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Components - Added more GCP BigQuery components (3914)
* Update _client.py * updated the gcp components * Update the GCP BigQuery Components * update the readme and component * updated components
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| # Name | ||
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| Gather data by querying BigQuery and save it in a CSV file. | ||
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| # Labels | ||
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| GCP, BigQuery, Kubeflow, Pipeline | ||
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| # Summary | ||
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| A Kubeflow Pipeline component to submit a query to BigQuery and store the result in a csv file avialble for other components to utalize. | ||
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| # Details | ||
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| ## Intended use | ||
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| Use this Kubeflow component to: | ||
| * Select training data by submitting a query to BigQuery. | ||
| * Output the training data into a CSV files. | ||
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| ## Runtime arguments: | ||
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| ## Runtime arguments: | ||
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| | Argument | Description | Optional | Data type | Accepted values | Default | | ||
| |----------|-------------|----------|-----------|-----------------|---------| | ||
| | query | The query used by BigQuery to fetch the results. | No | String | | | | ||
| | project_id | The project ID of the Google Cloud Platform (GCP) project to use to execute the query. | No | GCPProjectID | | | | ||
| | output_filename | The file name of the output file. | Yes | String | | bq_results.csv | | ||
| | job_config | The full configuration specification for the query job. See [QueryJobConfig](https://googleapis.github.io/google-cloud-python/latest/bigquery/generated/google.cloud.bigquery.job.QueryJobConfig.html#google.cloud.bigquery.job.QueryJobConfig) for details. | Yes | Dict | A JSONobject which has the same structure as [QueryJobConfig](https://googleapis.github.io/google-cloud-python/latest/bigquery/generated/google.cloud.bigquery.job.QueryJobConfig.html#google.cloud.bigquery.job.QueryJobConfig) | None | | ||
| ## Input data schema | ||
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| The input data is a BigQuery job containing a query that pulls data from various sources. | ||
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| ## Output: | ||
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| Name | Description | Type | ||
| :--- | :---------- | :--- | ||
| output_path | The path to the file containing the query output in CSV format. | OutputPath | ||
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| ## Cautions & requirements | ||
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| To use the component, the following requirements must be met: | ||
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| * The BigQuery API is enabled. | ||
| * The component can authenticate to GCP. Refer to [Authenticating Pipelines to GCP](https://www.kubeflow.org/docs/gke/authentication-pipelines/) for details. | ||
| * The Kubeflow user service account is a member of the `roles/bigquery.admin` role of the project. | ||
| * The Kubeflow user service account is a member of the `roles/storage.objectCreator `role of the Cloud Storage output bucket. | ||
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| ## Detailed description | ||
| This Kubeflow Pipeline component is used to: | ||
| * Submit a query to BigQuery. | ||
| * The query results are extracted and stored as a csv file locally avilable for other kubeflow components. | ||
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| Use the code below as an example of how to run your BigQuery job. | ||
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| ## Sample | ||
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| Note: The following sample code works in an IPython notebook or directly in Python code. | ||
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| #### Set sample parameters | ||
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| ```python | ||
| %%capture --no-stderr | ||
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| KFP_PACKAGE = 'https://storage.googleapis.com/ml-pipeline/release/0.1.14/kfp.tar.gz' | ||
| !pip3 install $KFP_PACKAGE --upgrade | ||
| ``` | ||
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| 2. Load the component using KFP SDK | ||
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| ```python | ||
| import kfp.components as comp | ||
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| bigquery_query_op = comp.load_component_from_url( | ||
| 'https://raw.githubusercontent.com/kubeflow/pipelines/01a23ae8672d3b18e88adf3036071496aca3552d/components/gcp/bigquery/query/to?gcs/component.yaml') | ||
| help(bigquery_query_op) | ||
| ``` | ||
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| ### Query | ||
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| In this sample, we send a query to get the top questions from stackdriver public data and output the data to CSV file which other components can access. Here is the query: | ||
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| ```python | ||
| QUERY = 'SELECT * FROM `bigquery-public-data.stackoverflow.posts_questions` LIMIT 10' | ||
