---
id: online-compute_FlinkSQL_flinksql_017
name: Row-Level TopN (Windowless)
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 spending stream, retrieves the top 3 records by spending amount grouped by `country_id` without any window, and outputs the results directly to the console.

**Business Background and Objective**: Generate user spending records using a datagen built-in table at a rate of 1000 rows per second. Fields include `country_id` (country ID, 1–30), `user_id` (user ID, 1–100,000), and `cost_money` (spending amount, 0–10,000). No event time or watermark is required, since no window operations are involved.

Use the `ROW_NUMBER()` window function, partitioned by `country_id` and sorted by `cost_money` in descending order, keeping only the top 3 records per partition (`row_num <= 3`), and output the results directly to the console table. This is a continuous TopN query where each country's top 3 dynamically updates as new data flows in.

**Source Table Definition**:
- `spend_source` (datagen connector):
  - `country_id INT`: Country ID, randomly generated in the range 1–30
  - `user_id INT`: User ID, randomly generated in the range 1–100,000
  - `cost_money DOUBLE`: Spending amount, randomly generated in the range 0–10,000
  - Generation rate: `rows-per-second = 1000`

**Output Table Definition**:
- `console_output` (print connector):
  - `country_id INT`: Country ID
  - `user_id INT`: User ID
  - `cost_money DOUBLE`: Spending amount
  - `row_num BIGINT`: Row number

**TopN Logic**:
- Use `ROW_NUMBER() OVER (PARTITION BY country_id ORDER BY cost_money DESC)` to generate row numbers
- Apply `WHERE row_num <= 3` to keep the top 3 per country
- No window operation is required; no event time or watermark needs to be defined

**Output Requirements**:
- Use `INSERT INTO console_output` to output the results.
- Output field order: `country_id`, `user_id`, `cost_money`, `row_num`