Files from multiple data sources arrive in an Amazon S3 bucket on a regular basis. A data engineer wants to ingest new files into Amazon Redshift in near real time when the new files arrive in the S3 bucket. Which solution will meet these requirements?
Which of the following suggestions would be the most effective for maintaining query performance in DynamoDB at scale?
What is the most efficient and transactionally consistent approach for applying these updates?
Which AWS service should the company use to meet these requirements?
A data engineer wants to orchestrate a set of extract, transform, and load (ETL) jobs that run on AWS. The
ETL jobs contain tasks that must run Apache Spark jobs on Amazon EMR, make API calls to Salesforce, and
load data into Amazon Redshift.
The ETL jobs need to handle failures and retries automatically. The data engineer needs to use Python to
orchestrate the jobs.
Which service will meet these requirements?
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