Amazon Athena service overview and things to consider when choosing Athena Service. Презентация подготовлена по материалам выступления Романа Москаленко на витебской конференции “Developer's Software Conference” (30.11.2019).

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

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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
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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

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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

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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

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Supported data types
• Text files (CSV, raw)
• Apache Web Logs, TSV
• JSON (simple, nested)
• Compressed files
• Apache parquet & Apache ORC

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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
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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

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Simple use case
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Simple use case
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Integration with other services
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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

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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

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