| ``` | ||
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| #### Set sample parameters | ||
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| ```python | ||
| # Required Parameters | ||
| PROJECT_ID = '<Please put your project ID here>' | ||
| ``` | ||
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| ```python | ||
| # Optional Parameters | ||
| FILE_NAME = 'test.csv' | ||
| ``` | ||
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| #### Run the component as a single pipeline | ||
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| ```python | ||
| import kfp.dsl as dsl | ||
| import json | ||
| @dsl.pipeline( | ||
| name='Bigquery query pipeline', | ||
| description='Bigquery query pipeline' | ||
| ) | ||
| def pipeline( | ||
| query=QUERY, | ||
| project_id = PROJECT_ID, | ||
| output_filename=FILE_NAME | ||
| job_config='' | ||
| ): | ||
| bigquery_query_op( | ||
| query=query, | ||
| project_id=project_id, | ||
| job_config=job_config) | ||
| ``` | ||
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| #### Compile the pipeline | ||
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| ```python | ||
| pipeline_func = pipeline | ||
| pipeline_filename = pipeline_func.__name__ + '.zip' | ||
| import kfp.compiler as compiler | ||
| compiler.Compiler().compile(pipeline_func, pipeline_filename) | ||
| ``` | ||
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| #### Submit the pipeline for execution | ||
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| ```python | ||
| #Specify pipeline argument values | ||
| arguments = {} | ||
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| #Get or create an experiment and submit a pipeline run | ||
| import kfp | ||
| client = kfp.Client() | ||
| experiment = client.create_experiment(EXPERIMENT_NAME) | ||
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| #Submit a pipeline run | ||
| run_name = pipeline_func.__name__ + ' run' | ||
| run_result = client.run_pipeline(experiment.id, run_name, pipeline_filename, arguments) | ||
| ``` | ||
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| #### Use the output in a pipeline | ||
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| Small example on how to use the output form the component, here `read_csv` any component of interest that can consume a csv file. | ||
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| ```python | ||
| def pipeline( | ||
| query=QUERY, | ||
| project_id = PROJECT_ID, | ||
| job_config='' | ||
| ): | ||
| bq_out = bigquery_query( | ||
| query=query, | ||
| project_id=project_id, | ||
| output_filename=FILE_NAME, | ||
| job_config=job_config) | ||
| read_csv(input_path=bq_out.outputs["table"] + "/" + FILE_NAME) | ||
| ``` | ||
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| ## References | ||
| * [Component python code](https://github.com/kubeflow/pipelines/blob/master/components/gcp/container/component_sdk/python/kfp_component/google/bigquery/_query.py) | ||
| * [Component docker file](https://github.com/kubeflow/pipelines/blob/master/components/gcp/container/Dockerfile) | ||
| * [BigQuery query REST API](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) | ||
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| ## License | ||
| By deploying or using this software you agree to comply with the [AI Hub Terms of Service](https://aihub.cloud.google.com/u/0/aihub-tos) and the [Google APIs Terms of Service](https://developers.google.com/terms/). To the extent of a direct conflict of terms, the AI Hub Terms of Service will control. |
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| # Export to file for next processing step in pipeline | ||
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| # Copyright 2020 Google LLC | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
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| name: Bigquery - Query | ||
| description: | | ||
| A Kubeflow Pipeline component to submit a query to Google Cloud Bigquery and | ||
| store the results to a csv file. | ||
| metadata: | ||
| labels: | ||
| add-pod-env: 'true' | ||
| inputs: | ||
| - name: query | ||
| description: 'The query used by Bigquery service to fetch the results.' | ||
| type: String | ||
| - name: project_id | ||
| description: 'The project to execute the query job.' | ||
| type: GCPProjectID | ||
| - name: job_config | ||
| description: >- | ||
| The full config spec for the query job.See | ||
| [QueryJobConfig](https://googleapis.github.io/google-cloud-python/latest/bigquery/generated/google.cloud.bigquery.job.QueryJobConfig.html#google.cloud.bigquery.job.QueryJobConfig) | ||
| for details. | ||
| default: '' | ||
| type: Dict | ||
| - name: output_filename | ||
| description: 'The output file name' | ||
| default: 'bq_results.csv' | ||
| type: String | ||
| outputs: | ||
| - name: MLPipeline UI metadata | ||
| type: UI metadata | ||
| - name: table | ||
| description: 'The path to the result from BigQuery' | ||
| type: CSV | ||
| implementation: | ||
| container: | ||
| image: gcr.io/ml-pipeline/ml-pipeline-gcp | ||
| args: [ | ||
| --ui_metadata_path, {outputPath: MLPipeline UI metadata}, | ||
| kfp_component.google.bigquery, query, | ||
| --query, {inputValue: query}, | ||
| --project_id, {inputValue: project_id}, | ||
| --output_path, {outputPath: table}, | ||
| --output_filename, {inputValue: output_filename}, | ||
| --job_config, {inputValue: job_config}, | ||
| ] | ||
| env: | ||
| KFP_POD_NAME: "{{pod.name}}" |
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