 (BE nearly in beta), the following example should demonstrate the usage you're looking for:\r\n\r\n```python\r\nfrom kfp import compiler\r\nfrom kfp import dsl\r\nfrom kfp.dsl import component\r\n\r\n\r\n@component\r\ndef print_op(message: str):\r\n \"\"\"Prints a message.\"\"\"\r\n print(message)\r\n\r\n\r\n@component\r\ndef fail_op(message: str):\r\n \"\"\"Fails.\"\"\"\r\n import sys\r\n print(message)\r\n sys.exit(1)\r\n\r\n\r\n@component\r\ndef get_run_state(status: dict) -> str:\r\n print('Pipeline status: ', status)\r\n return status['state']\r\n\r\n\r\n@dsl.pipeline\r\ndef exit_op():\r\n print_op(message='notify task failure.')\r\n\r\n\r\n@dsl.pipeline\r\ndef my_pipeline():\r\n exit_task = exit_op()\r\n\r\n with dsl.ExitHandler(exit_task):\r\n print_op(message='message')\r\n fail_op(message='Task failed.')\r\n```", "Thank you for your answer!\r\n\r\nTried this method, but couldn't compile it with two components (loaded from a file) called from inside the exit_op. ", "@AlbertCintas, could you share a minimal reproducible example, as well as the SDK version?", "Hello, sorry for the late answer, I've been on vacation. I think I might have not been clear with my request, sorry for that.\r\n\r\nWhat I need are two components as part of the exit handler component (one performs cleanup, the other sends a notification). Unfortunately, we're still running KFP v1, even though I've been compiling some pipelines to be V2_compatible. I've tried so many ways of doing it, but none compiles (if using v1) or works in KFP v1 (if compiled using v2).\r\n\r\nFollowing your example, what I would need is something like this:\r\n```\r\n@component\r\ndef cleanup_op():\r\n print(\"This component performs cleanup\")\r\n\r\n@component\r\ndef notification_op():\r\n print(\"This component sends a notification\")\r\n\r\n@component\r\ndef print_op(message: str):\r\n \"\"\"Prints a message.\"\"\"\r\n print(message)\r\n\r\n@dsl.pipeline\r\ndef exit_op():\r\n cleanup_op()\r\n notification_op()\r\n\r\n@dsl.pipeline\r\ndef my_pipeline():\r\n exit_task = exit_op()\r\n\r\n with dsl.ExitHandler(exit_task):\r\n print_op(message='message')\r\n```\r\n\r\nIs it possible to do this in KFP v1? I was reading Argo documentation and it is possible to have multiple exit handlers running and even choose which one to run depending on a condition, but I've found nothing related for Kubeflow.", "I see, @AlbertCintas. This is not possible in v1.\r\n\r\nIn v2, you can use a pipeline as your exit task to accomplish this: https://github.com/kubeflow/pipelines/blob/9926f31a3a0f5c250a8b31ce474f16bb72520ab5/sdk/python/test_data/pipelines/pipeline_as_exit_task.py#L51", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-02T15:38:42"

"2023-08-26T07:42:39"

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[]

[]

