Source code for tests.system.providers.amazon.aws.example_glue_data_quality

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from __future__ import annotations

from datetime import datetime

from airflow import DAG
from airflow.decorators import task, task_group
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.hooks.glue import GlueDataQualityHook
from airflow.providers.amazon.aws.operators.athena import AthenaOperator
from airflow.providers.amazon.aws.operators.glue import (
    GlueDataQualityOperator,
    GlueDataQualityRuleSetEvaluationRunOperator,
)
from airflow.providers.amazon.aws.operators.s3 import (
    S3CreateBucketOperator,
    S3CreateObjectOperator,
    S3DeleteBucketOperator,
)
from airflow.providers.amazon.aws.sensors.glue import GlueDataQualityRuleSetEvaluationRunSensor
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.amazon.aws.utils import SystemTestContextBuilder

[docs]ROLE_ARN_KEY = "ROLE_ARN"
[docs]sys_test_context_task = SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()
[docs]DAG_ID = "example_glue_data_quality"
[docs]SAMPLE_DATA = """"Alice",20 "Bob",25 "Charlie",30"""
[docs]SAMPLE_FILENAME = "airflow_sample.csv"
[docs]RULE_SET = """ Rules = [ RowCount between 2 and 8, IsComplete "name", Uniqueness "name" > 0.95, ColumnLength "name" between 3 and 14, ColumnValues "age" between 19 and 31 ] """
@task_group
[docs]def glue_data_quality_workflow(): # [START howto_operator_glue_data_quality_operator] create_rule_set = GlueDataQualityOperator( task_id="create_rule_set", name=rule_set_name, ruleset=RULE_SET, data_quality_ruleset_kwargs={ "TargetTable": { "TableName": athena_table, "DatabaseName": athena_database, } }, ) # [END howto_operator_glue_data_quality_operator] # [START howto_operator_glue_data_quality_ruleset_evaluation_run_operator] start_evaluation_run = GlueDataQualityRuleSetEvaluationRunOperator( task_id="start_evaluation_run", datasource={ "GlueTable": { "TableName": athena_table, "DatabaseName": athena_database, } }, role=test_context[ROLE_ARN_KEY], rule_set_names=[rule_set_name], ) # [END howto_operator_glue_data_quality_ruleset_evaluation_run_operator] start_evaluation_run.wait_for_completion = False # [START howto_sensor_glue_data_quality_ruleset_evaluation_run] await_evaluation_run_sensor = GlueDataQualityRuleSetEvaluationRunSensor( task_id="await_evaluation_run_sensor", evaluation_run_id=start_evaluation_run.output, ) # [END howto_sensor_glue_data_quality_ruleset_evaluation_run] chain(create_rule_set, start_evaluation_run, await_evaluation_run_sensor)
@task(trigger_rule=TriggerRule.ALL_DONE)
[docs]def delete_ruleset(ruleset_name): hook = GlueDataQualityHook() hook.conn.delete_data_quality_ruleset(Name=ruleset_name)
with DAG( dag_id=DAG_ID, schedule="@once", start_date=datetime(2021, 1, 1), tags=["example"], catchup=False, ) as dag:
[docs] test_context = sys_test_context_task()
env_id = test_context["ENV_ID"] rule_set_name = f"{env_id}-system-test-ruleset" s3_bucket = f"{env_id}-glue-dq-athena-bucket" athena_table = f"{env_id}_test_glue_dq_table" athena_database = f"{env_id}_glue_dq_default" query_create_database = f"CREATE DATABASE IF NOT EXISTS {athena_database}" query_create_table = f"""CREATE EXTERNAL TABLE IF NOT EXISTS {athena_database}.{athena_table} ( `name` string, `age` int ) ROW FORMAT SERDE "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe" WITH SERDEPROPERTIES ( "serialization.format" = ",", "field.delim" = "," ) LOCATION "s3://{s3_bucket}//{athena_table}" TBLPROPERTIES ("has_encrypted_data"="false") """ query_read_table = f"SELECT * from {athena_database}.{athena_table}" query_drop_table = f"DROP TABLE IF EXISTS {athena_database}.{athena_table}" query_drop_database = f"DROP DATABASE IF EXISTS {athena_database}" create_s3_bucket = S3CreateBucketOperator(task_id="create_s3_bucket", bucket_name=s3_bucket) upload_sample_data = S3CreateObjectOperator( task_id="upload_sample_data", s3_bucket=s3_bucket, s3_key=f"{athena_table}/{SAMPLE_FILENAME}", data=SAMPLE_DATA, replace=True, ) create_database = AthenaOperator( task_id="create_database", query=query_create_database, database=athena_database, output_location=f"s3://{s3_bucket}/", sleep_time=1, ) create_table = AthenaOperator( task_id="create_table", query=query_create_table, database=athena_database, output_location=f"s3://{s3_bucket}/", sleep_time=1, ) drop_table = AthenaOperator( task_id="drop_table", query=query_drop_table, database=athena_database, output_location=f"s3://{s3_bucket}/", trigger_rule=TriggerRule.ALL_DONE, sleep_time=1, ) drop_database = AthenaOperator( task_id="drop_database", query=query_drop_database, database=athena_database, output_location=f"s3://{s3_bucket}/", trigger_rule=TriggerRule.ALL_DONE, sleep_time=1, ) delete_s3_bucket = S3DeleteBucketOperator( task_id="delete_s3_bucket", bucket_name=s3_bucket, force_delete=True, trigger_rule=TriggerRule.ALL_DONE, ) chain( # TEST SETUP test_context, create_s3_bucket, upload_sample_data, create_database, create_table, # TEST BODY glue_data_quality_workflow(), # TEST TEARDOWN delete_ruleset(rule_set_name), drop_table, drop_database, delete_s3_bucket, ) from tests.system.utils.watcher import watcher # This test needs watcher in order to properly mark success/failure # when "tearDown" task with trigger rule is part of the DAG list(dag.tasks) >> watcher() from tests.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)

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