feat: logic to deploy dvt on Cloud Run

samples/run/Dockerfile

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+FROM python:3.9-slim
+
+# Allow statements and log messages to immediately appear in the Knative logs
+ENV PYTHONUNBUFFERED True
+
+# Copy local code to the container image.
+ENV APP_HOME /app
+WORKDIR $APP_HOME
+COPY . ./
+
+# Install production dependencies.
+RUN apt-get update \
+    && apt-get install gcc -y \
+    && apt-get clean
+RUN pip install --upgrade pip
+RUN pip install Flask gunicorn google_pso_data_validator
+
+# Oracle Dependencies
+# if you are using Oracle you should add .rpm files
+# under your license to a directory called oracle/
+# and then uncomment the setup below.
+
+# ENV ORACLE_SID oracle
+# ENV ORACLE_ODBC_VERSION 12.2
+# ENV ORACLE_HOME /usr/lib/oracle/${ORACLE_ODBC_VERSION}/client64
+
+# RUN pip install cx_Oracle
+# RUN apt-get -y install --fix-missing --upgrade vim alien unixodbc-dev wget libaio1 libaio-dev
+
+# COPY oracle/*.rpm ./
+# RUN alien -i *.rpm && rm *.rpm \
+#     && echo "/usr/lib/oracle/${ORACLE_ODBC_VERSION}/client64/lib/" > /etc/ld.so.conf.d/oracle.conf \
+#     && ln -s /usr/include/oracle/${ORACLE_ODBC_VERSION}/client64 $ORACLE_HOME/include \
+#     && ldconfig -v
+
+
+# Run the web service on container startup. Here we use the gunicorn
+# webserver, with one worker process and 8 threads.
+# For environments with multiple CPU cores, increase the number of workers
+# to be equal to the cores available.
+# Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
+CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 --timeout 0 main:app

samples/run/README.md

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+# Data Validation on Cloud Run
+
+### Quick Steps
+
+The dpeloyment logic is discussed in more detail below; however, to quickly
+deploy you follow follow this simple script:
+
+```
+export PROJECT_ID=<PROJECT-ID>
+./deploy.sh
+python3 test.py
+```
+
+### Build Docker Image
+
+You will need to build a Docker image to be used by Cloud Run. In order to add
+Teradata or Oracle, you will need to customize the Dockerfile and add your
+licensed utilities.
+
+```
+export PROJECT_ID=<PROJECT-ID>
+gcloud builds submit --tag gcr.io/${PROJECT_ID}/data-validation \
+    --project=${PROJECT_ID}
+```
+
+### Deploy to Cloud Run
+
+```
+gcloud run deploy --image gcr.io/${PROJECT_ID}/data-validation \
+    --project=${PROJECT_ID}
+```
+
+### Test Cloud Run Endpoint
+
+You can easily run a request via Python.  For a quick test, we have provided this logic in `test.py` to run a validation against a public BigQuery table. The example is similar and also shows how you can foward results to BigQuery from the Cloud Run job:
+
+```
+# 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.
+
+import os
+import re
+import requests
+
+PROJECT_ID = os.environ.get("PROJECT_ID")
+
+DESCRIBE_SERVICE = """
+gcloud run services describe {service_name} --region=us-central1 --project={project_id}
+"""
+
+
+def get_token():
+  with os.popen("gcloud auth print-identity-token") as cmd:
+    token = cmd.read().strip()
+
+  return token
+
+
+def get_cloud_run_url(service_name, project_id):
+  describe_service = DESCRIBE_SERVICE.format(service_name=service_name,
+                                             project_id=project_id)
+  with os.popen(describe_service) as service:
+    description = service.read()
+
+  return re.findall("URL:.*\n", description)[0].split()[1].strip()
+
+
+data = {
+    "source_conn": {
+        "source_type": "BigQuery",
+        "project_id": PROJECT_ID,
+    },
+    "target_conn": {
+        "source_type": "BigQuery",
+        "project_id": PROJECT_ID,
+    },
+    "type": "Column",
+    "schema_name": "bigquery-public-data.new_york_citibike",
+    "table_name": "citibike_stations",
+    "target_schema_name": "bigquery-public-data.new_york_citibike",
+    "target_table_name": "citibike_stations",
+    "result_handler": {
+      "type": "BigQuery",
+      "project_id": PROJECT_ID,
+      "table_id": "pso_data_validator.results"
+   },
+
+    "aggregates": [
+        {
+            "source_column": None,
+            "target_column": None,
+            "field_alias": "count",
+            "type": "count"
+        }],
+}
+
+url = get_cloud_run_url("data-validation", PROJECT_ID)
+res = requests.post(
+    url, headers={"Authorization": "Bearer " + get_token()}, json=data)
+print(res.content.decode())
+```
+
+### Oracle Setup
+
+If you would like to use Data Validation against an Oracle DB you will need to
+supply your own license files.  To do so:
+
+1) Create an `oracle` directory and add your .rpm files into it.
+
+- oracle/oracle-instantclient12.2-basiclite-12.2.0.1.0-1.x86_64.rpm
+- oracle/oracle-instantclient12.2-devel-12.2.0.1.0-1.x86_64.rpm
+- oracle/oracle-instantclient12.2-odbc-12.2.0.1.0-2.x86_64.rpm
+
+2) Uncomment all logic in the Dockerfile under the Oracle Dependencies comments
+