[ "Hi @MatthewRalston , you need to create parent directories for the output path, before you can write the data. See example: https://github.com/kubeflow/pipelines/blob/61a6172e7d88e21ee90af8b3ecf63b0224b8172c/sdk/python/test_data/pipelines/pipeline_with_outputs.py#L36", "@chensun that's a nice example, and thank you so much, but it doesn't alone solve this issue for users!\r\n\r\nSpecifically, the developer should suggest documentation pages! Examples of this behavior elsewhere! Where in the documentation does it connect the filename, the component's OutputPath returned, how that name gets acquired, and why/where the user needs to specify, instead of Kubeflow, the output directory path and then the user has to make it themselves????\r\n\r\n\r\nThis isn't solved! @vanpelt can you suggest something more direct? This is very much a documentation smell, a code smell, possibly a versioning confilct (v1.8 kfp standards vs v2.0 migration), and actually a *ghost* feature: specifically because *after reading Google's Kubeflow documentation for production Kubernetes environments* there is no mention of explicit artifact or directory creation as recommended. How to save artifacts on my v1.6.1 Manifest standard installation?\r\n\r\nAlso, the issue seems to be *tagged* incorrectly as well. This *might* not even be a 'kfp' issue per-se, but something related to artifact saving, kubeflow instance configuration, etc.\r\n\r\nEveryone (but not just the very attentive and helpful @chensun ) keeps recommending I modify *syntax* to address the problem.\r\n\r\n\r\nThis problem emerges from lack of documentation and implicit conventions, instead of completed version-specific docs, detailing how artifact saving process may be in flux, and the conventions at play (\"/tmp/data/Outputs\" needs to be created, are you sure @chensun ?)", "Still really confused about this. This seems confusing that Kubeflow doesn't manage files on its own. Is this a syntax issue, or is my Kubeflow instance malformed?\r\n\r\n@chensun can you maybe tag someone from the Manifests group to review this configuration?\r\n\r\n\r\nMinikube, kustomize, minio\r\n\r\n minikube 1.28.0\r\n kustomize 3.2.0\r\n kubernetes/kubectl 1.22.2\r\n docker 20.10.21\r\n containerd v1.6.10\r\n\r\n\r\n```bash\r\n>kustomize version\r\nVersion: {KustomizeVersion:3.2.0 GitCommit:a3103f1e62ddb5b696daa3fd359bb6f2e8333b49 BuildDate:2019-09-18T16:26:36Z GoOs:linux GoArch:amd64}\r\n>minio --version\r\nminio version RELEASE.2023-01-20T02-05-44Z (commit-id=0f591d245d3a1810b0e6aebbf3f32937227f68f8)\r\nRuntime: go1.19.5 linux/amd64\r\nLicense: GNU AGPLv3 <https://www.gnu.org/licenses/agpl-3.0.html>\r\nCopyright: 2015-0000 MinIO, Inc.\r\n>minikube addons enable istio\r\n>istioctl install --set revision=canary\r\n>minikube kubectl -- create -f config/profile.yaml\r\n```\r\n\r\n* `config/profile.yaml`\r\n\r\n```yaml\r\n\r\n resourceQuotaSpec: # resource quota can be set optionally\r\n hard:\r\napiVersion: kubeflow.org/v1beta1\r\nkind: Profile\r\nmetadata:\r\n name: user\r\nspec:\r\n owner:\r\n kind: User\r\n name: email@example.org\r\n recourceQuotaSpec:\r\n hard:\r\n cpu: \"3000m\"\r\n memory: 100Gi\r\n pods: \"24\"\r\n requests.nvidia.com/gpu: \"1\"\r\n persistentvolumeclaims: \"1\"\r\n requests.storage: \"200Gi\"\r\n \r\n```\r\n\r\n\r\nThen, I do various obvious port-forwarding routines locally to expose the Kubeflow dashboard.\r\n\r\n\r\nAfter starting vanilla minikube, I apply the 1.6.1 Kubeflow/manifests to the cluster as per instructions.\r\n\r\nDo I need to adjust something in my configuration, or is this, as @chensun suggests, simply a v1.8 syntax issue requiring me to create directories for output files to somehow be managed by kubeflow?" ]

"2023-02-02T14:33:55"

"2023-02-10T01:12:03"

"2023-02-02T23:56:28"

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[]

[ "@JakeSummers, I think this is a good idea. If you're interested in contributing this (including the [docs](https://github.com/kubeflow/website) fix) I would happy to review your PR.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-01T16:42:34"

"2023-08-26T07:42:41"

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[ "Looking at this a bit further, it seems like it is not asking for the `namespace` but for the `experiment`. \r\n\r\nChanging this: \r\n\r\n```\r\n current_recurring_runs: ApiListJobsResponse = client.list_recurring_runs(page_token=None)\r\n```\r\n\r\nTo this: \r\n\r\n```\r\n current_recurring_runs: ApiListJobsResponse = client.list_recurring_runs(page_token=None, experiment_id=123)\r\n```\r\n\r\nFixed the issue. ", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-02-01T16:11:57"

"2023-08-26T07:42:43"

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[]

[ "I logged this under the wrong area. Relogging as #8777" ]

"2023-02-01T16:02:25"

"2023-02-01T16:13:11"

"2023-02-01T16:13:10"

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[]

