A company with a video streaming website wants to analyze user behavior to make recommendations to users in real time Clickstream data is being sent to Amazon Kinesis Data Streams and reference data i

An AWS Glue Python shell job is not designed for continuous, high-throughput real-time stream processing from Kinesis Data Streams. It's typically used for lightweight, short-running scripts or orchestration, not for real-time analytics with SQL and reference data joins.

While AWS Glue streaming ETL jobs can process data from Kinesis Data Streams, Kinesis Data Analytics is specifically designed for real-time SQL-based stream processing. KDA offers a more direct and integrated approach for standard SQL queries and efficiently joining with S3 reference data within the streaming application itself.

This choice is a duplicate of D, which is the correct answer. Assuming this is a clerical error in the provided options and both refer to the same correct approach using Amazon Kinesis Data Analytics.

Amazon Kinesis Data Analytics (KDA) for Apache Flink allows processing real-time streaming data from Kinesis Data Streams using standard SQL (Flink SQL). It directly supports creating 'in-application' reference tables from static data stored in Amazon S3, enabling real-time lookups and joins with the incoming stream data for generating immediate recommendations, perfectly meeting all specified requirements.