Document History for Amazon Kinesis Data Analytics
The following table describes the important changes to the documentation since the last release of Amazon Kinesis Data Analytics.
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API version: 2015-08-14
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Latest documentation update: July 18, 2018
| Change | Description | Date |
|---|---|---|
| Kinesis Data Analytics available in Frankfurt region | Kinesis Analytics is now available in the EU (Frankfurt) Region region. For more information, see AWS Regions and Endpoints: Kinesis Data Analytics. | July 18, 2018 |
| Use reference data in the console | You can now work with application reference data in the console. For more information, see Example: Adding Reference Data to a Kinesis Data Analytics Application . | July 13, 2018 |
| Windowed query examples | Example applications for windows and aggregation. For more information, see Examples: Windows and Aggregation . | July 9, 2018 |
| Testing applications | Guidance on testing changes to application schema and code. For more information, see Testing Applications . | July 3, 2018 |
| Example applications for preprocessing data | Additional code samples for REGEX_LOG_PARSE, REGEX_REPLACE, and DateTime operators. For more information, see Examples: Transforming Data . | May 18, 2018 |
| Increase in size of returned rows and SQL code | The limit for the size for a returned row is increased to 512 KB, and the limit for the size of the SQL code in an application is increased to 100 KB. For more information, see Limits. | May 2, 2018 |
| AWS Lambda function examples in Java and .NET | Code samples for creating Lambda functions for preprocessing records and for application destinations. For more information, see Creating Lambda Functions for Preprocessing and Creating Lambda Functions for Application Destinations. | March 22, 2018 |
New HOTSPOTS function
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Locate and return information about relatively dense regions in your data. For more information, see Example: Detecting Hotspots on a Stream (HOTSPOTS Function). | March 19, 2018 |
| Lambda function as a destination | Send analytics results to a Lambda function as a destination. For more information, see Using a Lambda Function as Output. | December 20, 2017 |
New RANDOM_CUT_FOREST_WITH_EXPLANATION function
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Get an explanation of what fields contribute to an anomaly score in a data stream. For more information, see Example: Detecting Data Anomalies and Getting an Explanation (RANDOM_CUT_FOREST_WITH_EXPLANATION Function). | November 2, 2017 |
| Schema discovery on static data | Run schema discovery on static data stored in an Amazon S3 bucket. For more information, see Using the Schema Discovery Feature on Static Data. | October 6, 2017 |
| Lambda preprocessing feature | Preprocess records in an input stream with AWS Lambda before analysis. For more information, see Preprocessing Data Using a Lambda Function. | October 6, 2017 |
| Auto scaling applications | Automatically increase the data throughput of your application with auto scaling. For more information, see Automatically Scaling Applications to Increase Throughput. | September 13, 2017 |
| Multiple in-application input streams | Increase application throughput with multiple in-application streams. For more information, see Parallelizing Input Streams for Increased Throughput. | June 29, 2017 |
| Guide to using the AWS Management Console for Kinesis Data Analytics | Edit an inferred schema and SQL code using the schema editor and SQL editor in the Kinesis Data Analytics console. For more information, see Step 4 (Optional) Edit the Schema and SQL Code Using the Console. | April 7, 2017 |
| Public release | Public release of the Amazon Kinesis Data Analytics Developer Guide. | August 11, 2016 |
| Preview release | Preview release of the Amazon Kinesis Data Analytics Developer Guide. | January 29, 2016 |
