After careful consideration, we have decided to discontinue Amazon Kinesis Data Analytics for SQL applications:

1. From **September 1, 2025**, we won't provide any bug fixes for Amazon Kinesis Data Analytics for SQL applications because we will have limited support for it, given the upcoming discontinuation.

2. From **October 15, 2025**, you will not be able to create new Kinesis Data Analytics for SQL applications.

3. 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](discontinuation.md).

# Example: Split Strings into Multiple Fields (VARIABLE\$1COLUMN\$1LOG\$1PARSE Function)
<a name="examples-transforming-strings-variablecolumnlogparse"></a>

This example uses the `VARIABLE_COLUMN_LOG_PARSE` function to manipulate strings in Kinesis Data Analytics. `VARIABLE_COLUMN_LOG_PARSE` splits an input string into fields separated by a delimiter character or a delimiter string. For more information, see [VARIABLE\$1COLUMN\$1LOG\$1PARSE](https://docs.aws.amazon.com/kinesisanalytics/latest/sqlref/sql-reference-variable-column-log-parse.html) in the *Amazon Managed Service for Apache Flink SQL Reference*.

In this example, you write semi-structured records to an Amazon Kinesis data stream. The example records are as follows:

```
{ "Col_A" : "string",
  "Col_B" : "string",
  "Col_C" : "string",
  "Col_D_Unstructured" : "value,value,value,value"}
{ "Col_A" : "string",
  "Col_B" : "string",
  "Col_C" : "string",
  "Col_D_Unstructured" : "value,value,value,value"}
```



You then create an Kinesis Data Analytics application on the console, using the Kinesis stream as the streaming source. The discovery process reads sample records on the streaming source and infers an in-application schema with four columns, as shown following:

![\[Console screenshot showing in-application schema with 4 columns.\]](http://docs.aws.amazon.com/kinesisanalytics/latest/dev/images/unstructured-10.png)


Then, you use the application code with the `VARIABLE_COLUMN_LOG_PARSE` function to parse the comma-separated values, and insert normalized rows in another in-application stream, as shown following:



![\[Console screenshot showing real-time analytics tab with in-application stream.\]](http://docs.aws.amazon.com/kinesisanalytics/latest/dev/images/unstructured-20.png)


**Topics**
+ [Step 1: Create a Kinesis Data Stream](#examples-transforming-strings-variablecolumnlogparse-1)
+ [Step 2: Create the Kinesis Data Analytics Application](#examples-transforming-strings-variablecolumnlogparse-2)

## Step 1: Create a Kinesis Data Stream
<a name="examples-transforming-strings-variablecolumnlogparse-1"></a>

Create an Amazon Kinesis data stream and populate the log records as follows:

1. Sign in to the AWS Management Console and open the Kinesis console at [https://console.aws.amazon.com/kinesis](https://console.aws.amazon.com/kinesis).

1. Choose **Data Streams** in the navigation pane.

1. Choose **Create Kinesis stream**, and create a stream with one shard. For more information, see [Create a Stream](https://docs.aws.amazon.com/streams/latest/dev/learning-kinesis-module-one-create-stream.html) in the *Amazon Kinesis Data Streams Developer Guide*.

1. Run the following Python code to populate the sample log records. This simple code continuously writes the same log record to the stream.

   ```
    
   import json
   import boto3
   
   STREAM_NAME = "ExampleInputStream"
   
   
   def get_data():
       return {"Col_A": "a", "Col_B": "b", "Col_C": "c", "Col_E_Unstructured": "x,y,z"}
   
   
   def generate(stream_name, kinesis_client):
       while True:
           data = get_data()
           print(data)
           kinesis_client.put_record(
               StreamName=stream_name, Data=json.dumps(data), PartitionKey="partitionkey"
           )
   
   
   if __name__ == "__main__":
       generate(STREAM_NAME, boto3.client("kinesis"))
   ```

   

## Step 2: Create the Kinesis Data Analytics Application
<a name="examples-transforming-strings-variablecolumnlogparse-2"></a>

Create an Kinesis Data Analytics application as follows:

1. Open the Managed Service for Apache Flink console at [ https://console.aws.amazon.com/kinesisanalytics](https://console.aws.amazon.com/kinesisanalytics).

1. Choose **Create application**, type an application name, and choose **Create application**.

1. On the application details page, choose **Connect streaming data**. 

1. On the **Connect to source** page, do the following:

   1. Choose the stream that you created in the preceding section.

   1. Choose the option to create an IAM role.

   1. Choose **Discover schema**. Wait for the console to show the inferred schema and samples records used to infer the schema for the in-application stream created. Note that the inferred schema has only one column.

   1. Choose **Save and continue**.

   

1. On the application details page, choose **Go to SQL editor**. To start the application, choose **Yes, start application** in the dialog box that appears.

1. In the SQL editor, write application code, and verify the results:

   1. Copy the following application code and paste it into the editor:

      ```
      CREATE OR REPLACE STREAM "DESTINATION_SQL_STREAM"(
                  "column_A" VARCHAR(16),
                  "column_B" VARCHAR(16),
                  "column_C" VARCHAR(16),
                  "COL_1" VARCHAR(16),             
                  "COL_2" VARCHAR(16),            
                  "COL_3" VARCHAR(16));
      
      CREATE OR REPLACE PUMP "SECOND_STREAM_PUMP" AS
      INSERT INTO "DESTINATION_SQL_STREAM"
         SELECT STREAM  t."Col_A", t."Col_B", t."Col_C",
                        t.r."COL_1", t.r."COL_2", t.r."COL_3"
         FROM (SELECT STREAM 
                 "Col_A", "Col_B", "Col_C",
                 VARIABLE_COLUMN_LOG_PARSE ("Col_E_Unstructured",
                                           'COL_1 TYPE VARCHAR(16), COL_2 TYPE VARCHAR(16), COL_3 TYPE VARCHAR(16)',
                                           ',') AS r 
               FROM "SOURCE_SQL_STREAM_001") as t;
      ```

   1. Choose **Save and run SQL**. On the **Real-time analytics **tab, you can see all the in-application streams that the application created and verify the data.