No type found for query: kubeflow.org/alpha/execution

[montenegrodr]

/kind bug

What steps did you take and what happened:
[A clear and concise description of what the bug is.]

Created a step in my kubeflow pipeline only for persisting metadata. But the step fails when trying to create an Execution with:

tensorflow.python.framework.errors_impl.NotFoundError: No type found for query: kubeflow.org/alpha/execution

Full stack:

2020-08-18 11:12:36.533692: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2020-08-18 11:12:36.533919: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
ERROR:absl:mlmd client NotFoundError: No type found for query: kubeflow.org/alpha/execution
ERROR:absl:mlmd client NotFoundError: No type found for query: kubeflow.org/alpha/execution
ERROR:absl:mlmd client NotFoundError: No type found for query: kubeflow.org/alpha/execution
ERROR:absl:mlmd client NotFoundError: No type found for query: kubeflow.org/alpha/execution
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/ml_metadata/metadata_store/metadata_store.py", line 157, in _call_method
    response.CopyFrom(grpc_method(request))
  File "/usr/local/lib/python3.7/site-packages/grpc/_channel.py", line 826, in __call__
    return _end_unary_response_blocking(state, call, False, None)
  File "/usr/local/lib/python3.7/site-packages/grpc/_channel.py", line 729, in _end_unary_response_blocking
    raise _InactiveRpcError(state)
grpc._channel._InactiveRpcError: <_InactiveRpcError of RPC that terminated with:
	status = StatusCode.NOT_FOUND
	details = "No type found for query: kubeflow.org/alpha/execution"
	debug_error_string = "{"created":"@1597749167.874007111","description":"Error received from peer ipv4:10.11.249.115:8080","file":"src/core/lib/surface/call.cc","file_line":1061,"grpc_message":"No type found for query: kubeflow.org/alpha/execution","grpc_status":5}"
>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
  File "/app/run.py", line 45, in <module>
    work()
  File "/app/run.py", line 28, in work
    description="execution example",
  File "/usr/local/lib/python3.7/site-packages/kubeflow/metadata/metadata.py", line 284, in __init__
    self._type_id = _retry(lambda: self.workspace.store.get_execution_type(
  File "/usr/local/lib/python3.7/site-packages/retrying.py", line 49, in wrapped_f
    return Retrying(*dargs, **dkw).call(f, *args, **kw)
  File "/usr/local/lib/python3.7/site-packages/retrying.py", line 212, in call
    raise attempt.get()
  File "/usr/local/lib/python3.7/site-packages/retrying.py", line 247, in get
    six.reraise(self.value[0], self.value[1], self.value[2])
  File "/usr/local/lib/python3.7/site-packages/six.py", line 703, in reraise
    raise value
  File "/usr/local/lib/python3.7/site-packages/retrying.py", line 200, in call
    attempt = Attempt(fn(*args, **kwargs), attempt_number, False)
  File "/usr/local/lib/python3.7/site-packages/kubeflow/metadata/metadata.py", line 756, in _retry
    return f()
  File "/usr/local/lib/python3.7/site-packages/kubeflow/metadata/metadata.py", line 285, in <lambda>
    Execution.EXECUTION_TYPE_NAME).id)
  File "/usr/local/lib/python3.7/site-packages/ml_metadata/metadata_store/metadata_store.py", line 630, in get_execution_type
    self._call('GetExecutionType', request, response)
  File "/usr/local/lib/python3.7/site-packages/ml_metadata/metadata_store/metadata_store.py", line 131, in _call
    return self._call_method(method_name, request, response)
  File "/usr/local/lib/python3.7/site-packages/ml_metadata/metadata_store/metadata_store.py", line 162, in _call_method
    raise _make_exception(e.details(), e.code().value[0])
tensorflow.python.framework.errors_impl.NotFoundError: No type found for query: kubeflow.org/alpha/execution

Pipeline Step:

from uuid import uuid4
from kubeflow.metadata import metadata
from datetime import datetime


METADATA_STORE_HOST = "metadata-grpc-service.kubeflow"
METADATA_STORE_PORT = 8080


def work():
    ws1 = metadata.Workspace(
        # Connect to metadata service in namespace kubeflow in k8s cluster.
        store=metadata.Store(grpc_host=METADATA_STORE_HOST, grpc_port=METADATA_STORE_PORT),
        name="workspace_1",
        description="a workspace for testing",
        labels={"n1": "v1"})

    r = metadata.Run(
        workspace=ws1,
        name="run-" + datetime.utcnow().isoformat("T"),
        description="a run in ws_1",
    )

    exec = metadata.Execution(
        name="execution" + datetime.utcnow().isoformat("T"),
        workspace=ws1,
        run=r,
        description="execution example",
    )
    print("An execution was created with id %s" % exec.id)

    date_set_version = "data_set_version_" + str(uuid4())
    data_set = exec.log_input(
        metadata.DataSet(
            description="an example data",
            name="mytable-dump",
            owner="owner@my-company.org",
            uri="file://path/to/dataset",
            version=date_set_version,
            query="SELECT * FROM mytable"))
    print("Data set id is {0.id} with version '{0.version}'".format(data_set))


if __name__ == "__main__":
    work()

What did you expect to happen:

Create an execution and store the metadata.

Anything else you would like to add:
[Miscellaneous information that will assist in solving the issue.]

Running in a GCP managed service.

Environment:

• Metadata version:

kubeflow-metadata==0.3.1

• Kubeflow version:

Version: 1.0.0

• Minikube version:
• Kubernetes version: (use kubectl version):

Client Version: version.Info{Major:"1", Minor:"18", GitVersion:"v1.18.4", GitCommit:"c96aede7b5205121079932896c4ad89bb93260af", GitTreeState:"clean", BuildDate:"2020-06-17T11:41:22Z", GoVersion:"go1.13.9", Compiler:"gc", Platform:"linux/amd64"}
Server Version: version.Info{Major:"1", Minor:"16+", GitVersion:"v1.16.13-gke.1", GitCommit:"688c6543aa4b285355723f100302d80431e411cc", GitTreeState:"clean", BuildDate:"2020-07-21T02:37:26Z", GoVersion:"go1.13.9b4", Compiler:"gc", Platform:"linux/amd64"}

• OS (e.g. from /etc/os-release):

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[OrrAvrech]

Any updates?
Got the same error on a similar code, after accessing the metadata-grpc-deployment through an external IP.
Kubeflow was deployed using GCP's UI.

[souvik-deepsource]

@jlewi Any update on this? This is breaking for the demo notebook.

[harshit-deepsource]

@jlewi Same with me.

@montenegrodr did you find any workaround?

[montenegrodr]

@jlewi Same with me.

@montenegrodr did you find any workaround?

no

[souvik-deepsource]

@montenegrodr It's due to this issue.

[harshit-deepsource]

@montenegrodr

Try using Kubeflow v1.1.0 and it should work just fine. It worked for me.

[anupash147]

am using kubeflow v1.2.0 and still seeing the issue,,

[umka1332]

AFAIK Kubeflow metadata is deleted from Kubeflow v1.2.0 in favor of ML metadata since the first one is abandoned and the second one is supported by KFP. Please see:
#242 (comment)
#250
#225
Please correct me if Kubeflow metadata should work with Kubeflow v1.2.0.

[neuromage]

AFAIK Kubeflow metadata is deleted from Kubeflow v1.2.0 in favor of ML metadata since the first one is abandoned and the second one is supported by KFP.

That is correct @umka1332. The SDK in this repo is unmaintained, and so we decided to move to MLMD gRPC service for now.