L-Finance runs multiple java web applications to process their business transactions, uses Kinesis Data Streams as the integration backbone, The transactions in the stream is processed through Kinesis Analytics Java to further enrich the data and useful to perform time-series analytics and load into Redshift, feed real-time dashboards running on QuickSight, and create real-time metrics.
What kind of connectors, operations and processing mechanism is used by Kinesis Analytics Java? Select 3 options

Answer options:

A.Sources, Sinks, Asynchronous IO
B.Sources, Sinks, Channels, Agents
C.Apache Flume
D.Apache Flink
E.Transformation and Aggregation
F.Format Conversion and Accumulation

Answer : A,D and E
With Amazon Kinesis Data Analytics for Java Applications, you can use Java to process and analyze streaming data. The service enables you to author and run Java code against streaming sources to perform time-series analytics, feed real-time dashboards, and create real-time metrics.
Build Java applications in Kinesis Data Analytics using open-source libraries based on Apache Flink. Apache Flink is a popular framework and engine for processing data streams.
Kinesis Data Analytics provides the underlying infrastructure for your Apache Flink applications. It handles core capabilities like provisioning compute resources, parallel computation, automatic scaling, and application backups (implemented as checkpoints and snapshots)
In Amazon Kinesis Data Analytics for Java Applications, connectors are software components that move data into and out of an Amazon Kinesis Data Analytics application. Connectors are flexible integrations that enable you to read from files and directors. Connectors consist of complete modules for interacting with AWS services and third-party systems.
Types of connectors include the following:
Sources: Provide data to your application from a Kinesis data stream, file, or other data source.
Sinks: Send data from your application to a Kinesis data stream, Kinesis Data Firehose delivery stream, or other data destination.
Asynchronous I/O: Provides asynchronous access to a data source (such as a database) to enrich stream events.
To transform incoming data in a Kinesis Data Analytics for Java application, you use an Apache Flink operator. An Apache Flink operator transforms one or more data streams into a new data stream. The new data stream contains modified data from the original data stream. Kinesis Applications for Java supports
Transform Operators
Aggregation Operators
https://docs.aws.amazon.com/kinesisanalytics/latest/java/what-is.html
https://docs.aws.amazon.com/kinesisanalytics/latest/java/how-operators.html