Release notes - Amazon Athena

Release notes

Describes Amazon Athena features, improvements, and bug fixes by release date.

Athena release notes for 2022

November 18, 2022

Published on 2022-11-18

You can now use the Amazon Athena connector for IBM Db2 to query Db2 from Athena. For example, you can run analytical queries over a data warehouse on Db2 and a data lake in Amazon S3.

The Amazon Athena Db2 connector exposes several configuration options through Lambda environment variables. For information about configuration options, parameters, connection strings, deployment, and limitations, see Amazon Athena IBM Db2 connector.

November 17, 2022

Published on 2022-11-17

Apache Iceberg support in Athena engine version 3 now offers the following enhanced ACID transaction features:

  • ORC and Avro support – Create Iceberg tables using the Apache Avro and Apache ORC row and column-based file formats. Support for these formats is in addition to the existing support for Parquet.

  • MERGE INTO – Use the MERGE INTO command to merge data at scale efficiently. MERGE INTO combines the INSERT, UPDATE, and DELETE operations into one transaction. This reduces the processing overhead in your data pipeline and takes less SQL to write. For more information, see Updating Iceberg table data and MERGE INTO.

  • CTAS and VIEW support – Use the CREATE TABLE AS SELECT (CTAS) and CREATE VIEW statements with Iceberg tables. For more information, see CREATE TABLE AS and CREATE VIEW.

  • VACUUM support – You can use the VACUUM statement to optimize your data lake by deleting snapshots and data that are no longer required. You can use this feature to improve read performance and meet regulatory requirements like GDPR. For more information, see Optimizing Iceberg tables and VACUUM.

These new features require Athena engine version 3 and are available in all Regions where Athena is supported. You can use them with the Athena console, drivers, or API.

For information about using Iceberg in Athena, see Using Iceberg tables.

November 14, 2022

Published on 2022-11-14

Amazon Athena now supports IPv6 endpoints for inbound connections that you can use to invoke Athena functions over IPv6. You can use this feature to meet IPv6 compliance requirements. It also removes the need for additional networking equipment to handle address translation between IPv4 and IPv6.

To use this feature, configure your applications to use the new Athena dual-stack endpoints, which support both IPv4 and IPv6. Dual-stack endpoints use the format athena.region.api.aws. For example, the dual-stack endpoint in the US East (N. Virginia) Region is athena.us-east-1.api.aws.

When you make a request to a dual-stack Athena endpoint, the endpoint resolves to an IPv6 or an IPv4 address depending on the protocol used by your network and client. To connect programmatically to an AWS service, you can use the AWS CLI or AWS SDK to specify an endpoint.

For more information on service endpoints, see AWS service endpoints. To learn more about Athena's service endpoints, see Amazon Athena endpoints and quotas in the AWS documentation.

You can use the new Athena dual-stack endpoints for inbound connections at no additional cost. Dual-stack endpoints are generally available in all AWS Regions except the China (Beijing), China (Ningxia), and AWS GovCloud (US) Regions.

November 11, 2022

Published on 2022-11-11

Athena announces the following fixes and improvements.

  • Expanded Lake Formation fine-grained access control – You can now use AWS Lake Formation fine-grained access control policies in Athena queries for data stored in any supported file or table format. You can use fine-grained access control in Lake Formation to restrict access to data in query results using data filters to achieve column-level, row-level, and cell-level security. Supported table formats in Athena include Apache Iceberg, Apache Hudi, and Apache Hive. Expanded fine-grained access control is available in all regions supported by Athena. The expanded table and file format support requires Athena engine version 3, which offers new features and improved query performance, but does not change how you set up fine-grained access control policies in Lake Formation.

    Use of this expanded fine-grained access control in Athena has the following considerations:

    For information about using fine-grained access control in Lake Formation, see Manage fine-grained access control using AWS Lake Formation in the AWS Big Data Blog.

  • Athena Federated Query – Athena Federated Query now preserves the original casing of field names in struct objects. Previously, struct field names were automatically made lower case.

November 8, 2022

Published on 2022-11-08

You can now use the query result reuse caching feature to accelerate repeat queries in Athena. A repeat query is a SQL query identical to one submitted just recently that produces the same results. When you need to run identical multiple queries, result reuse caching can decrease the time required to produce results. Result reuse caching also lowers costs by reducing the number of bytes scanned.

For more information, see Reusing query results.

October 13, 2022

Published on 2022-10-13

Athena announces Athena engine version 3.

Athena has upgraded its SQL query engine to include the latest features from the Trino open source project. In addition to supporting all the features of Athena engine version 2, Athena engine version 3 includes over 50 new SQL functions, 30 new features, and more than 90 query performance improvements. With today’s launch, Athena is also introducing a continuous integration approach to open source software management that improves currency with the Trino and Presto projects so that you get faster access to community improvements, integrated and tuned within the Athena engine.

For more information, see Athena engine version 3.

October 10, 2022

Published on 2022-10-10

Athena releases JDBC driver version 2.0.33. The JDBC 2.0.33 driver includes the following changes:

  • New driver version, JDBC version, and plugin name properties were added to the user-agent string in the credentials provider class.

  • Error messages were corrected and necessary information added.

  • Prepared statements are now deallocated if the connection is closed or the Athena prepared statement execution fails.

For more information, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver.

September 23, 2022

Published on 2022-09-26

The Amazon Athena Neptune connector now supports case insensitive matching on column and table names.

  • The Neptune data source connector can resolve column names on Neptune tables that use casing even if the column names are all lower cased in the table in AWS Glue. To enable this behavior, set the enable_caseinsensitivematch environment variable to true on the Neptune connector Lambda function.

  • Because AWS Glue supports only lower case table names, when you create a AWS Glue table for Neptune, specify the AWS Glue table parameter "glabel" = table_name.

For more information about the Neptune connector, see Amazon Athena Neptune connector.

September 13, 2022

Published on 2022-09-13

Athena announces the following fixes and improvements.

  • External Hive metastore – Athena now returns NULL instead of throwing an exception when a WHERE clause includes a partition that doesn't exist in an external Hive metastore (EHMS). The new behavior matches that of the AWS Glue Data Catalog.

  • Parameterized queries – Values in parameterized queries can now be cast to the DOUBLE data type.

  • Apache Iceberg – Write operations to Iceberg tables now succeed when Object Lock is enabled on an Amazon S3 bucket.

August 31, 2022

Published on 2022-08-31

Amazon Athena announces availability of Athena and its features in the Asia Pacific (Jakarta) Region.

This release expands Athena's availability in Asia Pacific to include Asia Pacific (Hong Kong), Asia Pacific (Jakarta), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo). For a complete list of AWS services available in these and other Regions, refer to the AWS Regional Services List.

August 23, 2022

Published on 2022-08-23

Release v2022.32.1 of the Athena Query Federation SDK includes the following changes:

  • Added support to the Amazon Athena Oracle data source connector for SSL based connections to Amazon RDS instances. Support is limited to the Transport Layer Security (TLS) protocol and to authentication of the server by the client. Because mutual authentication it is not supported in Amazon RDS, the update does not include support for mutual authentication.

    For more information, see Amazon Athena Oracle connector.

August 3, 2022

Published on 2022-08-03

Athena releases JDBC driver version 2.0.32. The JDBC 2.0.32 driver includes the following changes:

  • The User-Agent string sent to the Athena SDK has been extended to contain the driver version, JDBC specification version, and the name of the authentication plugin.

  • Fixed a NullPointerException that was thrown when no value was provided for the CheckNonProxyHost parameter.

  • Fixed an issue with login_url parsing in the BrowserSaml authentication plugin.

  • Fixed a proxy host issue that occurred when the UseProxyforIdp parameter was set to true.

For more information, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver.

August 1, 2022

Published on 2022-08-01

Athena announces improvements to the Athena Query Federation SDK and Athena prebuilt data source connectors. The improvements include the following:

  • Struct parsing – Fixed a GlueFieldLexer parsing issue in the Athena Query Federation SDK that prevented certain complicated structs from displaying all of their data. This issue affected connectors built on the Athena Query Federation SDK.

  • AWS Glue tables – Added additional support for the set and decimal column types in AWS Glue tables.

  • DynamoDB connector – Added the ability to ignore casing on DynamoDB attribute names. For more information, see the disable_projection_and_casing section of the Amazon Athena DynamoDB connector documentation on GitHub.

For more information, see Release v2022.30.2 of Athena Query Federation on GitHub.

July 21, 2022

Published on 2022-07-21

You can now analyze and debug your queries using performance metrics and interactive, visual query analysis tools in the Athena console. The query performance data and execution details can help you identify bottlenecks in queries, inspect the operators and statistics for each stage of a query, trace the volume of data flowing between stages, and validate the impact of query predicates. You can now:

  • Access the distributed and logical execution plan for your query in a single click.

  • Explore the operations at each stage before the stage is run.

  • Visualize the performance of completed queries with metrics for time spent in the queuing, planning, and execution stages.

  • Get information about the number of rows and amount of source data processed and output by your query.

  • See granular execution details for your queries presented in context and formatted as an interactive graph.

  • Use precise, stage-level execution details to understand the flow of data through your query.

  • Analyze query performance data programmatically using new APIs to get query runtime statistics, also released today.

To learn how to use these capabilities on your queries, watch the video tutorial Optimize Amazon Athena Queries with New Query Analysis Tools on the AWS YouTube channel.

For documentation, see Viewing execution plans for SQL queries and Viewing statistics and execution details for completed queries.

July 11, 2022

Published on 2022-07-11

You can now run parameterized queries directly from the Athena console or API without preparing SQL statements in advance.

