A company currently has an application that writes data onto AWS RDS-MySQL.
They want to push data on a daily basis to archive records from MySQL tables to S3 for future analysis.
How can you accomplish this in the easiest way?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer - B.
A sample of this is given in the AWS Documentation.
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Export MySQL Data to Amazon S3 Using AWS Data Pipeline.
This tutorial walks you through the process of creating a data pipeline to copy data (rows) from a table in MySQL database to a CSV (comma-separated values) file in an Amazon S3 bucket and then sending an Amazon SNS notification after the copy activity completes successfully.
You will use an EC2 instance provided by AWS Data Pipeline for this copy activity.
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Option A is incorrect since the events can only trigger an event but not directly be used to ingest data.
Option C is incorrect since this would be not be cost effective option just to try to ingest data.
Option D is incorrect since the database migration service should ideally be used for a one time activity.
For more information on this tutorial, please visit the url.
https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-copydata-mysql.htmlOption A: Create an S3 event to ingest the data from the MySQL table This option is not a viable solution because S3 events are used to trigger Lambda functions or other AWS services when an object is created, modified or deleted in S3. It does not allow the ingestion of data from MySQL to S3. Therefore, option A is not a correct solution.
Option B: Use the AWS DataPipeline service and run a job on a daily basis AWS DataPipeline is a fully managed ETL service that enables the movement and transformation of data among different AWS services and on-premises data sources. With AWS DataPipeline, you can schedule regular data transfers from MySQL to S3 for archiving purposes. This option is the easiest way to accomplish this task. AWS DataPipeline supports various data formats and can be customized according to specific needs.
Option C: Create an EMR Cluster which will run a MapReduce job Amazon EMR is a fully managed cluster platform that simplifies running big data frameworks such as Apache Hadoop, Spark, and Presto on AWS. While EMR is a viable solution for processing large data sets, it is not the best solution for moving data from MySQL to S3. It requires more setup time and resources to create an EMR cluster, configure the job, and run it. Therefore, option C is not the easiest way to accomplish the task.
Option D: Use the database migration service to transfer the data. AWS Database Migration Service is a fully managed service that enables seamless migrations from various databases to AWS. It is not the best solution for transferring data from MySQL to S3 for archiving purposes. This service is primarily used for database migrations and not designed for data ingestion or transfer between different storage services. Therefore, option D is not a correct solution.
Conclusion: The best option to accomplish this task is to use AWS DataPipeline service and schedule regular data transfers from MySQL to S3 for archiving purposes. This solution is the easiest and most cost-effective method for archiving MySQL data to S3.