Named Windows in window functions

documentation/cookbook/integrations/grafana/overlay-timeshift.md

@@ -28,11 +28,10 @@ WITH sampled AS (
      AND symbol = @symbol
 ), cumulative AS (
      SELECT timestamp, symbol,
-           SUM(traded_value)
-                OVER (ORDER BY timestamp) AS cumulative_value,
-           SUM(volume)
-                OVER (ORDER BY timestamp) AS cumulative_volume
+           SUM(traded_value) OVER w AS cumulative_value,
+           SUM(volume) OVER w AS cumulative_volume
      FROM sampled
+     WINDOW w AS (ORDER BY timestamp)
 )
 SELECT timestamp as time, cumulative_value/cumulative_volume AS vwap_yesterday FROM cumulative;
 ```
@@ -52,11 +51,10 @@ WITH sampled AS (
      AND symbol = @symbol
 ), cumulative AS (
      SELECT timestamp, symbol,
-           SUM(traded_value)
-                OVER (ORDER BY timestamp) AS cumulative_value,
-           SUM(volume)
-                OVER (ORDER BY timestamp) AS cumulative_volume
+           SUM(traded_value) OVER w AS cumulative_value,
+           SUM(volume) OVER w AS cumulative_volume
      FROM sampled
+     WINDOW w AS (ORDER BY timestamp)
 )
 SELECT dateadd('d',-1,timestamp) as time, cumulative_value/cumulative_volume AS vwap_today FROM cumulative;
 ```

documentation/cookbook/sql/finance/bollinger-bands.md

@@ -36,15 +36,10 @@ WITH OHLC AS (
   SELECT
     timestamp,
     close,
-    AVG(close) OVER (
-      ORDER BY timestamp
-      ROWS 19 PRECEDING
-    ) AS sma20,
-    AVG(close * close) OVER (
-      ORDER BY timestamp
-      ROWS 19 PRECEDING
-    ) AS avg_close_sq
+    AVG(close) OVER w AS sma20,
+    AVG(close * close) OVER w AS avg_close_sq
   FROM OHLC
+  WINDOW w AS (ORDER BY timestamp ROWS 19 PRECEDING)
 )
 SELECT
   timestamp,
@@ -74,9 +69,11 @@ The core of the Bollinger Bands calculation is the rolling standard deviation. P
 
 **Different period lengths:**
 ```sql
--- 10-period Bollinger Bands (change 19 to 9)
-AVG(close) OVER (ORDER BY timestamp ROWS 9 PRECEDING) AS sma10,
-AVG(close * close) OVER (ORDER BY timestamp ROWS 9 PRECEDING) AS avg_close_sq
+-- 10-period Bollinger Bands (change ROWS 19 to ROWS 9)
+AVG(close) OVER w AS sma10,
+AVG(close * close) OVER w AS avg_close_sq
+...
+WINDOW w AS (ORDER BY timestamp ROWS 9 PRECEDING)
 ```
 
 **Different band multipliers:**
@@ -116,17 +113,10 @@ WITH OHLC AS (
     timestamp,
     symbol,
     close,
-    AVG(close) OVER (
-      PARTITION BY symbol
-      ORDER BY timestamp
-      ROWS 19 PRECEDING
-    ) AS sma20,
-    AVG(close * close) OVER (
-      PARTITION BY symbol
-      ORDER BY timestamp
-      ROWS 19 PRECEDING
-    ) AS avg_close_sq
+    AVG(close) OVER w AS sma20,
+    AVG(close * close) OVER w AS avg_close_sq
   FROM OHLC
+  WINDOW w AS (PARTITION BY symbol ORDER BY timestamp ROWS 19 PRECEDING)
 )
 SELECT
   timestamp,