When you run queries in the Athena console that have parameters in the form of question marks, the user interface now prompts you to enter values for the parameters directly. This eliminates the need to modify literal values in the query editor every time you want to run the query.

If you use the enhanced query execution API, you can now provide the execution parameters and their values in a single call.

For more information, see Using parameterized queries in this user guide and the AWS Big Data Blog post Use Amazon Athena parameterized queries to provide data as a service.

July 8, 2022

Published on 2022-07-08

Athena announces the following fixes and improvements.

  • Fixed an issue with DATE column conversion handling for SageMaker endpoints (UDF) that was causing query failures.

June 6, 2022

Published on 2022-06-06

Athena releases JDBC driver version 2.0.31. The JDBC 2.0.31 driver includes the following changes:

  • log4j dependency issue – Resolved a Cannot find driver class error message caused by a log4j dependency.

For more information, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver.

May 25, 2022

Published on 2022-05-25

Athena announces the following fixes and improvements.

  • Iceberg support

    • Introduced support for cross-region queries. Now you can query Iceberg tables in an AWS Region that is different from the AWS Region that you are using.

    • Introduced support for server side encryption configuration. Now you can use SSE-S3/SSE-KMS to encrypt data from Iceberg write operations in Amazon S3.

    For more information about using Apache Iceberg in Athena, see Using Iceberg tables.

  • JDBC 2.0.30 driver release

    The JDBC 2.0.30 driver for Athena has the following improvements:

    • Fixes a data race issue that affected parameterized prepared statements.

    • Fixes an application start up issue that occurred in Gradle build environments.

    To download the JDBC 2.0.30 driver, release notes, and documentation, see Using Athena with the JDBC driver.

May 6, 2022

Published on 2022-05-06

Released the JDBC 2.0.29 and ODBC 1.1.17 drivers for Athena.

These drivers include the following changes:

  • Updated the SAML plugin browser launch process.

For more information about these changes, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver and Connecting to Amazon Athena with ODBC.

April 22, 2022

Published on 2022-04-22

Athena announces the following fixes and improvements.

  • Fixed an issue in the partition indices and filtering feature with the partition cache that occurred when the following conditions were met:

    • The partition_filtering.enabled key was set to true in the AWS Glue table properties for a table.

    • The same table was used multiple times with different partition filter values.

April 21, 2022

Published on 2022-04-21

You can now use Amazon Athena to run federated queries on new data sources, including Google BigQuery, Azure Synapse, and Snowflake. New data source connectors include:

For a complete list of data sources supported by Athena, see Using Athena data source connectors.

To make it easier to browse the available sources and connect to your data, you can now search, sort, and filter the available connectors from an updated Data Sources screen in the Athena console.

To learn about querying federated sources, see Using Amazon Athena Federated Query and Writing federated queries.

April 13, 2022

Published on 2022-04-13

Athena releases JDBC driver version 2.0.28. The JDBC 2.0.28 driver includes the following changes:

  • JWT support – The driver now supports JSON web tokens (JWT) for authentication. For information about using JWT with the JDBC driver, see the installation and configuration guide, downloadable from the JDBC driver page.

  • Updated Log4j libraries – The JDBC driver now uses the following Log4j libraries:

    • Log4j-api 2.17.1 (previously 2.17.0)

    • Log4j-core 2.17.1 (previously 2.17.0)

    • Log4j-jcl 2.17.2

  • Other improvements – The new driver also includes the following improvements and bug fixes:

    • The Athena prepared statements feature is now available through JDBC. For information about prepared statements, see Using parameterized queries.

    • Athena JDBC SAML federation is now functional for the China Regions.

    • Additional minor improvements.

For more information, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver.

March 30, 2022

Published on 2022-03-30

Athena announces the following fixes and improvements.

  • Cross-region querying – You can now use Athena to query data located in an Amazon S3 bucket across AWS Regions including Asia Pacific (Hong Kong), Middle East (Bahrain), Africa (Cape Town), and Europe (Milan).

March 18, 2022

Published on 2022-03-18

Athena announces the following fixes and improvements.

  • Dynamic filteringDynamic filtering has been improved for integer columns by efficiently applying the filter to each record of a corresponding table.

  • Iceberg – Fixed an issue that caused failures when writing Iceberg Parquet files larger than 2GB.

  • Uncompressed outputCREATE TABLE statements now support writing uncompressed files. To write uncompressed files, use the following syntax:

    • CREATE TABLE (text file or JSON) – In TBLPROPERTIES, specify write.compression = NONE.

    • CREATE TABLE (Parquet) – In TBLPROPERTIES, specify parquet.compression = UNCOMPRESSED.

    • CREATE TABLE (ORC) – In TBLPROPERTIES, specify orc.compress = NONE.

  • Compression – Fixed an issue with inserts for text file tables that created files compressed in one format but used another compression format file extension when non-default compression methods were used.

  • Avro – Fixed issues that occurred when reading decimals of the fixed type from Avro files.

March 2, 2022

Published on 2022-03-02

Athena announces the following features and improvements.

February 23, 2022

Published on 2022-02-23

Athena announces the following fixes and performance improvements.

  • Memory handling improvements to enhance performance and reduce memory errors.

  • Athena now reads ORC timestamp columns with time zone information stored in stripe footers and writes ORC files with time zone (UTC) in footers. This only impacts the behavior of ORC timestamp reads if the ORC file to be read was created in a non-UTC time zone environment.

  • Fixed incorrect symlink table size estimates that resulted in suboptimal query plans.

  • Lateral exploded views can now be queried in the Athena console from Hive metastore data sources.

  • Improved Amazon S3 read error messages to include more detailed Amazon S3 error code information.

  • Fixed an issue that caused output files in ORC format to become incompatible with Apache Hive 3.1.

  • Fixed an issue that caused table names with quotes to fail in certain DML and DDL queries.

February 15, 2022

Published on 2022-02-15

Amazon Athena has increased the active DML query quota in all AWS Regions. Active queries include both running and queued queries. With this change, you can now have more DML queries in an active state than before.

For information about Athena service quotas, see Service Quotas. For the query quotas in the Region where you use Athena, see Amazon Athena endpoints and quotas in the AWS General Reference.

To monitor your quota usage, you can use CloudWatch usage metrics. Athena publishes the ActiveQueryCount metric in the AWS/Usage namespace. For more information, see Monitoring Athena usage metrics.

After reviewing your usage, you can use the Service Quotas console to request a quota increase. If you previously requested a quota increase for your account, your requested quota still applies if it exceeds the new default active DML query quota. Otherwise, all accounts use the new default.

February 14, 2022

Published on 2022-02-14

This release adds the ErrorType subfield to the AthenaError response object in the Athena GetQueryExecution API action.

While the existing ErrorCategory field indicates the general source of a failed query (system, user, or other), the new ErrorType field provides more granular information about the error that occurred. Combine the information from both fields to gain insight into the causes of query failure.

For more information, see Athena error catalog.

February 9, 2022

Published on 2022-02-09

The old Athena console is no longer available. Athena's new console supports all of the features of the earlier console, but with an easier to use, modern interface and includes new features that improve the experience of developing queries, analyzing data, and managing your usage. To use the new Athena console, visit https://console.aws.amazon.com/athena/.

February 8, 2022

Published on 2022-02-08

Expected bucket owner – As an added security measure, you can now optionally specify the AWS account ID that you expect to be the owner of your query results output location bucket in Athena. If the account ID of the query results bucket owner does not match the account ID that you specify, attempts to output to the bucket will fail with an Amazon S3 permissions error. You can make this setting at the client or workgroup level.

For more information, see Specifying a query result location.

January 28, 2022

Published on 2022-01-28

Athena announces the following engine feature enhancements.

  • Apache Hudi – Snapshot queries on Hudi Merge on Read (MoR) tables can now read timestamp columns that have the INT64 data type.

  • UNION queries – Performance improvement and data scan reduction for certain UNION queries that scan the same table multiple times.

  • Disjunct queries – Performance improvement for queries that have only disjunct values for each partition column on the filter.

  • Partition projection enhancements

    • Multiple disjunct values are now allowed on the filter condition for columns of the injected type. For more information, see Injected type.

    • Performance improvement for columns of string-based types like CHAR or VARCHAR that have only disjunct values on the filter.

January 13, 2022

Published on 2022-01-13

Released the JDBC 2.0.27 and ODBC 1.1.15 drivers for Athena.

The JDBC 2.0.27 driver includes the following changes:

  • The driver has been updated to retrieve external catalogs.

  • The extended driver version number is now included in the user-agent string as part of the Athena API call.

The ODBC 1.1.15 driver includes the following changes:

  • Corrects an issue with second calls to SQLParamData().

For more information about these changes, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver and Connecting to Amazon Athena with ODBC.

Athena release notes for 2021

November 30, 2021

Published on 2021-11-30

Amazon Athena users can now use AWS Lake Formation to configure fine-grained access permissions and read from ACID-compliant tables. Amazon Athena makes it simple to analyze data in Amazon S3 based data lakes to help ensure that users only have access to data to which they're authorized. The ACID features help ensure that their queries are reliable in the face of complex changes to the underlying data.

Use Lake Formation data filtering to secure the tables in your Amazon S3 data lake by granting permissions at the column, row, and cell levels. These permissions are enforced when Athena users query your data. This fine level of control means that you can grant users access to sensitive information without using course-grained masking that would otherwise impede their analyses. Furthermore, with Lake Formation governed tables, Athena users can query data while multiple users simultaneously add and delete the table's Amazon S3 data objects.

For more information, see Using Athena ACID transactions and Using governed tables.

