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Effective Amazon Machine Learning by Alexis Perrier

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A brief tour of AWS Athena

In Athena, the data is not stored in a database; it remains in S3. When you create a table in Athena, you are creating an information layer that tells Athena where to find the data, how it is structured, and what format it is in. The schema in Athena is a logical namespace of objects. Once the data structure and location are known to Athena, you can query the data via standard SQL statements. 

Athena uses Hive Data Definition Language (DDL) to create or drop databases and tables (more information on Hive DDL can be found at https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL). Athena can understand multiple formats (CSV, TSV, JSON, and so on) through the use of serializer-deserializer (SerDes) libraries. ...

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