> **Window Agg**
> <table>
> <tr>
> <td width="25%"><img src="assets/ex_window_aggregate.png"></td>
> <td>Computes window functions (e.g., <code>ROW_NUMBER()</code>, <code>RANK()</code>). It requires the input set to be partitioned and sorted, allowing the engine to slide a 'window' over the rows and calculate values relative to the current row.</td>
> </tr>
> </table>
>
> ```sql
> -- Calculating row numbers over a sorted set
> EXPLAIN (ANALYZE, COSTS, BUFFERS, VERBOSE)
> SELECT name, row_number() OVER (ORDER BY name)
> FROM animals;
> ```
>
> 
>
> <!-- literal-explain-plan
> Captured EXPLAIN provenance for the adjacent reader-facing visual plan.
> Canonical capture metadata lives in scratch/actual_operation_plans.json.
>
> WindowAgg (cost=838.40..1013.39 rows=10000 width=19) (actual time=4.593..5.606 rows=10000 loops=1)
> Output: name, row_number() OVER (?)
> Buffers: shared hit=77
> -> Sort (cost=838.39..863.39 rows=10000 width=11) (actual time=4.586..4.785 rows=10000 loops=1)
> Output: name
> Sort Key: animals.name
> Sort Method: quicksort Memory: 385kB
> Buffers: shared hit=77
> -> Seq Scan on public.animals (cost=0.00..174.00 rows=10000 width=11) (actual time=0.003..0.325 rows=10000 loops=1)
> Output: name
> Buffers: shared hit=74
> Planning:
> Buffers: shared hit=86
> Planning Time: 0.179 ms
> Execution Time: 5.810 ms
> -->
>
>
> <!--
> Raw-capture provenance — separate run.
> SQL, setup, dataset, settings, and scope: artifacts/chapter4_capture_matrix.json.
> Target: PostgreSQL 18.x companion fixture. Cache state: uncontrolled.
> Boundary: pg_wait_tracer backend execution root; client states are included when the chart shows them.
> Fidelity: exact pg_wait_tracer export. Not the adjacent EXPLAIN run; compare state shape, not durations.
> -->
>
> 
>
> <table>
> <tr>
> <td rowspan="2" width="25%"><img src="assets/ex_window_aggregate.svg"></td>
> <td><b>Performance</b></td><td>CPU-intensive as it must track state across multiple rows; memory-intensive if using large partitions.</td>
> </tr>
> <tr><td><b>Cost</b></td><td><code>window function cost * number of rows</code></td></tr>
> </table>