November 26, 2021

Published on 2021-11-26

Athena announces the public preview of Athena ACID transactions, which add write, delete, update, and time travel operations to Athena's SQL data manipulation language (DML). Athena ACID transactions enable multiple concurrent users to make reliable, row-level modifications to Amazon S3 data. Built on the Apache Iceberg table format, Athena ACID transactions are compatible with other services and engines such as Amazon EMR and Apache Spark that also support the Iceberg table formats.

Athena ACID transactions and familiar SQL syntax simplify updates to your business and regulatory data. For example, to respond to a data erasure request, you can perform a SQL DELETE operation. To make manual record corrections, you can use a single UPDATE statement. To recover data that was recently deleted, you can issue time travel queries using a SELECT statement. Athena transactions are available through Athena's console, API operations, and ODBC and JDBC drivers.

For more information, see Using Athena ACID transactions.

November 24, 2021

Published on 2021-11-24

Athena announces support for reading and writing ZStandard compressed ORC, Parquet, and textfile data. Athena uses ZStandard compression level 3 when writing ZStandard compressed data.

For information about data compression in Athena, see Athena compression support.

November 22, 2021

Published on 2021-11-22

You can now manage AWS Step Functions workflows from the Amazon Athena console, making it easier to build scalable data processing pipelines, execute queries based on custom business logic, automate administrative and alerting tasks, and more.

Step Functions is now integrated with Athena's upgraded console, and you can use it to view an interactive workflow diagram of your state machines that invoke Athena. To get started, select Workflows from the left navigation panel. If you have existing state machines with Athena queries, select a state machine to view an interactive diagram of the workflow. If you are new to Step Functions, you can get started by launching a sample project from the Athena console and customizing it to suit your use cases.

For more information, see Build and orchestrate ETL pipelines using Amazon Athena and AWS Step Functions, or consult the Step Functions documentation.

November 18, 2021

Published on 2021-11-18

Athena announces new features and improvements.

  • Support for spill-to-disk for aggregation queries that contain DISTINCT, ORDER BY, or both, as in the following example:

    SELECT array_agg(orderstatus ORDER BY orderstatus) FROM orders GROUP BY orderpriority, custkey
  • Addressed memory handling issues for queries that use DISTINCT. To avoid error messages like Query exhausted resources at this scale factor when you use DISTINCT queries, choose columns that have a low cardinality for DISTINCT, or reduce the data size of the query.

  • In SELECT COUNT(*) queries that do not specify a specific column, improved performance and memory usage by keeping only the count without row buffering.

  • Introduced the following string functions.

    • translate(source, from, to) – Returns the source string with the characters found in the from string replaced by the corresponding characters in the to string. If the from string contains duplicates, only the first is used. If the source character does not exist in the from string, the source character is copied without translation. If the index of the matching character in the from string is greater than the length of the to string, the character is omitted from the resulting string.

    • concat_ws(string0, array(varchar)) – Returns the concatenation of elements in the array using string0 as a separator. If string0 is null, then the return value is null. Any null values in the array are skipped.

  • Fixed a bug in which queries failed when trying to access a missing subfield in a struct. Queries now return a null for the missing subfield.

  • Fixed an issue with inconsistent hashing for the decimal data type.

  • Fixed an issue that caused exhausted resources when there were too many columns in a partition.

November 17, 2021

Published on 2021-11-17

Amazon Athena now supports partition indexing to accelerate queries on partitioned tables in the AWS Glue Data Catalog.

When querying partitioned tables, Athena retrieves and filters the available table partitions to the subset relevant to your query. As new data and partitions are added, more time is required to process the partitions and query runtime can increase. To optimize partition processing and improve query performance on highly partitioned tables, Athena now supports AWS Glue partition indexes.

For more information, see AWS Glue partition indexing and filtering.

November 16, 2021

Published on 2021-11-16

The new and improved Amazon Athena console is now generally available in the AWS commercial and GovCloud regions where Athena is available. Athena's new console supports all of the features of the earlier console, but with an easier to use, modern interface and includes new features that improve the experience of developing queries, analyzing data, and managing your usage. You can now:

  • Rearrange, navigate to, or close multiple query tabs from a redesigned query tab bar.

  • Read and edit queries more easily with improved SQL and text formatting.

  • Copy query results to your clipboard in addition to downloading the full result set.

  • Sort your query history, saved queries, and workgroups, and choose which columns to show or hide.

  • Use a simplified interface to configure data sources and workgroups in fewer clicks.

  • Set preferences for displaying query results, query history, line wrapping, and more.

  • Increase your productivity with new and improved keyboard shortcuts and embedded product documentation.

With today's announcement, the redesigned console is now the default. To tell us about your experience, choose Feedback in the bottom-left corner of the console.

If desired, you may use the earlier console by logging into your AWS account, choosing Amazon Athena, and deselecting New Athena experience from the navigation panel on the left.

November 12, 2021

Published on 2021-11-12

You can now use Amazon Athena to run federated queries on data sources located in an AWS account other than your own. Until today, querying this data required the data source and its connector to use the same AWS account as the user that queried the data.

As a data administrator, you can enable cross-account federated queries by sharing your data connector with a data analyst's account. As a data analyst, you can add a data connector that a data administrator has shared with you to your account. Configuration changes to the connector in the originating account apply automatically to the shared connector.

For information about enabling cross-account federated queries, see Enabling cross-account federated queries. To learn about querying federated sources, see Using Amazon Athena Federated Query and Writing federated queries.

November 2, 2021

Published on 2021-11-02

You can now use the EXPLAIN ANALYZE statement in Athena to view the distributed execution plan and cost of each operation for your SQL queries.

For more information, see Using EXPLAIN and EXPLAIN ANALYZE in Athena.

October 29, 2021

Published on 2021-10-29

Athena releases JDBC 2.0.25 and ODBC 1.1.13 drivers and announces features and improvements.

JDBC and ODBC Drivers

Released JDBC 2.0.25 and ODBC 1.1.13 drivers for Athena. Both drivers offer support for browser SAML multi-factor authentication, which can be configured to work with any SAML 2.0 provider.

The JDBC 2.0.25 driver includes the following changes:

  • Support for browser SAML authentication. The driver includes a browser SAML plugin which can be configured to work with any SAML 2.0 provider.

  • Support for AWS Glue API calls. You can use the GlueEndpointOverride parameter to override the AWS Glue endpoint.

  • Changed the com.simba.athena.amazonaws class path to com.amazonaws.

The ODBC 1.1.13 driver includes the following changes:

  • Support for browser SAML authentication. The driver includes a browser SAML plugin which can be configured to work with any SAML 2.0 provider. For an example of how to use the browser SAML plugin with the ODBC driver, see Configuring single sign-on using ODBC, SAML 2.0, and the Okta Identity Provider.

  • You can now configure the role session duration when you use ADFS, Azure AD, or Browser Azure AD for authentication.

For more information about these and other changes, and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver and Connecting to Amazon Athena with ODBC.

Features and Improvements

Athena announces the following features and improvements.

  • A new optimization rule has been introduced to avoid duplicate table scans in certain cases.

October 4, 2021

Published on 2021-10-04

Athena announces the following features and improvements.

  • SQL OFFSET – The SQL OFFSET clause is now supported in SELECT statements. For more information, see SELECT.

  • CloudWatch usage metrics – Athena now publishes the ActiveQueryCount metric in the AWS/Usage namespace. For more information, see Monitoring Athena usage metrics.

  • Query planning – Fixed a bug that could in rare cases cause query planning timeouts.

September 16, 2021

Published on 2021-09-16

Athena announces the following new features and improvements.

Features

  • The Apache Hudi Metadata Listing Feature is now available for Hudi tables, reducing Amazon S3 overhead and query times for partitioned table queries. For information about using Apache Hudi in Athena, see Using Athena to query Apache Hudi datasets.

  • Added support for specifying textfile and JSON compression in CTAS using the write_compression table property. You can also specify the write_compression property in CTAS for the Parquet and ORC formats. For more information, see CTAS table properties.

  • The BZIP2 compression format is now supported for writing textfile and JSON files. For more information about the compression formats in Athena, see Athena compression support.

Improvements

  • Fixed a bug in which identity information failed to be sent to the UDF Lambda function.

  • Fixed a predicate pushdown issue with disjunct filter conditions.

  • Fixed a hashing issue for decimal types.

  • Fixed an unnecessary statistics collection issue.

  • Removed an inconsistent error message.

  • Improved broadcast join performance by applying dynamic partition pruning in the worker node.

  • For federated queries:

    • Altered configuration to reduce the occurrence of CONSTRAINT_VIOLATION errors in federated queries.

September 15, 2021

Published on 2021-09-15

You can now use a redesigned Amazon Athena console (Preview). A new Athena JDBC driver has been released.

Athena Console Preview

You can now use a redesigned Amazon Athena console (Preview) from any AWS Region where Athena is available. The new console supports all of the features of the existing console, but from an easier to use, modern interface.

To switch to the new console, log into your AWS account and choose Amazon Athena. From the AWS console navigation bar, choose Switch to the new console. To return to the default console, deselect New Athena experience from the navigation panel on the left.

Get started with the new console today. Choose Feedback in the bottom-left corner to tell us about your experience.

Athena JDBC Driver 2.0.24

Athena announces availability of JDBC driver version 2.0.24 for Athena. This release updates proxy support for all credentials providers. The driver now supports proxy authentication for all hosts that are not supported by the NonProxyHosts connection property.

As a convenience, this release includes downloads of the JDBC driver both with and without the AWS SDK. This JDBC driver version allows you to have both the AWS-SDK and the Athena JDBC driver embedded in project.

For more information and to download the new driver, release notes, and documentation, see Using Athena with the JDBC driver.

August 31, 2021

Published on 2021-08-31

Athena announces the following feature enhancements and bug fixes.

