Tumbling Windows (Aggregations Using GROUP BY) - Amazon Kinesis Data Analytics for SQL Applications Developer Guide

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

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Tumbling Windows (Aggregations Using GROUP BY)

When a windowed query processes each window in a non-overlapping manner, the window is referred to as a tumbling window. In this case, each record on an in-application stream belongs to a specific window. It is processed only once (when the query processes the window to which the record belongs).

Timeline showing non-overlapping windows processing data streams at distinct time intervals.

For example, an aggregation query using a GROUP BY clause processes rows in a tumbling window. The demo stream in the getting started exercise receives stock price data that is mapped to the in-application stream SOURCE_SQL_STREAM_001 in your application. This stream has the following schema.

(TICKER_SYMBOL VARCHAR(4), 
 SECTOR varchar(16), 
 CHANGE REAL, 
 PRICE REAL)

In your application code, suppose that you want to find aggregate (min, max) prices for each ticker over a one-minute window. You can use the following query.

SELECT STREAM ROWTIME,
              Ticker_Symbol,
              MIN(Price) AS Price,
              MAX(Price) AS Price
FROM     "SOURCE_SQL_STREAM_001"
GROUP BY Ticker_Symbol, 
         STEP("SOURCE_SQL_STREAM_001".ROWTIME BY INTERVAL '60' SECOND);

The preceding is an example of a windowed query that is time-based. The query groups records by ROWTIME values. For reporting on a per-minute basis, the STEP function rounds down the ROWTIME values to the nearest minute.

Note

You can also use the FLOOR function to group records into windows. However, FLOOR can only round time values down to a whole time unit (hour, minute, second, and so on). STEP is recommended for grouping records into tumbling windows because it can round values down to an arbitrary interval, for example, 30 seconds.

This query is an example of a nonoverlapping (tumbling) window. The GROUP BY clause groups records in a one-minute window, and each record belongs to a specific window (no overlapping). The query emits one output record per minute, providing the min/max ticker price recorded at the specific minute. This type of query is useful for generating periodic reports from the input data stream. In this example, reports are generated each minute.

To test the query

  1. Set up an application by following the getting started exercise.

  2. Replace the SELECT statement in the application code by the preceding SELECT query. The resulting application code is shown following:

    CREATE OR REPLACE STREAM "DESTINATION_SQL_STREAM" (
                                   ticker_symbol VARCHAR(4), 
                                   Min_Price     DOUBLE, 
                                   Max_Price     DOUBLE);
-- CREATE OR REPLACE PUMP to insert into output
CREATE OR REPLACE PUMP "STREAM_PUMP" AS 
  INSERT INTO "DESTINATION_SQL_STREAM" 
    SELECT STREAM Ticker_Symbol,
                  MIN(Price) AS Min_Price,
                  MAX(Price) AS Max_Price
    FROM    "SOURCE_SQL_STREAM_001"
    GROUP BY Ticker_Symbol, 
             STEP("SOURCE_SQL_STREAM_001".ROWTIME BY INTERVAL '60' SECOND);