[ "Hi @Rstar1998 , you can achieve that using \"Containerized Python components\": https://www.kubeflow.org/docs/components/pipelines/v2/author-a-pipeline/components/#2-containerized-python-components" ]

"2023-02-01T09:14:21"

"2023-02-02T23:50:56"

"2023-02-02T23:50:55"

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[]

[ "Hi @elim19, you may find more info about launcher in the design doc we shared with the community: [bit.ly/kfp-v2](https://bit.ly/kfp-v2)\r\nTo gain access to the doc, please join https://groups.google.com/g/kubeflow-discuss google group.\r\n" ]

"2023-01-31T09:57:17"

"2023-02-03T00:28:56"

"2023-02-02T23:46:35"

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[ "/assign @chensun ", "We also experience the very same issue, once our cluster Auto-Scales. All logs are gone and NOT read from our mirror in MINIO (interface of KFP to access S3) / AWS S3 (physical location).", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-26T06:52:18"

"2023-08-26T07:42:45"

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[]

"2023-01-25T17:56:39"

"2023-03-15T23:46:30"

"2023-03-15T23:46:30"

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[ "/assign @gkcalat ", "Hi @deepk2u!\r\nIt may be due to insufficient resource provisioning or the lack of etc maintenance (see [here](https://etcd.io/docs/v3.3/op-guide/maintenance/)). How longs did it take for you to reach these numbers?", "It's an eks cluster. We connected with AWS support and they are maintaining the cluster and running defragmentation and doing all kinds of maintenance for etcd.\r\n\r\n\r\nthe oldest object I have on the list is from 14th July 2022.\r\n", "Can check how large are your pipeline manifests used in these recurring runs?", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-25T04:25:41"

"2023-08-26T07:42:47"

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[ "/assign @chensun ", "I'm seeing something similar when trying to test with a local k3s install. I installed kfp 2.0.0b12 backend and sdk, and then used the example [from the new 2.0.0b12 docs](https://kubeflow-pipelines.readthedocs.io/en/2.0.0b12/#getting-started), but I get errors. Oddly enough, I was able to run v1-compiled pipelines, but I couldn't get the example from the docs, or anything v2 to work.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-24T15:55:20"

"2023-08-26T07:42:49"

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[]

[]

[ "@samcaetano, I recommend you try KFP SDK v2 (`pip install kfp --pre`). It is in beta phase, but stable.", "Any update on this?", "@LuigiCerone, no fix for this yet. This is captured by https://github.com/kubeflow/pipelines/issues/8385. Let's treat that one as the canonical bug and close this one, since the other has more discussion." ]

"2023-01-22T16:26:21"

"2023-03-17T20:37:45"

"2023-03-17T20:37:45"

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[ "/assign @chensun", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-20T15:18:50"

"2023-08-26T07:42:51"

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[ "/assign @chensun ", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-20T05:45:14"

"2023-08-27T07:41:43"

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[]

[ "`kfp==2.0.0b10` and `kfp-pipeline==0.1.17` are yanked. This is no longer be an issue." ]

"2023-01-20T00:35:32"

"2023-01-20T21:46:19"

"2023-01-20T21:46:19"

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[]

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[ "/cc @gkcalat ", "This has been fixed in #8633" ]

"2023-01-19T22:38:17"

"2023-03-10T00:54:43"

"2023-02-07T00:27:12"

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[]

"2023-01-19T19:13:12"

"2023-02-07T01:24:34"

"2023-02-07T01:24:34"