  • Athena federation enhancements – Athena has added support to map types and better support for complex types as part of the Athena Query Federation SDK. This version also includes some memory enhancements and performance optimizations.

  • New error categories – Introduced the USER and SYSTEM error categories in error messages. These categories help you distinguish between errors that you can fix yourself (USER) and errors that can require assistance from Athena support (SYSTEM).

  • Federated query error messaging – Updated USER_ERROR categorizations for federated query related errors.

  • JOIN – Fixed spill-to-disk related bugs and memory issues to enhance performance and reduce memory errors in JOIN operations.

August 12, 2021

Published on 2021-08-12

Released the ODBC 1.1.12 driver for Athena. This version corrects issues related to SQLPrepare(), SQLGetInfo(), and EndpointOverride.

To download the new driver, release notes, and documentation, see Connecting to Amazon Athena with ODBC.

August 6, 2021

Published on 2021-08-06

Amazon Athena announces availability of Athena and its features in the Asia Pacific (Osaka) Region.

This release expands Athena's availability in Asia Pacific to include Asia Pacific (Hong Kong), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo). For a complete list of AWS services available in these and other Regions, refer to the AWS Regional Services List.

August 5, 2021

Published on 2021-08-05

You can use the UNLOAD statement to write the output of a SELECT query to the PARQUET, ORC, AVRO, and JSON formats.

For more information, see UNLOAD.

July 30, 2021

Published on 2021-07-30

Athena announces the following feature enhancements and bug fixes.

  • Dynamic filtering and partition pruning – Improvements increase performance and reduce the amount of data scanned in certain queries, as in the following example.

    This example assumes that Table_B is an unpartitioned table that has file sizes that add up to less than 20Mb. For queries like this, less data is read from Table_A and the query completes more quickly.

    SELECT * FROM Table_A JOIN Table_B ON Table_A.date = Table_B.date WHERE Table_B.column_A = "value"
  • ORDER BY with LIMIT, DISTINCT with LIMIT – Performance improvements to queries that use ORDER BY or DISTINCT followed by a LIMIT clause.

  • S3 Glacier Deep Archive files – When Athena queries a table that contains a mix of S3 Glacier Deep Archive files and non-S3 Glacier files, Athena now skips the S3 Glacier Deep Archive files for you. Previously, you were required to manually move these files from the query location or the query would fail. If you want to use Athena to query objects in S3 Glacier Deep Archive storage, you must restore them. For more information, see Restoring an archived object in the Amazon S3 User Guide.

  • Fixed a bug in which empty files created by the CTAS bucketed_by table property were not encrypted correctly.

July 21, 2021

Published on 2021-07-21

With the July 2021 release of Microsoft Power BI Desktop, you can create reports and dashboards using a native data source connector for Amazon Athena. The connector for Amazon Athena is available as a standard connector in Power BI, supports DirectQuery, and enables analysis on large datasets and content refresh through Power BI Gateway.

Because the connector uses your existing ODBC data source name (DSN) to connect to and run queries on Athena, it requires the Athena ODBC driver. To download the latest ODBC driver, see Connecting to Amazon Athena with ODBC.

For more information, see Using the Amazon Athena Power BI connector.

July 16, 2021

Published on 2021-07-16

Amazon Athena has updated its integration with Apache Hudi. Hudi is an open-source data management framework used to simplify incremental data processing in Amazon S3 data lakes. The updated integration enables you to use Athena to query Hudi 0.8.0 tables managed through Amazon EMR, Apache Spark, Apache Hive or other compatible services. In addition, Athena now supports two additional features: snapshot queries on Merge-on-Read (MoR) tables and read support on bootstrapped tables.

Apache Hudi provides record-level data processing that can help you simplify development of Change Data Capture (CDC) pipelines, comply with GDPR-driven updates and deletes, and better manage streaming data from sensors or devices that require data insertion and event updates. The 0.8.0 release makes it easier to migrate large Parquet tables to Hudi without copying data so you can query and analyze them through Athena. You can use Athena's new support for snapshot queries to have near real-time views of your streaming table updates.

To learn more about using Hudi with Athena, see Using Athena to query Apache Hudi datasets.

July 8, 2021

Published on 2021-07-08

Released the ODBC 1.1.11 driver for Athena. The ODBC driver can now authenticate the connection using a JSON Web Token (JWT). On Linux, the default value for the Workgroup property has been set to Primary.

For more information and to download the new driver, release notes, and documentation, see Connecting to Amazon Athena with ODBC.

July 1, 2021

Published on 2021-07-01

On July 1, 2021, special handling of preview workgroups ended. While AmazonAthenaPreviewFunctionality workgroups retain their name, they no longer have special status. You can continue to use AmazonAthenaPreviewFunctionality workgroups to view, modify, organize, and run queries. However, queries that use features that were formerly in preview are now subject to standard Athena billing terms and conditions. For billing information, see Amazon Athena pricing.

June 23, 2021

Published on 2021-06-23

Released JDBC 2.0.23 and ODBC 1.1.10 drivers for Athena. Both drivers offer improved read performance and support EXPLAIN statements and parameterized queries.

EXPLAIN statements show the logical or distributed execution plan of a SQL query. Parameterized queries enable the same query to be used multiple times with different values supplied at run time.

The JDBC release also adds support for Active Directory Federation Services 2019 and a custom endpoint override option for AWS STS. The ODBC release fixes an issue with IAM profile credentials.

For more information and to download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver and Connecting to Amazon Athena with ODBC.

May 12, 2021

Published on 2021-05-12

You can now use Amazon Athena to register an AWS Glue catalog from an account other than your own. After you configure the required IAM permissions for AWS Glue, you can use Athena to run cross-account queries.

For more information, see Registering an AWS Glue Data Catalog from another account and Cross-account access to AWS Glue data catalogs.

May 10, 2021

Published on 2021-05-10

Released ODBC driver version 1.1.9.1001 for Athena. This version fixes an issue with the BrowserAzureAD authentication type when using Azure Active Directory (AD).

To download the new drivers, release notes, and documentation, see Connecting to Amazon Athena with ODBC.

May 5, 2021

Published on 2021-05-05

You can now use the Amazon Athena Vertica connector in federated queries to query Vertica data sources from Athena. For example, you can run analytical queries over a data warehouse on Vertica and a data lake in Amazon S3.

To deploy the Athena Vertica connector, visit the AthenaVerticaConnector page in the AWS Serverless Application Repository.

The Amazon Athena Vertica connector exposes several configuration options through Lambda environment variables. For information about configuration options, parameters, connection strings, deployment, and limitations, see Amazon Athena Vertica connector.

For in-depth information about using the Vertica connector, see Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK in the AWS Big Data Blog.

April 30, 2021

Published on 2021-04-30

Released drivers JDBC 2.0.21 and ODBC 1.1.9 for Athena. Both releases support SAML authentication with Azure Active Directory (AD) and SAML authentication with PingFederate. The JDBC release also supports parameterized queries. For information about parameterized queries in Athena, see Using parameterized queries.

To download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver and Connecting to Amazon Athena with ODBC.

April 29, 2021

Published on 2021-04-29

Amazon Athena announces availability of Athena engine version 2 in the China (Beijing) and China (Ningxia) Regions.

For information about Athena engine version 2, see Athena engine version 2.

April 26, 2021

Published on 2021-04-26

Window value functions in Athena engine version 2 now support IGNORE NULLS and RESPECT NULLS.

For more information, see Value Functions in the Presto documentation.

April 21, 2021

Published on 2021-04-21

Amazon Athena announces availability of Athena engine version 2 in the Europe (Milan) and Africa (Cape Town) Regions.

For information about Athena engine version 2, see Athena engine version 2.

April 5, 2021

Published on 2021-04-05

EXPLAIN Statement

You can now use the EXPLAIN statement in Athena to view the execution plan for your SQL queries.

For more information, see Using EXPLAIN and EXPLAIN ANALYZE in Athena and Understanding Athena EXPLAIN statement results.

SageMaker Machine Learning Models in SQL Queries

Machine learning model inference with Amazon SageMaker is now generally available for Amazon Athena. Use machine learning models in SQL queries to simplify complex tasks such as anomaly detection, customer cohort analysis, and time-series predictions by invoking a function in a SQL query.

For more information, see Using Machine Learning (ML) with Amazon Athena.

User Defined Functions (UDF)

User defined functions (UDFs) are now generally available for Athena. Use UDFs to leverage custom functions that process records or groups of records in a single SQL query.

For more information, see Querying with user defined functions.

March 30, 2021

Published on 2021-03-30

Amazon Athena announces availability of Athena engine version 2 in the Asia Pacific (Hong Kong) and Middle East (Bahrain) Regions.

For information about Athena engine version 2, see Athena engine version 2.

March 25, 2021

Published on 2021-03-25

Amazon Athena announces availability of Athena engine version 2 in the Europe (Stockholm) Region.

For information about Athena engine version 2, see Athena engine version 2.

March 5, 2021

Published on 2021-03-05

Amazon Athena announces availability of Athena engine version 2 in the Canada (Central), Europe (Frankfurt), and South America (São Paulo) Regions.

For information about Athena engine version 2, see Athena engine version 2.

February 25, 2021

Published on 2021-02-25

Amazon Athena announces general availability of Athena engine version 2 in the Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (London), and Europe (Paris) Regions.

For information about Athena engine version 2, see Athena engine version 2.

Athena release notes for 2020

December 16, 2020

Published on 2020-12-16

Amazon Athena announces availability of Athena engine version 2, Athena Federated Query, and AWS PrivateLink in additional Regions.

