Aggregate a Stream in a Tumbling Window with Confluent Cloud for Apache Flink

Aggregate a continuous stream into fixed, non-overlapping intervals in Confluent Cloud for Apache Flink® by using a tumbling window with the window table-valued functions (Window TVFs) SQL-standard syntax. Each event belongs to exactly one window, so you can compute per-window minimum, maximum, average, first or last record, or totals over an unbounded Flink SQL stream.

In this guide, you learn how to run an Flink SQL statement that identifies the maximum and minimum orders from a continuous data stream of orders data.

This topic shows the following steps:

Step 1: Inspect the example stream
Step 2: View aggregated results in a tumbling window

Prerequisites

You need the following prerequisites to use Flink in Confluent Cloud Console.

Access to Confluent Cloud.

Step 1: Inspect the example stream

In this step, you query the read-only orders table in the examples.marketplace database to inspect the stream for fields that you can aggregate.

Log in to Confluent Cloud and navigate to your Flink workspace.
In the Use catalog dropdown, select your environment.
In the Use database dropdown, select your Kafka cluster.

Run the following statement to inspect the example orders stream.

SELECT * FROM examples.marketplace.orders;

Your output should resemble:

order_id                                customer_id   product_id  price
68362284-34df-41a3-87fb-50b79647b786    3195          1267        47.48
6e03663e-d20b-4a23-848a-aec959d794e3    3094          1412        50.92
84217b5d-7dcb-46d1-9600-675a3734a3ed    3038          1094        83.56
...

Step 2: View aggregated results in a tumbling window

Run the following statement to start a windowed query on the orders data.

SELECT
  window_start,
  window_end,
  MIN(price) as minimum_order_value,
  MAX(price) as maximum_order_value
FROM TUMBLE(TABLE examples.marketplace.orders, DESCRIPTOR($rowtime), INTERVAL '10' SECOND)
GROUP BY window_start, window_end;

Your output should resemble:

window_start            window_end              minimum_order_value maximum_order_value
2023-09-12 08:54:20.000 2023-09-12 08:54:30.000 10.05               99.75
2023-09-12 08:54:30.000 2023-09-12 08:54:40.000 10.22               99.88
2023-09-12 08:54:40.000 2023-09-12 08:54:50.000 10.09               150.45
...

The Flink statement created with this query identifies the minimum and maximum order value in each 10-second window.

Aggregate a Stream in a Tumbling Window with Confluent Cloud for Apache Flink

Prerequisites

Step 1: Inspect the example stream

Step 2: View aggregated results in a tumbling window

Related content