System test for Dynamo DB to S3 (AIP-47)

docs/apache-airflow-providers-amazon/operators/transfer/dynamodb_to_s3.rst

@@ -48,7 +48,7 @@ To get more information visit:
 
 Example usage:
 
-.. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_dynamodb_to_s3.py
+.. exampleinclude:: /../../tests/system/providers/amazon/aws/example_dynamodb_to_s3.py
     :language: python
     :dedent: 4
     :start-after: [START howto_transfer_dynamodb_to_s3]
@@ -57,7 +57,7 @@ Example usage:
 To parallelize the replication, users can create multiple ``DynamoDBToS3Operator`` tasks using the
 ``TotalSegments`` parameter.  For instance to replicate with parallelism of 2, create two tasks:
 
-.. exampleinclude:: /../../airflow/providers/amazon/aws/example_dags/example_dynamodb_to_s3.py
+.. exampleinclude:: /../../tests/system/providers/amazon/aws/example_dynamodb_to_s3.py
     :language: python
     :dedent: 4
     :start-after: [START howto_transfer_dynamodb_to_s3_segmented]

tests/system/providers/amazon/aws/example_dynamodb_to_s3.py

@@ -0,0 +1,162 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+from __future__ import annotations
+
+from datetime import datetime
+
+import boto3
+
+from airflow.decorators import task
+from airflow.models.baseoperator import chain
+from airflow.models.dag import DAG
+from airflow.providers.amazon.aws.operators.s3 import S3CreateBucketOperator, S3DeleteBucketOperator
+from airflow.providers.amazon.aws.transfers.dynamodb_to_s3 import DynamoDBToS3Operator
+from airflow.utils.trigger_rule import TriggerRule
+from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
+
+DAG_ID = 'example_dynamodb_to_s3'
+
+sys_test_context_task = SystemTestContextBuilder().build()
+
+TABLE_ATTRIBUTES = [
+    {'AttributeName': 'ID', 'AttributeType': 'S'},
+    {'AttributeName': 'Value', 'AttributeType': 'S'},
+]
+TABLE_KEY_SCHEMA = [
+    {'AttributeName': 'ID', 'KeyType': 'HASH'},
+    {'AttributeName': 'Value', 'KeyType': 'RANGE'},
+]
+TABLE_THROUGHPUT = {'ReadCapacityUnits': 1, 'WriteCapacityUnits': 1}
+S3_KEY_PREFIX = 'dynamodb-segmented-file'
+
+
+@task
+def set_up_table(table_name: str):
+    dynamo_resource = boto3.resource('dynamodb')
+    table = dynamo_resource.create_table(
+        AttributeDefinitions=TABLE_ATTRIBUTES,
+        TableName=table_name,
+        KeySchema=TABLE_KEY_SCHEMA,
+        ProvisionedThroughput=TABLE_THROUGHPUT,
+    )
+    boto3.client('dynamodb').get_waiter('table_exists').wait(
+        TableName=table_name, WaiterConfig={'Delay': 10, 'MaxAttempts': 10}
+    )
+    table.put_item(Item={'ID': '123', 'Value': 'Testing'})
+
+
+@task
+def wait_for_bucket(s3_bucket_name):
+    waiter = boto3.client('s3').get_waiter('bucket_exists')
+    waiter.wait(Bucket=s3_bucket_name)
+
+
+@task(trigger_rule=TriggerRule.ALL_DONE)
+def delete_dynamodb_table(table_name: str):
+    boto3.resource('dynamodb').Table(table_name).delete()
+    boto3.client('dynamodb').get_waiter('table_not_exists').wait(
+        TableName=table_name, WaiterConfig={'Delay': 10, 'MaxAttempts': 10}
+    )
+
+
+with DAG(
+    dag_id=DAG_ID,
+    schedule='@once',
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
+    tags=['example'],
+) as dag:
+    test_context = sys_test_context_task()
+    env_id = test_context[ENV_ID_KEY]
+    table_name = f'{env_id}-dynamodb-table'
+    bucket_name = f'{env_id}-dynamodb-bucket'
+
+    create_table = set_up_table(table_name=table_name)
+
+    create_bucket = S3CreateBucketOperator(task_id='create_bucket', bucket_name=bucket_name)
+
+    # [START howto_transfer_dynamodb_to_s3]
+    backup_db = DynamoDBToS3Operator(
+        task_id='backup_db',
+        dynamodb_table_name=table_name,
+        s3_bucket_name=bucket_name,
+        # Max output file size in bytes.  If the Table is too large, multiple files will be created.
+        file_size=20,
+    )
+    # [END howto_transfer_dynamodb_to_s3]
+
+    # [START howto_transfer_dynamodb_to_s3_segmented]
+    # Segmenting allows the transfer to be parallelized into {segment} number of parallel tasks.
+    backup_db_segment_1 = DynamoDBToS3Operator(
+        task_id='backup_db_segment_1',
+        dynamodb_table_name=table_name,
+        s3_bucket_name=bucket_name,
+        # Max output file size in bytes.  If the Table is too large, multiple files will be created.
+        file_size=1000,
+        s3_key_prefix=f'{S3_KEY_PREFIX}-1-',
+        dynamodb_scan_kwargs={
+            "TotalSegments": 2,
+            "Segment": 0,
+        },
+    )
+
+    backup_db_segment_2 = DynamoDBToS3Operator(
+        task_id="backup_db_segment_2",
+        dynamodb_table_name=table_name,
+        s3_bucket_name=bucket_name,
+        # Max output file size in bytes.  If the Table is too large, multiple files will be created.
+        file_size=1000,
+        s3_key_prefix=f'{S3_KEY_PREFIX}-2-',
+        dynamodb_scan_kwargs={
+            "TotalSegments": 2,
+            "Segment": 1,
+        },
+    )
+    # [END howto_transfer_dynamodb_to_s3_segmented]
+    delete_table = delete_dynamodb_table(table_name=table_name)
+
+    delete_bucket = S3DeleteBucketOperator(
+        task_id='delete_bucket',
+        bucket_name=bucket_name,
+        trigger_rule=TriggerRule.ALL_DONE,
+        force_delete=True,
+    )
+
+    chain(
+        # TEST SETUP
+        test_context,
+        create_table,
+        create_bucket,
+        wait_for_bucket(s3_bucket_name=bucket_name),
+        # TEST BODY
+        backup_db,
+        backup_db_segment_1,
+        backup_db_segment_2,
+        # TEST TEARDOWN
+        delete_table,
+        delete_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)
+test_run = get_test_run(dag)