Athena engine version 2 and Athena Federated Query

Amazon Athena announces general availability of Athena engine version 2 and Athena Federated Query in the Asia Pacific (Mumbai), Asia Pacific (Tokyo), Europe (Ireland), and US West (N. California) Regions. Athena engine version 2 and federated queries are already available in the US East (N. Virginia), US East (Ohio), and US West (Oregon) Regions.

For more information, see Athena engine version 2 and Using Amazon Athena Federated Query.

AWS PrivateLink for Athena is now supported in the Europe (Stockholm) Region. For information about AWS PrivateLink for Athena, see Connect to Amazon Athena using an interface VPC endpoint.

November 24, 2020

Published on 2020-11-24

Released drivers JDBC 2.0.16 and ODBC 1.1.6 for Athena. These releases support, at the account level, Okta Verify multifactor authentication (MFA). You can also use Okta MFA to configure SMS authentication and Google Authenticator authentication as factors.

To download the new drivers, release notes, and documentation, see Using Athena with the JDBC driver and Connecting to Amazon Athena with ODBC.

November 11, 2020

Published on 2020-11-11

Amazon Athena announces general availability in the US East (N. Virginia), US East (Ohio), and US West (Oregon) Regions for Athena engine version 2 and federated queries.

Athena engine version 2

Amazon Athena announces general availability of a new query engine version, Athena engine version 2, in the US East (N. Virginia), US East (Ohio), and US West (Oregon) Regions.

Athena engine version 2 includes performance enhancements and new feature capabilities such as schema evolution support for Parquet format data, additional geospatial functions, support for reading nested schema to reduce cost, and performance enhancements in JOIN and AGGREGATE operations.

Federated SQL Queries

You can now use Athena's federated query in the US East (N. Virginia), US East (Ohio), and US West (Oregon) Regions without using the AmazonAthenaPreviewFunctionality workgroup.

Use Federated SQL queries to run SQL queries across relational, non-relational, object, and custom data sources. With federated querying, you can submit a single SQL query that scans data from multiple sources running on premises or hosted in the cloud.

Running analytics on data spread across applications can be complex and time consuming for the following reasons:

  • Data required for analytics is often spread across relational, key-value, document, in-memory, search, graph, object, time-series and ledger data stores.

  • To analyze data across these sources, analysts build complex pipelines to extract, transform, and load into a data warehouse so that the data can be queried.

  • Accessing data from various sources requires learning new programming languages and data access constructs.

Federated SQL queries in Athena eliminate this complexity by allowing users to query the data in-place from wherever it resides. Analysts can use familiar SQL constructs to JOIN data across multiple data sources for quick analysis, and store results in Amazon S3 for subsequent use.

Data Source Connectors

To process federated queries, Athena uses Athena Data Source Connectors that run on AWS Lambda. The following open sourced, pre-built connectors were written and tested by Athena. Use them to run SQL queries in Athena on their corresponding data sources.

Custom Data Source Connectors

Using Athena Query Federation SDK, developers can build connectors to any data source to enable Athena to run SQL queries against that data source. Athena Query Federation Connector extends the benefits of federated querying beyond AWS provided connectors. Because connectors run on AWS Lambda, you do not have to manage infrastructure or plan for scaling to peak demands.

Next Steps

October 22, 2020

Published on 2020-10-22

You can now call Athena with AWS Step Functions. AWS Step Functions can control certain AWS services directly using the Amazon States Language. You can use Step Functions with Athena to start and stop query execution, get query results, run ad-hoc or scheduled data queries, and retrieve results from data lakes in Amazon S3.

For more information, see Call Athena with Step Functions in the AWS Step Functions Developer Guide.

July 29, 2020

Published on 2020-07-29

Released JDBC driver version 2.0.13. This release supports using multiple data catalogs registered with Athena, Okta service for authentication, and connections to VPC endpoints.

To download and use the new version of the driver, see Using Athena with the JDBC driver.

July 9, 2020

Published on 2020-07-09

Amazon Athena adds support for querying compacted Hudi datasets and adds the AWS CloudFormation AWS::Athena::DataCatalog resource for creating, updating, or deleting data catalogs that you register in Athena.

Querying Apache Hudi Datasets

Apache Hudi is an open-source data management framework that simplifies incremental data processing. Amazon Athena now supports querying the read-optimized view of an Apache Hudi dataset in your Amazon S3-based data lake.

For more information, see Using Athena to query Apache Hudi datasets.

AWS CloudFormation Data Catalog Resource

To use Amazon Athena's federated query feature to query any data source, you must first register your data catalog in Athena. You can now use the AWS CloudFormation AWS::Athena::DataCatalog resource to create, update, or delete data catalogs that you register in Athena.

For more information, see AWS::Athena::DataCatalog in the AWS CloudFormation User Guide.

June 1, 2020

Published on 2020-06-01

Using Apache Hive Metastore as a Metacatalog with Amazon Athena

You can now connect Athena to one or more Apache Hive metastores in addition to the AWS Glue Data Catalog with Athena.

To connect to a self-hosted Hive metastore, you need an Athena Hive metastore connector. Athena provides a reference implementation connector that you can use. The connector runs as an AWS Lambda function in your account.

For more information, see Using Athena Data Connector for External Hive Metastore.

May 21, 2020

Published on 2020-05-21

Amazon Athena adds support for partition projection. Use partition projection to speed up query processing of highly partitioned tables and automate partition management. For more information, see Partition projection with Amazon Athena.

April 1, 2020

Published on 2020-04-01

In addition to the US East (N. Virginia) Region, the Amazon Athena federated query, user defined functions (UDFs), machine learning inference, and external Hive metastore features are now available in preview in the Asia Pacific (Mumbai), Europe (Ireland), and US West (Oregon) Regions.

March 11, 2020

Published on 2020-03-11

Amazon Athena now publishes Amazon CloudWatch Events for query state transitions. When a query transitions between states -- for example, from Running to a terminal state such as Succeeded or Cancelled -- Athena publishes a query state change event to CloudWatch Events. The event contains information about the query state transition. For more information, see Monitoring Athena queries with CloudWatch events.

March 6, 2020

Published on 2020-03-06

You can now create and update Amazon Athena workgroups by using the AWS CloudFormation AWS::Athena::WorkGroup resource. For more information, see AWS::Athena::WorkGroup in the AWS CloudFormation User Guide.

Athena release notes for 2019

November 26, 2019

Published on 2019-12-17

Amazon Athena adds support for running SQL queries across relational, non-relational, object, and custom data sources, invoking machine learning models in SQL queries, User Defined Functions (UDFs) (Preview), using Apache Hive Metastore as a metadata catalog with Amazon Athena (Preview), and four additional query-related metrics.

Federated SQL Queries

Use Federated SQL queries to run SQL queries across relational, non-relational, object, and custom data sources.

You can now use Athena's federated query to scan data stored in relational, non-relational, object, and custom data sources. With federated querying, you can submit a single SQL query that scans data from multiple sources running on premises or hosted in the cloud.

Running analytics on data spread across applications can be complex and time consuming for the following reasons:

  • Data required for analytics is often spread across relational, key-value, document, in-memory, search, graph, object, time-series and ledger data stores.

  • To analyze data across these sources, analysts build complex pipelines to extract, transform, and load into a data warehouse so that the data can be queried.

  • Accessing data from various sources requires learning new programming languages and data access constructs.

Federated SQL queries in Athena eliminate this complexity by allowing users to query the data in-place from wherever it resides. Analysts can use familiar SQL constructs to JOIN data across multiple data sources for quick analysis, and store results in Amazon S3 for subsequent use.

Data Source Connectors

Athena processes federated queries using Athena Data Source Connectors that run on AWS Lambda. Use these open sourced data source connectors to run federated SQL queries in Athena across Amazon DynamoDB, Apache HBase, Amazon Document DB, Amazon CloudWatch, Amazon CloudWatch Metrics, and JDBC-compliant relational databases such MySQL, and PostgreSQL under the Apache 2.0 license.

Custom Data Source Connectors

Using Athena Query Federation SDK, developers can build connectors to any data source to enable Athena to run SQL queries against that data source. Athena Query Federation Connector extends the benefits of federated querying beyond AWS provided connectors. Because connectors run on AWS Lambda, you do not have to manage infrastructure or plan for scaling to peak demands.

Preview Availability

Athena federated query is available in preview in the US East (N. Virginia) Region.

Next Steps

Invoking Machine Learning Models in SQL Queries

You can now invoke machine learning models for inference directly from your Athena queries. The ability to use machine learning models in SQL queries makes complex tasks such anomaly detection, customer cohort analysis, and sales predictions as simple as invoking a function in a SQL query.

ML Models

You can use more than a dozen built-in machine learning algorithms provided by Amazon SageMaker, train your own models, or find and subscribe to model packages from AWS Marketplace and deploy on Amazon SageMaker Hosting Services. There is no additional setup required. You can invoke these ML models in your SQL queries from the Athena console, Athena APIs, and through Athena's preview JDBC driver.

Preview Availability

Athena's ML functionality is available today in preview in the US East (N. Virginia) Region.

Next Steps

User Defined Functions (UDFs) (Preview)

You can now write custom scalar functions and invoke them in your Athena queries. You can write your UDFs in Java using the Athena Query Federation SDK. When a UDF is used in a SQL query submitted to Athena, it is invoked and run on AWS Lambda. UDFs can be used in both SELECT and FILTER clauses of a SQL query. You can invoke multiple UDFs in the same query.

Preview Availability

Athena UDF functionality is available in Preview mode in the US East (N. Virginia) Region.

Next Steps

Using Apache Hive Metastore as a Metacatalog with Amazon Athena (Preview)

You can now connect Athena to one or more Apache Hive Metastores in addition to the AWS Glue Data Catalog with Athena.

