After careful consideration, we have decided to discontinue Amazon Kinesis Data Analytics for SQL applications in two steps:
1. From October 15, 2025, you will not be able to create new Kinesis Data Analytics for SQL applications.
2. We will delete your applications starting January 27, 2026. You will not be able to start or operate your Amazon Kinesis Data Analytics for SQL applications. Support will no longer be available for Amazon Kinesis Data Analytics for SQL from that time. For more information, see Amazon Kinesis Data Analytics for SQL Applications discontinuation.
Example: Creating Simple Alerts
In this Kinesis Data Analytics application, the query runs continuously on the in-application stream that is created over the demo stream. For more information, see Continuous Queries.
If any rows show a stock price change that is greater than 1 percent, those rows are inserted into another in-application stream. In the exercise, you can configure the application output to persist the results to an external destination. You can then further investigate the results. For example, you can use an AWS Lambda function to process records and send you alerts.
To create a simple alerts application
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Create the analytics application as described in the Kinesis Data Analytics Getting Started exercise.
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In the SQL editor in Kinesis Data Analytics, replace the application code with the following:
CREATE OR REPLACE STREAM "DESTINATION_SQL_STREAM" (ticker_symbol VARCHAR(4), sector VARCHAR(12), change DOUBLE, price DOUBLE); CREATE OR REPLACE PUMP "STREAM_PUMP" AS INSERT INTO "DESTINATION_SQL_STREAM" SELECT STREAM ticker_symbol, sector, change, price FROM "SOURCE_SQL_STREAM_001" WHERE (ABS(Change / (Price - Change)) * 100) > 1;
The
SELECT
statement in the application code filters rows in theSOURCE_SQL_STREAM_001
for stock price changes greater than 1 percent. It then inserts those rows into another in-application streamDESTINATION_SQL_STREAM
using a pump. For more information about the coding pattern that explains using pumps to insert rows into in-application streams, see Application Code. -
Choose Save and run SQL.
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Add a destination. To do this, either choose the Destination tab in the SQL editor or choose Add a destination on the application details page.
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In the SQL editor, choose the Destination tab, and then choose Connect to a destination.
On the Connect to destination page, choose Create New.
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Choose Go to Kinesis Streams.
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On the Amazon Kinesis Data Streams console, create a new Kinesis stream (for example,
gs-destination
) with one shard. Wait until the stream status is ACTIVE. -
Return to the Kinesis Data Analytics console. On the Connect to destination page, choose the stream that you created.
If the stream does not appear, refresh the page.
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Choose Save and continue.
Now you have an external destination, a Kinesis data stream, where Kinesis Data Analytics persists your application output in the
DESTINATION_SQL_STREAM
in-application stream. -
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Configure AWS Lambda to monitor the Kinesis stream you created and invoke a Lambda function.
For instructions, see Preprocessing Data Using a Lambda Function.