Running SQL queries using Amazon Athena
You can run SQL queries using Amazon Athena on data sources that are registered with the
AWS Glue Data Catalog and data sources such as Hive metastores and Amazon DocumentDB instances that you connect
to using the Athena Federated Query feature. For more information about working with data sources, see
Connecting to data sources. When you
run a Data Definition Language (DDL) query that modifies schema, Athena writes the metadata
to the metastore associated with the data source. In addition, some queries, such as
CREATE TABLE AS
and INSERT INTO
can write records to the
dataset—for example, adding a CSV record to an Amazon S3 location. When you run a query,
Athena saves the results of a query in a query result location that you specify. This allows
you to view query history and to download and view query results sets.
This section provides guidance for running Athena queries on common data sources and data
types using a variety of SQL statements. General guidance is provided for working with
common structures and operators—for example, working with arrays, concatenating,
filtering, flattening, and sorting. Other examples include queries for data in tables with
nested structures and maps, tables based on JSON-encoded datasets, and datasets associated
with AWS services such as AWS CloudTrail logs and Amazon EMR logs. Comprehensive coverage of standard
SQL usage is beyond the scope of this documentation. For more information about SQL, refer
to the Trino
Topics
- Viewing query plans
- Query results and recent queries
- Reusing query results
- Viewing query stats
- Working with views
- Using saved queries
- Using parameterized queries
- Handling schema updates
- Querying arrays
- Querying geospatial data
- Querying JSON
- Using ML with Athena
- Querying with UDFs
- Querying across regions
- Querying AWS Glue Data Catalog
- Querying AWS service logs
- Querying web server logs
For considerations and limitations, see Considerations and limitations for SQL queries in Amazon Athena.