Metastore Connector

To connect to a self-hosted Hive Metastore, you need an Athena Hive Metastore connector. Athena provides a reference implementation connector that you can use. The connector runs as an AWS Lambda function in your account. For more information, see Using Athena Data Connector for External Hive Metastore (Preview).

Preview Availability

The Hive Metastore feature is available in Preview mode in the US East (N. Virginia) Region.

Next Steps

New Query-Related Metrics

Athena now publishes additional query metrics that can help you understand Amazon Athena performance. Athena publishes query-related metrics to Amazon CloudWatch. In this release, Athena publishes the following additional query metrics:

  • Query Planning Time – The time taken to plan the query. This includes the time spent retrieving table partitions from the data source.

  • Query Queuing Time – The time that the query was in a queue waiting for resources.

  • Service Processing Time – The time taken to write results after the query engine finishes processing.

  • Total Execution Time – The time Athena took to run the query.

To consume these new query metrics, you can create custom dashboards, set alarms and triggers on metrics in CloudWatch, or use pre-populated dashboards directly from the Athena console.

Next Steps

For more information, see Monitoring Athena Queries with CloudWatch Metrics.

November 12, 2019

Published on 2019-12-17

Amazon Athena is now available in the Middle East (Bahrain) Region.

November 8, 2019

Published on 2019-12-17

Amazon Athena is now available in the US West (N. California) Region and the Europe (Paris) Region.

October 8, 2019

Published on 2019-12-17

Amazon Athena now allows you to connect directly to Athena through an interface VPC endpoint in your Virtual Private Cloud (VPC). Using this feature, you can submit your queries to Athena securely without requiring an Internet Gateway in your VPC.

To create an interface VPC endpoint to connect to Athena, you can use the AWS Management Console or AWS Command Line Interface (AWS CLI). For information about creating an interface endpoint, see Creating an Interface Endpoint.

When you use an interface VPC endpoint, communication between your VPC and Athena APIs is secure and stays within the AWS network. There are no additional Athena costs to use this feature. Interface VPC endpoint charges apply.

To learn more about this feature, see Connect to Amazon Athena Using an Interface VPC Endpoint.

September 19, 2019

Published on 2019-12-17

Amazon Athena adds support for inserting new data to an existing table using the INSERT INTO statement. You can insert new rows into a destination table based on a SELECT query statement that runs on a source table, or based on a set of values that are provided as part of the query statement. Supported data formats include Avro, JSON, ORC, Parquet, and text files.

INSERT INTO statements can also help you simplify your ETL process. For example, you can use INSERT INTO in a single query to select data from a source table that is in JSON format and write to a destination table in Parquet format.

INSERT INTO statements are charged based on the number of bytes that are scanned in the SELECT phase, similar to how Athena charges for SELECT queries. For more information, see Amazon Athena pricing.

For more information about using INSERT INTO, including supported formats, SerDes and examples, see INSERT INTO in the Athena User Guide.

September 12, 2019

Published on 2019-12-17

Amazon Athena is now available in the Asia Pacific (Hong Kong) Region.

August 16, 2019

Published on 2019-12-17

Amazon Athena adds support for querying data in Amazon S3 Requester Pays buckets.

When an Amazon S3 bucket is configured as Requester Pays, the requester, not the bucket owner, pays for the Amazon S3 request and data transfer costs. In Athena, workgroup administrators can now configure workgroup settings to allow workgroup members to query S3 Requester Pays buckets.

For information about how to configure the Requester Pays setting for your workgroup, refer to Create a Workgroup in the Amazon Athena User Guide. For more information about Requester Pays buckets, see Requester Pays Buckets in the Amazon Simple Storage Service Developer Guide.

August 9, 2019

Published on 2019-12-17

Amazon Athena now supports enforcing AWS Lake Formation policies for fine-grained access control to new or existing databases, tables, and columns defined in the AWS Glue Data Catalog for data stored in Amazon S3.

You can use this feature in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). There are no additional charges to use this feature.

For more information about using this feature, see Using Athena to query data registered with AWS Lake Formation. For more information about AWS Lake Formation, see AWS Lake Formation.

June 26, 2019

Amazon Athena is now available in the Europe (Stockholm) Region. For a list of supported Regions, see AWS Regions and Endpoints.

May 24, 2019

Published on 2019-05-24

Amazon Athena is now available in the AWS GovCloud (US-East) and AWS GovCloud (US-West) Regions. For a list of supported Regions, see AWS Regions and Endpoints.

March 05, 2019

Published on 2019-03-05

Amazon Athena is now available in the Canada (Central) Region. For a list of supported Regions, see AWS Regions and Endpoints. Released the new version of the ODBC driver with support for Athena workgroups. For more information, see the ODBC Driver Release Notes.

To download the ODBC driver version 1.0.5 and its documentation, see Connecting to Amazon Athena with ODBC. For information about this version, see the ODBC Driver Release Notes.

To use workgroups with the ODBC driver, set the new connection property, Workgroup, in the connection string as shown in the following example:

Driver=Simba Athena ODBC Driver;AwsRegion=[Region];S3OutputLocation=[S3Path];AuthenticationType=IAM Credentials;UID=[YourAccessKey];PWD=[YourSecretKey];Workgroup=[WorkgroupName]

For more information, search for "workgroup" in the ODBC Driver Installation and Configuration Guide version 1.0.5. There are no changes to the ODBC driver connection string when you use tags on workgroups. To use tags, upgrade to the latest version of the ODBC driver, which is this current version.

This driver version lets you use Athena API workgroup actions to create and manage workgroups, and Athena API tag actions to add, list, or remove tags on workgroups. Before you begin, make sure that you have resource-level permissions in IAM for actions on workgroups and tags.

For more information, see:

If you use the JDBC driver or the AWS SDK, upgrade to the latest version of the driver and SDK, both of which already include support for workgroups and tags in Athena. For more information, see Using Athena with the JDBC driver.

February 22, 2019

Published on 2019-02-22

Added tag support for workgroups in Amazon Athena. A tag consists of a key and a value, both of which you define. When you tag a workgroup, you assign custom metadata to it. You can add tags to workgroups to help categorize them, using AWS tagging best practices. You can use tags to restrict access to workgroups, and to track costs. For example, create a workgroup for each cost center. Then, by adding tags to these workgroups, you can track your Athena spending for each cost center. For more information, see Using Tags for Billing in the AWS Billing and Cost Management User Guide.

You can work with tags by using the Athena console or the API operations. For more information, see Tagging Athena resources.

In the Athena console, you can add one or more tags to each of your workgroups, and search by tags. Workgroups are an IAM-controlled resource in Athena. In IAM, you can restrict who can add, remove, or list tags on workgroups that you create. You can also use the CreateWorkGroup API operation that has the optional tag parameter for adding one or more tags to the workgroup. To add, remove, or list tags, use TagResource, UntagResource, and ListTagsForResource. For more information, see Using tag operations.

To allow users to add tags when creating workgroups, ensure that you give each user IAM permissions to both the TagResource and CreateWorkGroup API actions. For more information and examples, see Tag-based IAM access control policies.

There are no changes to the JDBC driver when you use tags on workgroups. If you create new workgroups and use the JDBC driver or the AWS SDK, upgrade to the latest version of the driver and SDK. For information, see Using Athena with the JDBC driver.

February 18, 2019

Published on 2019-02-18

Added ability to control query costs by running queries in workgroups. For information, see Using workgroups to control query access and costs. Improved the JSON OpenX SerDe used in Athena, fixed an issue where Athena did not ignore objects transitioned to the GLACIER storage class, and added examples for querying Network Load Balancer logs.

Made the following changes:

  • Added support for workgroups. Use workgroups to separate users, teams, applications, or workloads, and to set limits on amount of data each query or the entire workgroup can process. Because workgroups act as IAM resources, you can use resource-level permissions to control access to a specific workgroup. You can also view query-related metrics in Amazon CloudWatch, control query costs by configuring limits on the amount of data scanned, create thresholds, and trigger actions, such as Amazon SNS alarms, when these thresholds are breached. For more information, see Using workgroups for running queries and Controlling costs and monitoring queries with CloudWatch metrics and events.

    Workgroups are an IAM resource. For a full list of workgroup-related actions, resources, and conditions in IAM, see Actions, Resources, and Condition Keys for Amazon Athena in the Service Authorization Reference. Before you create new workgroups, make sure that you use workgroup IAM policies, and the AWS managed policy: AmazonAthenaFullAccess.

    You can start using workgroups in the console, with the workgroup API operations, or with the JDBC driver. For a high-level procedure, see Setting up workgroups. To download the JDBC driver with workgroup support, see Using Athena with the JDBC driver.

    If you use workgroups with the JDBC driver, you must set the workgroup name in the connection string using the Workgroup configuration parameter as in the following example:

    jdbc:awsathena://AwsRegion=<AWSREGION>;UID=<ACCESSKEY>; PWD=<SECRETKEY>;S3OutputLocation=s3://<athena-output>-<AWSREGION>/; Workgroup=<WORKGROUPNAME>;

    There are no changes in the way you run SQL statements or make JDBC API calls to the driver. The driver passes the workgroup name to Athena.

    For information about differences introduced with workgroups, see Athena workgroup APIs and Troubleshooting workgroups.

  • Improved the JSON OpenX SerDe used in Athena. The improvements include, but are not limited to, the following:

    • Support for the ConvertDotsInJsonKeysToUnderscores property. When set to TRUE, it allows the SerDe to replace the dots in key names with underscores. For example, if the JSON dataset contains a key with the name "a.b", you can use this property to define the column name to be "a_b" in Athena. The default is FALSE. By default, Athena does not allow dots in column names.

