tasks/online-compute/FlinkSQL/flinksql_012_en/task.md

metadata

id: online-compute_FlinkSQL_flinksql_012
name: Session Window User Behavior Statistics
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 a user behavior data source, computes per-user behavioral statistics over a 30-minute session window (SESSION), and outputs the results to the console.

Business Background and Objective: Simulate a user behavior stream using a datagen built-in table. Group by a 30-minute session window to compute the total action count (COUNT) and the number of distinct action types (COUNT DISTINCT) per user within each session window. Output the results to the console.

Source Table Definition:

• user_actions (user behavior stream, datagen connector):
  • user_id INT: User ID, randomly generated in the range 1–5000
  • action_id INT: Action type ID, randomly generated in the range 1–10
  • event_time: Uses LOCALTIMESTAMP to generate event time, with a WATERMARK delay of 5 seconds
  • Generation rate: rows-per-second = 2000

Output Table Definition:

• console_output (print connector):
  • user_id INT: User ID
  • session_start TIMESTAMP(3): Session window start time
  • session_end TIMESTAMP(3): Session window end time
  • action_count BIGINT: Total action count
  • unique_actions BIGINT: Number of distinct action types

SQL Logic:

• Apply SESSION(event_time, INTERVAL '30' MINUTE) session window on user_actions
• Group by SESSION(event_time, INTERVAL '30' MINUTE) and user_id
• Aggregate COUNT(*) AS action_count and COUNT(DISTINCT action_id) AS unique_actions
• Use SESSION_START and SESSION_END functions to obtain the window start and end times

Output Requirements:

• Use INSERT INTO console_output to output the results.
• Output field order: user_id, session_start, session_end, action_count, unique_actions