A comprehensive and detailed explanation is:
Option A is correct because using batch writes to write multiple log events in a single write operation
is a recommended practice for optimizing the performance and cost of data ingestion in Timestream.
Batch writes can reduce the number of network round trips and API calls, and can also take
advantage of parallel processing by Timestream. Batch writes can also improve the compression ratio
of data in the memory store and the magnetic store, which can reduce the storage costs and improve
the query performance1.
Option B is incorrect because writing each log event as a single write operation is not a
recommended practice for optimizing the performance and cost of data ingestion in Timestream.
Writing each log event as a single write operation would increase the number of network round trips
and API calls, and would also reduce the compression ratio of data in the memory store and the
magnetic store. This would increase the storage costs and degrade the query performance1.
Option C is incorrect because treating each log as a single-measure record is not a recommended
practice for optimizing the query performance in Timestream. Treating each log as a single-measure
record would result in creating multiple records for each timestamp, which would increase the
storage size and the query latency. Moreover, treating each log as a single-measure record would
require using joins to query multiple measures for the same timestamp, which would add complexity
and overhead to the query processing2.
Option D is correct because treating each log as a multi-measure record is a recommended practice
for optimizing the query performance in Timestream. Treating each log as a multi-measure record
would result in creating a single record for each timestamp, which would reduce the storage size and
the query latency. Moreover, treating each log as a multi-measure record would allow querying
multiple measures for the same timestamp without using joins, which would simplify and speed up
the query processing2.
Option E is incorrect because configuring the memory store retention period to be longer than the
magnetic store retention period is not a valid option in Timestream. The memory store retention
period must always be shorter than or equal to the magnetic store retention period. This ensures
that data is moved from the memory store to the magnetic store before it expires out of the memory
store3.
Option F is correct because configuring the memory store retention period to be shorter than the
magnetic store retention period is a valid option in Timestream. The memory store retention period
determines how long data is kept in the memory store, which is optimized for fast point-in-time
queries. The magnetic store retention period determines how long data is kept in the magnetic store,
which is optimized for fast analytical queries. By configuring these retention periods appropriately,
you can balance your storage costs and query performance according to your application needs3.
