tasks/online-compute/FlinkSQL/flinksql_018_en/task.md

metadata

id: online-compute_FlinkSQL_flinksql_018
name: Dual Output (Detail + Windowed Aggregation)
category: online-compute/FlinkSQL
timeout_seconds: 600
modality: pure-text
engine: flink-sql

Prompt

I need you to write a Flink SQL that uses the built-in datagen connector to simulate an order stream, simultaneously outputting detail records to console1 and windowed aggregation results over a 1-minute tumbling window to console2.

Business Background and Objective: Generate an order event stream using a datagen built-in table at a rate of 2000 rows per second. Fields include order_id (order ID), user_id (user ID, 1–10,000), and amount (order amount, 0–1000). Use LOCALTIMESTAMP as the event time and set a 5-second watermark delay.

The same source data must be simultaneously output to two sinks:

• console1: Detail passthrough, directly outputting the original fields
• console2: Aggregation over a 1-minute TUMBLE tumbling window, grouped by user_id to compute the order count and total amount

Source Table Definition:

• order_source (datagen connector):
  • order_id BIGINT: Order ID, randomly generated
  • user_id INT: User ID, randomly generated in the range 1–10,000
  • amount DOUBLE: Order amount, randomly generated in the range 0–1000
  • event_time: Uses LOCALTIMESTAMP to generate event time, with a WATERMARK delay of 5 seconds
  • Generation rate: rows-per-second = 2000

Output Table 1 Definition:

• console1 (print connector, detail output):
  • order_id BIGINT
  • user_id INT
  • amount DOUBLE

Output Table 2 Definition:

• console2 (print connector, aggregation output):
  • window_start TIMESTAMP(3): Window start time
  • user_id INT: User ID
  • order_cnt BIGINT: Order count within the window
  • total_amount DOUBLE: Total order amount within the window

Aggregation Logic:

• Detail output: Direct passthrough from order_source
• Aggregation output: TUMBLE 1-minute tumbling window, GROUP BY user_id
• Aggregation metrics: COUNT(*) AS order_cnt, SUM(amount) AS total_amount

Output Requirements:

• Use two INSERT INTO statements to write to console1 and console2 respectively.
• console1 output field order: order_id, user_id, amount
• console2 output field order: window_start, user_id, order_cnt, total_amount