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[ "Hi @fstetic!\r\nThank you for reporting this. Could you please share more details on this: error message, logs, yaml pipeline spec?", "@fstetic, if you `pip install kfp-pipeline-spec==0.1.16` is the error resolved?", "@gkcalat sure!\r\n\r\nHere is the full error message:\r\n`{\"error_message\":\"Error creating pipeline: Create pipeline failed: InvalidInputError: unknown template format: pipeline spec is invalid\",\"error_details\":\"Error creating pipeline: Create pipeline failed: InvalidInputError: unknown template format: pipeline spec is invalid\"}`\r\nand here is the YAML spec:\r\n```\r\n# PIPELINE DEFINITION\r\n# Name: addition-pipeline\r\n# Inputs:\r\n# a: int\r\n# b: int\r\n# c: int [Default: 10.0]\r\ncomponents:\r\n comp-addition-component:\r\n executorLabel: exec-addition-component\r\n inputDefinitions:\r\n parameters:\r\n num1:\r\n parameterType: NUMBER_INTEGER\r\n num2:\r\n parameterType: NUMBER_INTEGER\r\n outputDefinitions:\r\n parameters:\r\n Output:\r\n parameterType: NUMBER_INTEGER\r\n comp-addition-component-2:\r\n executorLabel: exec-addition-component-2\r\n inputDefinitions:\r\n parameters:\r\n num1:\r\n parameterType: NUMBER_INTEGER\r\n num2:\r\n parameterType: NUMBER_INTEGER\r\n outputDefinitions:\r\n parameters:\r\n Output:\r\n parameterType: NUMBER_INTEGER\r\ndeploymentSpec:\r\n executors:\r\n exec-addition-component:\r\n container:\r\n args:\r\n - --executor_input\r\n - '{{$}}'\r\n - --function_to_execute\r\n - addition_component\r\n command:\r\n - sh\r\n - -c\r\n - \"\\nif ! [ -x \\\"$(command -v pip)\\\" ]; then\\n python3 -m ensurepip ||\\\r\n \\ python3 -m ensurepip --user || apt-get install python3-pip\\nfi\\n\\nPIP_DISABLE_PIP_VERSION_CHECK=1\\\r\n \\ python3 -m pip install --quiet --no-warn-script-location 'kfp==2.0.0-beta.10'\\\r\n \\ && \\\"$0\\\" \\\"$@\\\"\\n\"\r\n - sh\r\n - -ec\r\n - 'program_path=$(mktemp -d)\r\n\r\n printf \"%s\" \"$0\" > \"$program_path/ephemeral_component.py\"\r\n\r\n python3 -m kfp.components.executor_main --component_module_path \"$program_path/ephemeral_component.py\" \"$@\"\r\n\r\n '\r\n - \"\\nimport kfp\\nfrom kfp import dsl\\nfrom kfp.dsl import *\\nfrom typing import\\\r\n \\ *\\n\\ndef addition_component(num1: int, num2: int) -> int:\\n return\\\r\n \\ num1 + num2\\n\\n\"\r\n image: python:3.7\r\n exec-addition-component-2:\r\n container:\r\n args:\r\n - --executor_input\r\n - '{{$}}'\r\n - --function_to_execute\r\n - addition_component\r\n command:\r\n - sh\r\n - -c\r\n - \"\\nif ! [ -x \\\"$(command -v pip)\\\" ]; then\\n python3 -m ensurepip ||\\\r\n \\ python3 -m ensurepip --user || apt-get install python3-pip\\nfi\\n\\nPIP_DISABLE_PIP_VERSION_CHECK=1\\\r\n \\ python3 -m pip install --quiet --no-warn-script-location 'kfp==2.0.0-beta.10'\\\r\n \\ && \\\"$0\\\" \\\"$@\\\"\\n\"\r\n - sh\r\n - -ec\r\n - 'program_path=$(mktemp -d)\r\n\r\n printf \"%s\" \"$0\" > \"$program_path/ephemeral_component.py\"\r\n\r\n python3 -m kfp.components.executor_main --component_module_path \"$program_path/ephemeral_component.py\" \"$@\"\r\n\r\n '\r\n - \"\\nimport kfp\\nfrom kfp import dsl\\nfrom kfp.dsl import *\\nfrom typing import\\\r\n \\ *\\n\\ndef addition_component(num1: int, num2: int) -> int:\\n return\\\r\n \\ num1 + num2\\n\\n\"\r\n image: python:3.7\r\npipelineInfo:\r\n name: addition-pipeline\r\nroot:\r\n dag:\r\n tasks:\r\n addition-component:\r\n cachingOptions:\r\n enableCache: true\r\n componentRef:\r\n name: comp-addition-component\r\n inputs:\r\n parameters:\r\n num1:\r\n componentInputParameter: a\r\n num2:\r\n componentInputParameter: b\r\n taskInfo:\r\n name: addition-component\r\n addition-component-2:\r\n cachingOptions:\r\n enableCache: true\r\n componentRef:\r\n name: comp-addition-component-2\r\n dependentTasks:\r\n - addition-component\r\n inputs:\r\n parameters:\r\n num1:\r\n taskOutputParameter:\r\n outputParameterKey: Output\r\n producerTask: addition-component\r\n num2:\r\n componentInputParameter: c\r\n taskInfo:\r\n name: addition-component-2\r\n inputDefinitions:\r\n parameters:\r\n a:\r\n parameterType: NUMBER_INTEGER\r\n b:\r\n parameterType: NUMBER_INTEGER\r\n c:\r\n defaultValue: 10.0\r\n isOptional: true\r\n parameterType: NUMBER_INTEGER\r\nschemaVersion: 2.1.0\r\nsdkVersion: kfp-2.0.0-beta.10\r\n```\r\nYou made me try uploading it now without `defaultValue: 10.0` and `isOptional: true` and the problem isn't `defaultValue`, it's `isOptional`.\r\n\r\n---\r\n\r\nHi @connor-mccarthy! The error isn't resolved, the YAML spec looks identical. Also, pip throws a dependency error when installing `kfp-pipeline-spec 0.1.16`: `kfp 2.0.0b10 requires kfp-pipeline-spec<0.2.0,>=0.1.17, but you have kfp-pipeline-spec 0.1.16 which is incompatible`\r\n", "+1 Got exactly the same issue (same version but our Kubeflow is on EKS).", "**SOLUTION**\r\nIn the short term, this is resolved by downgrading to `kfp==2.0.0b9` (and recompiling your pipeline with this version). In the long term, this will be resolved for `kfp>=2.0.0b10` by the upcoming KFP BE beta release.\r\n\r\ncc @chensun @gkcalat @Linchin " ]

