Error Handling - Amazon Kinesis Data Analytics for SQL Applications Developer Guide
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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.

Error Handling

Amazon Kinesis Data Analytics returns API or SQL errors directly to you. For more information about API operations, see Actions. For more information about handling SQL errors, see Amazon Kinesis Data Analytics SQL Reference.

Amazon Kinesis Data Analytics reports runtime errors using an in-application error stream called error_stream.

Reporting Errors Using an In-Application Error Stream

Amazon Kinesis Data Analytics reports runtime errors to the in-application error stream called error_stream. The following are examples of errors that might occur:

  • A record read from the streaming source does not conform to the input schema.

  • Your application code specifies division by zero.

  • The rows are out of order (for example, a record appears on the stream with a ROWTIME value that a user modified that causes a record to go out of order).

  • The data in the source stream can't be converted to the data type specified in the schema (Coercion error). For information about what data types can be converted, see Mapping JSON Data Types to SQL Data Types.

We recommend that you handle these errors programmatically in your SQL code or persist the data on the error stream to an external destination. This requires that you add an output configuration (see Configuring Application Output) to your application. For an example of how the in-application error stream works, see Example: Exploring the In-Application Error Stream.


Your Kinesis Data Analytics application can't access or modify the error stream programmatically because the error stream is created using the system account. You must use the error output to determine what errors your application might encounter. You then write your application's SQL code to handle anticipated error conditions.

Error Stream Schema

The error stream has the following schema:


Data Type




The time when the error occurred









The row time of the incoming record



The hex-encoded data in the original row. You can use standard libraries to hex decode this value, or use web resources such as this Hex to String Converter.



The originating pump, as defined with CREATE PUMP