Amazon Athena is a serverless SQL query service designed for high execution speed and interactive use, supporting complex queries and various data formats stored in Amazon S3. It automates query parallelization and provides a cost-effective pay-per-query pricing model based on data scanned. However, users should be aware of certain limitations, such as the lack of support for user-defined functions and potential costs for canceled queries.

1. Amazon Athena overview
S o f t w a r e E n g i n e e r a t E P A M
R a m a n M a s k a l e n k a
3 0 Н О Я Б Р Я

2. © 2019 EPAM Systems, Inc.
Table of context
A M A Z O N A T H E N A O V E R V I E W
S U P P O R T E D D A T A T Y P E S
T E C H N O L O G I E S U N D E R T H E H O O D
S I M P L E U S E C A S E
I N T E G R A T I O N W I T H O T H E R S E R V I C E S
T H I N G S T O C O N S I D E R W H I L E U S I N G
A T H E N A
2

3. © 2019 EPAM Systems, Inc.
Amazon Athena Overview
• Serverless
• No need of setting up an infrastructure
• Zero Spin up time
• Transparent upgrades
• Interactive
• High execution speed of queries
• Descriptive error messages
SERVERLESS INTERACTIVE HIGHLY AVAILABLE SQL QUERY SERVICE

4. © 2019 EPAM Systems, Inc.
Amazon Athena Overview
• Highly available
• Athena uses warm compute pools across multiple Availability Zones
• Your data is stored in S3 which is also designed for availability
• Core effective
• Automatically parallelize queries
• Results are streamed to console
• Tuned for performance
SERVERLESS INTERACTIVE HIGHLY AVAILABLE SQL QUERY SERVICE

5. © 2019 EPAM Systems, Inc.
Amazon Athena Overview
• Uses ANSI SQL
• Supports complex joins, nested queries and window functions
• Supports Complex data types (arrays, structs)
• Supports partitioning by almost any key, except datetime timestamp
• Cost effective
• Pay per query
• $5 per TB scanned
SERVERLESS INTERACTIVE HIGHLY AVAILABLE SQL QUERY SERVICE

6. © 2019 EPAM Systems, Inc.
Supported data types
• Text files (CSV, raw)
• Apache Web Logs, TSV
• JSON (simple, nested)
• Compressed files
• Apache parquet & Apache ORC

7. © 2019 EPAM Systems, Inc.
Technologies under the hood
Originally created by Facebook for their data
analysis to run interactive queries on large
amount of data.
• In-memory distributed query engine, ANSI-
SQL compatible with extensions
• Used by Athena for SQL queries
7
Data warehouse software project built on top of
Apache Hadoop for providing data query and
analysis. Allows to run SQL queries over
distributed data.
• Used by Athena for Data definition language
(DDL) functionality
• Supports complex datatypes and multiple
formats
• Supports partitioning

8. © 2019 EPAM Systems, Inc.
Simple use case
8

9. © 2019 EPAM Systems, Inc.
Simple use case
9

10. © 2019 EPAM Systems, Inc.
Integration with other services
10

11. © 2019 EPAM Systems, Inc.
Things to consider while using Athena
• No data transformation is made in S3
• You can write complex regexes for table creation
• You don’t pay for data transformation
• You can store your data in compressed format to lower the costs
• Rich access control (IAM, ACL, S3 bucket policies)
• Can be integrated with a lot of Business intelligence (BI) tools
PROS

12. © 2019 EPAM Systems, Inc.
Things to consider while using Athena
• Canceled queries will cost money for the data scanned
• Queries are rounded up to the nearest MB, with a 10 MB minimum.
• Query execution cost will consist of S3 data read + Athena scanned data rates
• Not all Hive DDL’s are supported by Athena
• Hive or Presto transactions are not supported by Athena
• User-defined functions and stored procedures are not supported
CONS

13. © 2019 EPAM Systems, Inc.

14. © 2019 EPAM Systems, Inc.