A company has 10-15 ТВ of uncompressed .csv files in Amazon S3. The company is evaluating Amazon Athena as a one-time query engine. The company wants to transform the data to optimize query runtime an

The correct answer is C. Apache Parquet compressed with Snappy. Apache Parquet compressed with Snappy is the optimal format for Athena. Parquet is a columnar format that allows Athena to scan only the columns needed by a query, drastically reducing data read and query time. Snappy compression provides a good balance of fast decompression spee

Storage and Data Management

Question

A company has 10-15 ТВ of uncompressed .csv files in Amazon S3. The company is evaluating Amazon Athena as a one-time query engine. The company wants to transform the data to optimize query runtime and storage costs. Which option for data format and compression meets these requirements?

Options

ACSV compressed with zip
BJSON compressed with bzip2
CApache Parquet compressed with Snappy
DApache Avro compressed with LZO

How the community answered

(59 responses)

A
3% (2)
B
10% (6)
C
81% (48)
D
5% (3)

Explanation

Apache Parquet compressed with Snappy is the optimal format for Athena. Parquet is a columnar format that allows Athena to scan only the columns needed by a query, drastically reducing data read and query time. Snappy compression provides a good balance of fast decompression speed (important for query latency) and reasonable compression ratios, and it supports splittability for parallel processing. CSV with zip (A) is neither columnar nor splittable - zip is not splittable, so parallelism is limited. JSON with bzip2 (B) is row-based and while bzip2 is splittable, JSON is not efficient for analytics. Apache Avro with LZO (D) is row-based, making it unsuitable for column-selective analytical queries.

Topics

#Data Formats#Data Compression#Amazon Athena#Query Optimization

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