"2023-01-19T10:45:25"

"2023-06-06T07:20:38"

"2023-06-06T07:20:38"

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[ "Hi @fstetic!\r\nThank you for reporting this. Could you confirm whether the problem is persistent or if it goes away after the run completes?", "Hi @gkcalat! Thanks for the quick response.\r\n\r\nThe run doesn't complete. That error happens at the start of the run.\r\n\r\nI tried a tutorial pipeline with v1 YAML spec and that one behaves as expected. I inspected MinIO bucket and found out that v1 pipelines make a dir named `<workflow name>` in `mlpipelines/artifacts`, but v2 don't. \"contextName\" in the error message stated in the issue corresponds to the RunID of the pipeline, not workflow name.\r\n\r\nI also noticed in network requests, when a run is opened in UI, a POST request to `/ml_metadata.MetadataStoreService/GetContextByTypeAndName` where v1 and v2 pipelines differ. V1 pipelines send `pipeline_run` in request body and v2 pipelines send `system.PipelineRun`. Don't know if that means anything because in both cases the request fails with `400` error and message `Cannot POST /ml_metadata.MetadataStoreService/GetContextByTypeAndName`\r\n\r\nI also raised this issue in Slack and a person responded that it might be related to a namespace/profile instantiation issue so I'll look into that next.", "Hello @fstetic \r\n\r\nI am also having the same problem.\r\nHave you figured out what is wrong?\r\n\r\nTesting on 2.0.0-beta.1 for both API Server and UI, and kfp==2.0.0beta14", "Hi @tleewongjaro-agoda. Unfortunately no, I gave up and downgraded to v1 pipelines.", "/cc @chensun ", "> Hello @fstetic\r\n> \r\n> I am also having the same problem. Have you figured out what is wrong?\r\n> \r\n> Testing on 2.0.0-beta.1 for both API Server and UI, and kfp==2.0.0beta14\r\n\r\nHave u fighred out now? Or any ideas?", "I have the same problem reported above, I tried to downgrade to v1 pipelines but not a compatible version of the sdk anymore\r\n\r\nThe version below does not install\r\n`!pip install kfp==1.8.21`\r\n\r\nOutput:\r\n\r\nCollecting PyYAML<6,>=5.3\r\n Using cached PyYAML-5.4.1.tar.gz (175 kB)\r\n Installing build dependencies ... Getting requirements to build wheel ... error: subprocess-exited-with-error\r\n \r\n × Getting requirements to build wheel did not run successfully.\r\n │ exit code: 1\r\n ╰─> [62 lines of output]\r\n /tmp/pip-build-env-l8mhrdoz/overlay/lib/python3.10/site-packages/setuptools/config/setupcfg.py:293: _DeprecatedConfig: Deprecated config in `setup.cfg`\r\n !!\r\n ********************************************************************************\r\n The license_file parameter is deprecated, use license_files instead.\r\n By 2023-Oct-30, you need to update your project and remove deprecated calls\r\n or your builds will no longer be supported.\r\n See https://setuptools.pypa.io/en/latest/userguide/declarative_config.html for details.