    • Support for the case.insensitive property. By default, Athena requires that all keys in your JSON dataset use lowercase. Using WITH SERDE PROPERTIES ("case.insensitive"= FALSE;) allows you to use case-sensitive key names in your data. The default is TRUE. When set to TRUE, the SerDe converts all uppercase columns to lowercase.

    For more information, see OpenX JSON SerDe.

  • Fixed an issue where Athena returned "access denied" error messages, when it processed Amazon S3 objects that were archived to Glacier by Amazon S3 lifecycle policies. As a result of fixing this issue, Athena ignores objects transitioned to the GLACIER storage class. Athena does not support querying data from the GLACIER storage class.

    For more information, see Requirements for tables in Athena and data in Amazon S3 and Transitioning to the GLACIER Storage Class (Object Archival) in the Amazon Simple Storage Service User Guide.

  • Added examples for querying Network Load Balancer access logs that receive information about the Transport Layer Security (TLS) requests. For more information, see Querying Network Load Balancer logs.

Athena release notes for 2018

November 20, 2018

Published on 2018-11-20

Released the new versions of the JDBC and ODBC driver with support for federated access to Athena API with the AD FS and SAML 2.0 (Security Assertion Markup Language 2.0). For details, see the JDBC Driver Release Notes and ODBC Driver Release Notes.

With this release, federated access to Athena is supported for the Active Directory Federation Service (AD FS 3.0). Access is established through the versions of JDBC or ODBC drivers that support SAML 2.0. For information about configuring federated access to the Athena API, see Enabling federated access to the Athena API.

To download the JDBC driver version 2.0.6 and its documentation, see Using Athena with the JDBC driver. For information about this version, see JDBC Driver Release Notes.

To download the ODBC driver version 1.0.4 and its documentation, see Connecting to Amazon Athena with ODBC. For information about this version, ODBC Driver Release Notes.

For more information about SAML 2.0 support in AWS, see About SAML 2.0 Federation in the IAM User Guide.

October 15, 2018

Published on 2018-10-15

If you have upgraded to the AWS Glue Data Catalog, there are two new features that provide support for:

  • Encryption of the Data Catalog metadata. If you choose to encrypt metadata in the Data Catalog, you must add specific policies to Athena. For more information, see Access to Encrypted Metadata in the AWS Glue Data Catalog.

  • Fine-grained permissions to access resources in the AWS Glue Data Catalog. You can now define identity-based (IAM) policies that restrict or allow access to specific databases and tables from the Data Catalog used in Athena. For more information, see Fine-grained access to databases and tables in the AWS Glue Data Catalog.

    Note

    Data resides in the Amazon S3 buckets, and access to it is governed by the Access to Amazon S3. To access data in databases and tables, continue to use access control policies to Amazon S3 buckets that store the data.

October 10, 2018

Published on 2018-10-10

Athena supports CREATE TABLE AS SELECT, which creates a table from the result of a SELECT query statement. For details, see Creating a Table from Query Results (CTAS).

Before you create CTAS queries, it is important to learn about their behavior in the Athena documentation. It contains information about the location for saving query results in Amazon S3, the list of supported formats for storing CTAS query results, the number of partitions you can create, and supported compression formats. For more information, see Considerations and limitations for CTAS queries.

Use CTAS queries to:

September 6, 2018

Published on 2018-09-06

Released the new version of the ODBC driver (version 1.0.3). The new version of the ODBC driver streams results by default, instead of paging through them, allowing business intelligence tools to retrieve large data sets faster. This version also includes improvements, bug fixes, and an updated documentation for "Using SSL with a Proxy Server". For details, see the Release Notes for the driver.

For downloading the ODBC driver version 1.0.3 and its documentation, see Connecting to Amazon Athena with ODBC.

The streaming results feature is available with this new version of the ODBC driver. It is also available with the JDBC driver. For information about streaming results, see the ODBC Driver Installation and Configuration Guide, and search for UseResultsetStreaming.

The ODBC driver version 1.0.3 is a drop-in replacement for the previous version of the driver. We recommend that you migrate to the current driver.

Important

To use the ODBC driver version 1.0.3, follow these requirements:

  • Keep the port 444 open to outbound traffic.

  • Add the athena:GetQueryResultsStream policy action to the list of policies for Athena. This policy action is not exposed directly with the API and is only used with the ODBC and JDBC drivers, as part of streaming results support. For an example policy, see AWS managed policy: AWSQuicksightAthenaAccess.

August 23, 2018

Published on 2018-08-23

Added support for these DDL-related features and fixed several bugs, as follows:

  • Added support for BINARY and DATE data types for data in Parquet, and for DATE and TIMESTAMP data types for data in Avro.

  • Added support for INT and DOUBLE in DDL queries. INTEGER is an alias to INT, and DOUBLE PRECISION is an alias to DOUBLE.

  • Improved performance of DROP TABLE and DROP DATABASE queries.

  • Removed the creation of _$folder$ object in Amazon S3 when a data bucket is empty.

  • Fixed an issue where ALTER TABLE ADD PARTITION threw an error when no partition value was provided.

  • Fixed an issue where DROP TABLE ignored the database name when checking partitions after the qualified name had been specified in the statement.

For more about the data types supported in Athena, see Data types in Amazon Athena.

For information about supported data type mappings between types in Athena, the JDBC driver, and Java data types, see the "Data Types" section in the JDBC Driver Installation and Configuration Guide.

August 16, 2018

Published on 2018-08-16

Released the JDBC driver version 2.0.5. The new version of the JDBC driver streams results by default, instead of paging through them, allowing business intelligence tools to retrieve large data sets faster. Compared to the previous version of the JDBC driver, there are the following performance improvements:

  • Approximately 2x performance increase when fetching less than 10K rows.

  • Approximately 5-6x performance increase when fetching more than 10K rows.

The streaming results feature is available only with the JDBC driver. It is not available with the ODBC driver. You cannot use it with the Athena API. For information about streaming results, see the JDBC Driver Installation and Configuration Guide, and search for UseResultsetStreaming.

For downloading the JDBC driver version 2.0.5 and its documentation, see Using Athena with the JDBC driver.

The JDBC driver version 2.0.5 is a drop-in replacement for the previous version of the driver (2.0.2). To ensure that you can use the JDBC driver version 2.0.5, add the athena:GetQueryResultsStream policy action to the list of policies for Athena. This policy action is not exposed directly with the API and is only used with the JDBC driver, as part of streaming results support. For an example policy, see AWS managed policy: AWSQuicksightAthenaAccess. For more information about migrating from version 2.0.2 to version 2.0.5 of the driver, see the JDBC Driver Migration Guide.

If you are migrating from a 1.x driver to a 2.x driver, you will need to migrate your existing configurations to the new configuration. We highly recommend that you migrate to the current version of the driver. For more information, see the JDBC Driver Migration Guide.

August 7, 2018

Published on 2018-08-07

You can now store Amazon Virtual Private Cloud flow logs directly in Amazon S3 in a GZIP format, where you can query them in Athena. For information, see Querying Amazon VPC flow logs and Amazon VPC Flow Logs can now be delivered to S3.

June 5, 2018

Published on 2018-06-05

Support for Views

Added support for views. You can now use CREATE VIEW, DESCRIBE VIEW, DROP VIEW, SHOW CREATE VIEW, and SHOW VIEWS in Athena. The query that defines the view runs each time you reference the view in your query. For more information, see Working with views.

Improvements and Updates to Error Messages

  • Included a GSON 2.8.0 library into the CloudTrail SerDe, to solve an issue with the CloudTrail SerDe and enable parsing of JSON strings.

  • Enhanced partition schema validation in Athena for Parquet, and, in some cases, for ORC, by allowing reordering of columns. This enables Athena to better deal with changes in schema evolution over time, and with tables added by the AWS Glue Crawler. For more information, see Handling schema updates.

  • Added parsing support for SHOW VIEWS.

  • Made the following improvements to most common error messages:

    • Replaced an Internal Error message with a descriptive error message when a SerDe fails to parse the column in an Athena query. Previously, Athena issued an internal error in cases of parsing errors. The new error message reads: "HIVE_BAD_DATA: Error parsing field value for field 0: java.lang.String cannot be cast to org.openx.data.jsonserde.json.JSONObject".

    • Improved error messages about insufficient permissions by adding more detail.

Bug Fixes

Fixed the following bugs:

  • Fixed an issue that enables the internal translation of REAL to FLOAT data types. This improves integration with the AWS Glue crawler that returns FLOAT data types.

  • Fixed an issue where Athena was not converting AVRO DECIMAL (a logical type) to a DECIMAL type.

  • Fixed an issue where Athena did not return results for queries on Parquet data with WHERE clauses that referenced values in the TIMESTAMP data type.

May 17, 2018

Published on 2018-05-17

Increased query concurrency quota in Athena from five to twenty. This means that you can submit and run up to twenty DDL queries and twenty SELECT queries at a time. Note that the concurrency quotas are separate for DDL and SELECT queries.

Concurrency quotas in Athena are defined as the number of queries that can be submitted to the service concurrently. You can submit up to twenty queries of the same type (DDL or SELECT) at a time. If you submit a query that exceeds the concurrent query quota, the Athena API displays an error message.

After you submit your queries to Athena, it processes the queries by assigning resources based on the overall service load and the amount of incoming requests. We continuously monitor and make adjustments to the service so that your queries process as fast as possible.

For information, see Service Quotas. This is an adjustable quota. You can use the Service Quotas console to request a quota increase for concurrent queries.

April 19, 2018

Published on 2018-04-19

Released the new version of the JDBC driver (version 2.0.2) with support for returning the ResultSet data as an Array data type, improvements, and bug fixes. For details, see the Release Notes for the driver.

For information about downloading the new JDBC driver version 2.0.2 and its documentation, see Using Athena with the JDBC driver.

