Exam AWS Certified Data Analytics - Specialty topic 1 question 79 discussion

ANSWER:B,C,F OPTION B: Add a key prefix of the form date=year-month-day/ to the S3 objects to partition the data. EXPLAINATION: Your Amazon S3 bucket can support 3,500 PUT/COPY/POST/DELETE or 5,500 GET/HEAD requests per second per partitioned prefix.So with every partition prefix we get additional support and that is why it is wise to add prefix especially when we have large set of data . LINK:https://aws.amazon.com/premiumsupport/knowledge-center/s3-object-key-naming-pattern/ OPTION C:Convert the log files to Apache Parquet format. EXPLAINATION:Parquet format is columnar based and which improves your query performance when done for Athena . OPTION:F:Drop and recreate the table with the PARTITIONED BY clause. Run the MSCK REPAIR TABLE statement. EXPLAINATION:MSCK REPAIR TABLE compares the partitions in the table metadata and the partitions in S3. If new partitions are present in the S3 location that you specified when you created the table, it adds those partitions to the metadata and to the Athena table.

Details why B and not D https://docs.aws.amazon.com/athena/latest/ug/partitions.html

BCF: I passed the test

ANSWER: B,C,F

initially went with BCE but E is wrong as Athena favors "=" hive style partition year=2021/month=01/day=26/ with MSCK repair for non-hive partition style data/2021/01/26/ have to use ALTER TABLE

ans is B,C,F

B, C, F is the answer. C, D, E is a valid solution, but would in this case be more work. MSCK REPAIR TABLE scans through the directories on S3 to find partitions, but requires Hive-style partitioning, i. e. date=Y-M-D. You should almost never rely on MSCK REPAIR TABLE, it’s extremely inefficient, but the docs are full of examples using it so an exam would be too. The real way to do this is to use a Y-M-D/ partitioning scheme and partition projection.

Can anyone please explain why B and not D? I understand C&F.

B, C, F