\r\n ********************************************************************************\r\n !!\r\n parsed = self.parsers.get(option_name, lambda x: x)(value)\r\n running egg_info\r\n writing lib3/PyYAML.egg-info/PKG-INFO\r\n writing dependency_links to lib3/PyYAML.egg-info/dependency_links.txt", "The use of v1 pipelines is still viable?, I have the same problem reported above\r\n\r\nBut the proxy-agent pod is on CrashLoopBack, I searched the pod logs and the result is below\r\n\r\nIn the ui, I keep coming across this error without being able to use it\r\nError: failed to retrieve list of pipelines. Click Details for more information.\r\n\r\n+++ dirname /opt/proxy/attempt-register-vm-on-proxy.sh\r\n++ cd /opt/proxy\r\n++ pwd\r\n+ DIR=/opt/proxy\r\n++ jq -r '.data.Hostname // empty'\r\n++ kubectl get configmap inverse-proxy-config -o json\r\n+ HOSTNAME=\r\n+ [[ -n '' ]]\r\n+ [[ ! -z '' ]]\r\n++ curl http://metadata.google.internal/computeMetadata/v1/instance/zone -H 'Metadata-Flavor: Google'\r\n % Total % Received % Xferd Average Speed Time Time Time Current\r\n Dload Upload Total Spent Left Speed\r\n 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0curl: (6) Could not resolve host: metadata.google.internal\r\n+ INSTANCE_ZONE=/", "Sorry，I'm still using Pipeline v2. Can't help u.&nbsp;\r\n\r\n\r\n&nbsp;\r\n\r\n\r\n?????Enoch?????\r\n***@***.***\r\n\r\n\r\n\r\n&nbsp;\r\n\r\n\r\n\r\n\r\n------------------&nbsp;原始邮件&nbsp;------------------\r\n发件人: ***@***.***&gt;; \r\n发送时间: 2023年9月5日(星期二) 晚上6:56\r\n收件人: ***@***.***&gt;; \r\n抄送: ***@***.***&gt;; ***@***.***&gt;; \r\n主题: Re: [kubeflow/pipelines] [backend] Cannot get MLMD objects from Metadata store when running v2 pipeline (Issue #8733)\r\n\r\n\r\n\r\n\r\n\r\n \r\nThe use of v1 pipelines is still viable?, I have the same problem reported above\r\n \r\nBut the proxy-agent pod is on CrashLoopBack, I searched the pod logs and the result is below\r\n \r\nIn the ui, I keep coming across this error without being able to use it\r\n Error: failed to retrieve list of pipelines. Click Details for more information.\r\n \r\n+++ dirname /opt/proxy/attempt-register-vm-on-proxy.sh\r\n ++ cd /opt/proxy\r\n ++ pwd\r\n \r\nDIR=/opt/proxy\r\n ++ jq -r '.data.Hostname // empty'\r\n ++ kubectl get configmap inverse-proxy-config -o json\r\n \r\nHOSTNAME=\r\n \r\n[[ -n '' ]]\r\n \r\n[[ ! -z '' ]]\r\n ++ curl http://metadata.google.internal/computeMetadata/v1/instance/zone -H 'Metadata-Flavor: Google'\r\n % Total % Received % Xferd Average Speed Time Time Time Current\r\n Dload Upload Total Spent Left Speed\r\n 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0curl: (6) Could not resolve host: metadata.google.internal\r\n \r\nINSTANCE_ZONE=/\r\n \r\n—\r\nReply to this email directly, view it on GitHub, or unsubscribe.\r\nYou are receiving this because you commented.Message ID: ***@***.***&gt;" ]

"2023-01-19T10:30:18"

"2023-09-06T02:12:32"