The latest version of the JDBC driver is 2.0.2. If you are migrating from a 1.x driver to a 2.x driver, you will need to migrate your existing configurations to the new configuration. We highly recommend that you migrate to the current driver.

For information about the changes introduced in the new version of the driver, the version differences, and examples, see the JDBC Driver Migration Guide.

April 6, 2018

Published on 2018-04-06

Use auto-complete to type queries in the Athena console.

March 15, 2018

Published on 2018-03-15

Added an ability to automatically create Athena tables for CloudTrail log files directly from the CloudTrail console. For information, see Using the CloudTrail console to create an Athena table for CloudTrail logs .

February 2, 2018

Published on 2018-02-12

Added an ability to securely offload intermediate data to disk for memory-intensive queries that use the GROUP BY clause. This improves the reliability of such queries, preventing "Query resource exhausted" errors.

January 19, 2018

Published on 2018-01-19

Athena uses Presto, an open-source distributed query engine, to run queries.

With Athena, there are no versions to manage. We have transparently upgraded the underlying engine in Athena to a version based on Presto version 0.172. No action is required on your end.

With the upgrade, you can now use Presto 0.172 Functions and Operators, including Presto 0.172 Lambda Expressions in Athena.

Major updates for this release, including the community-contributed fixes, include:

  • Support for ignoring headers. You can use the skip.header.line.count property when defining tables, to allow Athena to ignore headers. This is supported for queries that use the LazySimpleSerDe and OpenCSV SerDe, and not for Grok or Regex SerDes.

  • Support for the CHAR(n) data type in STRING functions. The range for CHAR(n) is [1.255], while the range for VARCHAR(n) is [1,65535].

  • Support for correlated subqueries.

  • Support for Presto Lambda expressions and functions.

  • Improved performance of the DECIMAL type and operators.

  • Support for filtered aggregations, such as SELECT sum(col_name) FILTER, where id > 0.

  • Push-down predicates for the DECIMAL, TINYINT, SMALLINT, and REAL data types.

  • Support for quantified comparison predicates: ALL, ANY, and SOME.

  • Added functions: arrays_overlap(), array_except(), levenshtein_distance(), codepoint(), skewness(), kurtosis(), and typeof().

  • Added a variant of the from_unixtime() function that takes a timezone argument.

  • Added the bitwise_and_agg() and bitwise_or_agg() aggregation functions.

  • Added the xxhash64() and to_big_endian_64() functions.

  • Added support for escaping double quotes or backslashes using a backslash with a JSON path subscript to the json_extract() and json_extract_scalar() functions. This changes the semantics of any invocation using a backslash, as backslashes were previously treated as normal characters.

For a complete list of functions and operators, see DML queries, functions, and operators in this guide, and Functions and operators in the Presto documentation.

Athena does not support all of Presto's features. For more information, see Limitations.

Athena release notes for 2017

November 13, 2017

Published on 2017-11-13

Added support for connecting Athena to the ODBC Driver. For information, see Connecting to Amazon Athena with ODBC.

November 1, 2017

Published on 2017-11-01

Added support for querying geospatial data, and for Asia Pacific (Seoul), Asia Pacific (Mumbai), and EU (London) regions. For information, see Querying geospatial data and AWS Regions and Endpoints.

October 19, 2017

Published on 2017-10-19

Added support for EU (Frankfurt). For a list of supported regions, see AWS Regions and Endpoints.

October 3, 2017

Published on 2017-10-03

Create named Athena queries with AWS CloudFormation. For more information, see AWS::Athena::NamedQuery in the AWS CloudFormation User Guide.

September 25, 2017

Published on 2017-09-25

Added support for Asia Pacific (Sydney). For a list of supported regions, see AWS Regions and Endpoints.

August 14, 2017

Published on 2017-08-14

Added integration with the AWS Glue Data Catalog and a migration wizard for updating from the Athena managed data catalog to the AWS Glue Data Catalog. For more information, see Integration with AWS Glue.

August 4, 2017

Published on 2017-08-04

Added support for Grok SerDe, which provides easier pattern matching for records in unstructured text files such as logs. For more information, see Grok SerDe. Added keyboard shortcuts to scroll through query history using the console (CTRL + ⇧/⇩ using Windows, CMD + ⇧/⇩ using Mac).

June 22, 2017

Published on 2017-06-22

Added support for Asia Pacific (Tokyo) and Asia Pacific (Singapore). For a list of supported regions, see AWS Regions and Endpoints.

June 8, 2017

Published on 2017-06-08

Added support for Europe (Ireland). For more information, see AWS Regions and Endpoints.

May 19, 2017

Published on 2017-05-19

Added an Amazon Athena API and AWS CLI support for Athena; updated JDBC driver to version 1.1.0; fixed various issues.

  • Amazon Athena enables application programming for Athena. For more information, see Amazon Athena API Reference. The latest AWS SDKs include support for the Athena API. For links to documentation and downloads, see the SDKs section in Tools for Amazon Web Services.

  • The AWS CLI includes new commands for Athena. For more information, see the Amazon Athena API Reference.

  • A new JDBC driver 1.1.0 is available, which supports the new Athena API as well as the latest features and bug fixes. Download the driver at https://s3.amazonaws.com/athena-downloads/drivers/AthenaJDBC41-1.1.0.jar. We recommend upgrading to the latest Athena JDBC driver; however, you may still use the earlier driver version. Earlier driver versions do not support the Athena API. For more information, see Using Athena with the JDBC driver.

  • Actions specific to policy statements in earlier versions of Athena have been deprecated. If you upgrade to JDBC driver version 1.1.0 and have customer-managed or inline IAM policies attached to JDBC users, you must update the IAM policies. In contrast, earlier versions of the JDBC driver do not support the Athena API, so you can specify only deprecated actions in policies attached to earlier version JDBC users. For this reason, you shouldn't need to update customer-managed or inline IAM policies.

  • These policy-specific actions were used in Athena before the release of the Athena API. Use these deprecated actions in policies only with JDBC drivers earlier than version 1.1.0. If you are upgrading the JDBC driver, replace policy statements that allow or deny deprecated actions with the appropriate API actions as listed or errors will occur:

Deprecated Policy-Specific Action Corresponding Athena API Action
athena:RunQuery
athena:StartQueryExecution
athena:CancelQueryExecution
athena:StopQueryExecution
athena:GetQueryExecutions
athena:ListQueryExecutions

Improvements

  • Increased the query string length limit to 256 KB.

Bug Fixes

  • Fixed an issue that caused query results to look malformed when scrolling through results in the console.

  • Fixed an issue where a \u0000 character string in Amazon S3 data files would cause errors.

  • Fixed an issue that caused requests to cancel a query made through the JDBC driver to fail.

  • Fixed an issue that caused the AWS CloudTrail SerDe to fail with Amazon S3 data in US East (Ohio).

  • Fixed an issue that caused DROP TABLE to fail on a partitioned table.

April 4, 2017

Published on 2017-04-04

Added support for Amazon S3 data encryption and released JDBC driver update (version 1.0.1) with encryption support, improvements, and bug fixes.

Features

  • Added the following encryption features:

    • Support for querying encrypted data in Amazon S3.

    • Support for encrypting Athena query results.

  • A new version of the driver supports new encryption features, adds improvements, and fixes issues.

  • Added the ability to add, replace, and change columns using ALTER TABLE. For more information, see Alter Column in the Hive documentation.

  • Added support for querying LZO-compressed data.

For more information, see Encryption at rest.

Improvements

  • Better JDBC query performance with page-size improvements, returning 1,000 rows instead of 100.

  • Added ability to cancel a query using the JDBC driver interface.

  • Added ability to specify JDBC options in the JDBC connection URL. See Using Athena with the JDBC driver for the most current JDBC driver.

  • Added PROXY setting in the driver, which can now be set using ClientConfiguration in the AWS SDK for Java.

Bug Fixes

Fixed the following bugs:

  • Throttling errors would occur when multiple queries were issued using the JDBC driver interface.

  • The JDBC driver would stop when projecting a decimal data type.

  • The JDBC driver would return every data type as a string, regardless of how the data type was defined in the table. For example, selecting a column defined as an INT data type using resultSet.GetObject() would return a STRING data type instead of INT.

  • The JDBC driver would verify credentials at the time a connection was made, rather than at the time a query would run.

  • Queries made through the JDBC driver would fail when a schema was specified along with the URL.

March 24, 2017

Published on 2017-03-24

Added the AWS CloudTrail SerDe, improved performance, fixed partition issues.

Features

Improvements

  • Improved performance when scanning a large number of partitions.

  • Improved performance on MSCK Repair Table operation.

  • Added ability to query Amazon S3 data stored in regions other than your primary Region. Standard inter-region data transfer rates for Amazon S3 apply in addition to standard Athena charges.

Bug Fixes

  • Fixed a bug where a "table not found error" might occur if no partitions are loaded.

  • Fixed a bug to avoid throwing an exception with ALTER TABLE ADD PARTITION IF NOT EXISTS queries.

  • Fixed a bug in DROP PARTITIONS.

February 20, 2017

Published on 2017-02-20

Added support for AvroSerDe and OpenCSVSerDe, US East (Ohio) Region, and bulk editing columns in the console wizard. Improved performance on large Parquet tables.

Features

  • Introduced support for new SerDes:

  • US East (Ohio) Region (us-east-2) launch. You can now run queries in this region.

  • You can now use the Create Table From S3 bucket data form to define table schema in bulk. In the query editor, choose Create, S3 bucket data, and then choose Bulk add columns in the Column details section.

    Type name value pairs in the text box and choose Add.

Improvements

  • Improved performance on large Parquet tables.