For new projects, we recommend that you use the new Managed Service for Apache Flink Studio over Kinesis Data Analytics for SQL Applications. Managed Service for Apache Flink Studio combines ease of use with advanced analytical capabilities, enabling you to build sophisticated stream processing applications in minutes.
Step 3: Configure Application Output
After completing Step 2: Create an Application, you have application code that is reading heart rate data from a streaming source and assigning an anomaly score to each.
You can now send the application results from the in-application stream to an
external destination, which is another Kinesis data stream
(OutputStreamTestingAnomalyScores). You can analyze the anomaly
scores and determine which heart rate is anomalous. You can then extend this
application further to generate alerts.
Follow these steps to configure application output:
-
Open the Amazon Kinesis Data Analytics console. In the SQL editor, choose either Destination or Add a destination in the application dashboard.
-
On the Connect to destination page, choose the
OutputStreamTestingAnomalyScoresstream that you created in the preceding section.Now you have an external destination, where Amazon Kinesis Data Analytics persists any records your application writes to the in-application stream
DESTINATION_SQL_STREAM. -
You can optionally configure AWS Lambda to monitor the
OutputStreamTestingAnomalyScoresstream and send you alerts. For instructions, see Preprocessing Data Using a Lambda Function. If you don't set alerts, you can review the records that Kinesis Data Analytics writes to the external destination, which is the Kinesis data streamOutputStreamTestingAnomalyScores, as described in Step 4: Verify Output.
Next Step