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[ "Hi @HumairAK!\r\nThank you for reporting thins. Could you please share if you encounter this problem with `MySQL` DB?", "@gkcalat Percona xtradb is a drop in replacement for mysql db so I expect the same queries are made against mysql db, they may not show up in stdout logs though, you may need to check the query logs for it. I'll try to dig up some time to test it out with mysql proper. I did try it with mariadb and I could find these drop queries in the query log.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-19T04:52:31"

"2023-08-28T20:58:38"

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[ "issue also present in kfp 2.0.0b11", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-19T03:11:55"

"2023-08-27T07:41:47"

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[]

[]

[ "After another look, this is already supported." ]

"2023-01-18T22:51:52"

"2023-01-18T22:56:20"

"2023-01-18T22:56:20"

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[]

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{ "url": "https://api.github.com/repos/kubeflow/pipelines/milestones/10", "html_url": "https://github.com/kubeflow/pipelines/milestone/10", "labels_url": "https://api.github.com/repos/kubeflow/pipelines/milestones/10/labels", "id": 9154660, "node_id": "MI_kwDOB-71UM4Ai7Bk", "number": 10, "title": "KFP 2.0.0-GA", "description": "", "creator": { "login": "chensun", "id": 2043310, "node_id": "MDQ6VXNlcjIwNDMzMTA=", "avatar_url": "https://avatars.githubusercontent.com/u/2043310?v=4", "gravatar_id": "", "url": "https://api.github.com/users/chensun", "html_url": "https://github.com/chensun", "followers_url": "https://api.github.com/users/chensun/followers", "following_url": "https://api.github.com/users/chensun/following{/other_user}", "gists_url": "https://api.github.com/users/chensun/gists{/gist_id}", "starred_url": "https://api.github.com/users/chensun/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/chensun/subscriptions", "organizations_url": "https://api.github.com/users/chensun/orgs", "repos_url": "https://api.github.com/users/chensun/repos", "events_url": "https://api.github.com/users/chensun/events{/privacy}", "received_events_url": "https://api.github.com/users/chensun/received_events", "type": "User", "site_admin": false }, "open_issues": 7, "closed_issues": 19, "state": "open", "created_at": "2023-03-13T21:22:17", "updated_at": "2023-07-11T20:52:23", "due_on": null, "closed_at": null }

[]

"2023-01-18T22:04:51"

"2023-07-11T20:52:23"

"2023-07-11T20:52:23"

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[]

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[]

"2023-01-18T22:02:01"

"2023-06-23T02:42:11"

"2023-06-23T02:42:10"

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[ "Published: https://www.kubeflow.org/docs/components/pipelines/v2/migration/" ]

"2023-01-18T22:01:59"

"2023-04-04T17:46:45"

"2023-04-04T17:46:44"

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[]

"2023-01-18T22:01:57"

"2023-06-27T23:23:18"

"2023-06-27T23:23:17"

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[ "I was able to reproduce it. A possible root cause for this behavior is a failed MLMD update at runtime. As UI calls MLMD to get states of individual node (tasks) in a DAG, we can observe inconsistent states between run' state and its underlying tasks' states. This is already implemented in the backend in #8850.\r\n\r\nTo fix, UI needs to switch to reading states of the nodes from the v2 API's [run details](https://github.com/kubeflow/pipelines/blob/2.0.0-beta.1/backend/api/v2beta1/run.proto#L200), which carries states for each task coming from the KFP DB.\r\n\r\nKFP DB (correct state):\r\n\r\nMLMD (stale):\r\n\r\n\r\nUI integration is a post-GA work item: #8966 \r\n\r\n/cc @jlyaoyuli " ]

"2023-01-18T21:47:24"

"2023-05-04T16:53:11"

"2023-05-04T16:53:10"

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[ "Is there a workaround for this issue in the meantime?" ]

"2023-01-18T21:28:10"

"2023-05-03T00:58:16"

"2023-05-03T00:58:15"

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"2023-01-18T21:26:54"

"2023-02-09T23:41:04"

"2023-02-09T23:41:04"

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[]

[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-18T10:30:55"

"2023-08-27T07:41:48"

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[]

[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-18T10:26:23"

"2023-08-27T07:41:49"

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[]

[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions." ]

"2023-01-18T10:26:19"

"2023-08-27T07:41:51"

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