samples/run/deploy.sh

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+#!/bin/bash
+
+gcloud builds submit --tag gcr.io/${PROJECT_ID}/data-validation \
+    --project=${PROJECT_ID}
+gcloud run deploy data-validation --image gcr.io/${PROJECT_ID}/data-validation \
+    --region=us-central1 --project=${PROJECT_ID}

samples/run/main.py

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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.
+
+import json
+import os
+from data_validation import data_validation
+import flask
+import pandas
+
+app = flask.Flask(__name__)
+
+
+def _clean_dataframe(df):
+    rows = df.to_dict(orient="record")
+    for row in rows:
+        for key in row:
+            if type(row[key]) in [pandas.Timestamp]:
+                row[key] = str(row[key])
+
+    return json.dumps(rows)
+
+
+def _get_request_content(request):
+    return request.json
+
+
+def validate(config):
+    """Run Data Validation against the supplied config."""
+    validator = data_validation.DataValidation(config)
+    df = validator.execute()
+
+    return _clean_dataframe(df)
+
+
+def main(request):
+    """ Handle incoming Data Validation requests.
+
+        request (flask.Request): HTTP request object.
+    """
+    try:
+        config = _get_request_content(request)["config"]
+        return validate(config)
+    except Exception as e:
+        return "Unknown Error: {}".format(e)
+
+
+@app.route("/", methods=["POST"])
+def run():
+    try:
+        config = _get_request_content(flask.request)
+        result = validate(config)
+        return str(result)
+    except Exception as e:
+        print(e)
+        return "Found Error: {}".format(e)
+
+
+@app.route("/test", methods=["POST"])
+def other():
+    return _get_request_content(flask.request)
+
+
+if __name__ == "__main__":
+    app.run(debug=True, host="0.0.0.0", port=int(os.environ.get("PORT", 8080)))

samples/run/test.py

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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.
+
+import os
+import re
+import requests
+
+PROJECT_ID = os.environ.get("PROJECT_ID")
+
+DESCRIBE_SERVICE = """
+gcloud run services describe {service_name} --region=us-central1 --project={project_id}
+"""
+
+
+def get_token():
+    with os.popen("gcloud auth print-identity-token") as cmd:
+        token = cmd.read().strip()
+
+    return token
+
+
+def get_cloud_run_url(service_name, project_id):
+    describe_service = DESCRIBE_SERVICE.format(
+        service_name=service_name, project_id=project_id
+    )
+    with os.popen(describe_service) as service:
+        description = service.read()
+
+    return re.findall("URL:.*\n", description)[0].split()[1].strip()
+
+
+data = {
+    "source_conn": {"source_type": "BigQuery", "project_id": PROJECT_ID,},
+    "target_conn": {"source_type": "BigQuery", "project_id": PROJECT_ID,},
+    "type": "Column",
+    "schema_name": "bigquery-public-data.new_york_citibike",
+    "table_name": "citibike_stations",
+    "target_schema_name": "bigquery-public-data.new_york_citibike",
+    "target_table_name": "citibike_stations",
+    "aggregates": [
+        {
+            "source_column": None,
+            "target_column": None,
+            "field_alias": "count",
+            "type": "count",
+        }
+    ],
+}
+
+url = get_cloud_run_url("data-validation", PROJECT_ID)
+res = requests.post(url, headers={"Authorization": "Bearer " + get_token()}, json=data)
+print(res.content.decode())