In this article, we will see how a user can start a trigger in AWS Glue Data Catalog.
Example
Problem Statement: Use boto3 library in Python to start a trigger.
Approach/Algorithm to solve this problem
Step 1: Import boto3 and botocore exceptions to handle exceptions.
Step 2: trigger_name is the parameter in this function.
Step 3: Create an AWS session using boto3 lib. Make sure region_name is mentioned in the default profile. If it is not mentioned, then explicitly pass the region_name while creating the session.
Step 4: Create an AWS client for glue.
Step 5: Now use the start_trigger function and pass the parameter trigger_name as Name.
Step 6: It returns the response metadata and starts the triggers irrespective of its schedule.
Step 7: Handle the generic exception if something went wrong while starting a trigger.
Example Code
The following code starts a trigger in AWS Glue Data Catalog −
import boto3 from botocore.exceptions import ClientError def start_a_trigger(trigger_name) session = boto3.session.Session() glue_client = session.client('glue') try: response = glue_client.start_trigger(Name=trigger_name) return response except ClientError as e: raise Exception("boto3 client error in start_a_trigger: " + e.__str__()) except Exception as e: raise Exception("Unexpected error in start_a_trigger: " + e.__str__()) print(start_a_trigger("test-daily"))
Output
{'Name': 'test-daily', 'ResponseMetadata': {'RequestId': 'b2109689-*******************-d', 'HTTPStatusCode': 200, 'HTTPHeaders': {'date': 'Sun, 28 Mar 2021 08:00:04 GMT', 'content-type': 'application/x-amz-json-1.1', 'content-length': '26', 'connection': 'keep-alive', 'x-amzn-requestid': 'b2109689-***********************-d'}, 'RetryAttempts': 0}}