Kinesis Data Analytics SQL is configured to read a kinesis stream processing events that is generated by integration of data generated by the IOT devices.The support team wants to use the TIMESTAMP when the data was added to the in-application stream and redesign their time-based windowed queries.
Which of the below options provides relevant information? Select 2 options

Answer options:

A.ROWTIME
B.INGEST TIME
C.EVENT TIME
D.PROCESSING TIME

Answer : A, D
Option A is correct - ROWTIME stores a timestamp when Amazon Kinesis Data Analytics inserts a row in the first in-application stream. ROWTIME reflects the timestamp at which Amazon Kinesis Data Analytics inserted a record into the first in-application stream after reading from the streaming source. This ROWTIME value is then maintained throughout your application.
Amazon Kinesis Data Analytics guarantees that the ROWTIME values are monotonically increased. You use this timestamp in time-based windowed queries.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/timestamps-rowtime-concepts.html
Option B is incorrect - INGEST TIME is the timestamp of when record was added to the streaming source. Amazon Kinesis Data Streams includes a field called APPROXIMATE_ARRIVAL_TIME in every record that provides this timestamp. This is also sometimes referred to as the server-side time. This ingest time is often the close approximation of event time. the ingest time is rarely out of order, but it can occur due to the distributed nature of streaming data. Therefore, Ingest time is a mostly accurate and in-order reflection of the event time.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/timestamps-rowtime-concepts.html
Option C is incorrect - EVENT TIME is the timestamp when the event occurred. This is also sometimes called the client-side time. It is often desirable to use this time in analytics because it is the time when an event occurred. However, many event sources, such as mobile phones and web clients, do not have reliable clocks, which can lead to inaccurate times. In addition, connectivity issues can lead to records appearing on a stream not in the same order the events occurred.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/timestamps-rowtime-concepts.html
Option D is correct - PROCESSING TIME is the timestamp when Amazon Kinesis Data Analytics inserts a row in the first in-application stream. Amazon Kinesis Data Analytics provides this timestamp in the ROWTIME column that exists in each in-application stream. The processing time is always monotonically increasing. But it will not be accurate if your application falls behind. (If an application falls behind, the processing time does not accurately reflect the event time.) This ROWTIME is accurate in relation to the wall clock, but it might not be the time when the event actually occurred.
https://docs.aws.amazon.com/kinesisanalytics/latest/dev/timestamps-rowtime-concepts.html