documentation/cookbook/sql/finance/bollinger-bandwidth.md

@@ -46,17 +46,10 @@ bands AS (
     timestamp,
     symbol,
     close,
-    AVG(close) OVER (
-      PARTITION BY symbol
-      ORDER BY timestamp
-      ROWS BETWEEN 19 PRECEDING AND CURRENT ROW
-    ) AS sma20,
-    AVG(close * close) OVER (
-      PARTITION BY symbol
-      ORDER BY timestamp
-      ROWS BETWEEN 19 PRECEDING AND CURRENT ROW
-    ) AS avg_close_sq
+    AVG(close) OVER w AS sma20,
+    AVG(close * close) OVER w AS avg_close_sq
   FROM daily_ohlc
+  WINDOW w AS (PARTITION BY symbol ORDER BY timestamp ROWS 19 PRECEDING)
 ),
 bollinger AS (
   SELECT
@@ -88,9 +81,10 @@ with_range AS (
     upper_band,
     lower_band,
     bandwidth,
-    min(bandwidth) OVER (PARTITION BY symbol) AS min_bw,
-    max(bandwidth) OVER (PARTITION BY symbol) AS max_bw
+    min(bandwidth) OVER w AS min_bw,
+    max(bandwidth) OVER w AS max_bw
   FROM with_bandwidth
+  WINDOW w AS (PARTITION BY symbol)
 )
 SELECT
   timestamp,

documentation/cookbook/sql/finance/vwap.md

@@ -32,9 +32,9 @@ WITH sampled AS (
 )
 SELECT
   timestamp, symbol,
-  SUM(traded_value) OVER (ORDER BY timestamp) /
-    SUM(total_volume) OVER (ORDER BY timestamp) AS vwap
-FROM sampled;
+  SUM(traded_value) OVER w / SUM(total_volume) OVER w AS vwap
+FROM sampled
+WINDOW w AS (ORDER BY timestamp);
 ```
 
 This query:
@@ -43,11 +43,12 @@ This query:
 
 ## How it works
 
-The key insight is using `SUM(...) OVER (ORDER BY timestamp)` to create running totals, then dividing them directly:
+The key insight is using `SUM(...) OVER w` with a named window to create running totals, then dividing them directly:
 
 ```sql
-SUM(traded_value) OVER (ORDER BY timestamp) /
-  SUM(total_volume) OVER (ORDER BY timestamp) AS vwap
+SUM(traded_value) OVER w / SUM(total_volume) OVER w AS vwap
+...
+WINDOW w AS (ORDER BY timestamp)
 ```
 
 When using `SUM() OVER (ORDER BY timestamp)` without specifying a frame clause, QuestDB defaults to summing from the first row to the current row, which is exactly what we need for cumulative VWAP.
@@ -68,9 +69,9 @@ WITH sampled AS (
 )
 SELECT
   timestamp, symbol,
-  SUM(traded_value) OVER (PARTITION BY symbol ORDER BY timestamp) /
-    SUM(total_volume) OVER (PARTITION BY symbol ORDER BY timestamp) AS vwap
-FROM sampled;
+  SUM(traded_value) OVER w / SUM(total_volume) OVER w AS vwap
+FROM sampled
+WINDOW w AS (PARTITION BY symbol ORDER BY timestamp);
 ```
 
 The `PARTITION BY symbol` ensures each symbol's VWAP is calculated independently.

documentation/query/functions/window-functions/overview.md

@@ -25,7 +25,15 @@ function_name(arguments) OVER (
 
 Some functions (`first_value`, `last_value`, `lag`, `lead`) also support `IGNORE NULLS` or `RESPECT NULLS` before the `OVER` keyword to control null handling.
 
-For complete syntax details including frame specifications and exclusion options, see [OVER Clause Syntax](syntax.md).
+When multiple window functions share the same definition, use the `WINDOW` clause to define it once:
+
+```sql
+SELECT avg(price) OVER w, sum(amount) OVER w
+FROM trades
+WINDOW w AS (PARTITION BY symbol ORDER BY timestamp)
+```
+
+For complete syntax details including frame specifications, exclusion options, and named windows, see [OVER Clause Syntax](syntax.md).
 
 :::info Window function arithmetic (9.3.1+)
 Arithmetic operations on window functions (e.g., `sum(...) OVER (...) / sum(...) OVER (...)`) are supported from version 9.3.1. Earlier versions require wrapping window functions in CTEs or subqueries.
@@ -257,15 +265,15 @@ WITH ohlc AS (
         sum(amount) AS volume
     FROM trades
     WHERE timestamp IN '2024-05-22' AND symbol = @symbol
-    SAMPLE BY 1m ALIGN TO CALENDAR
+    SAMPLE BY 1m
 )
 SELECT
     ts,
     symbol,
     open, high, low, close, volume,
-    sum((high + low + close) / 3 * volume) OVER (ORDER BY ts CUMULATIVE)
-        / sum(volume) OVER (ORDER BY ts CUMULATIVE) AS vwap
+    sum((high + low + close) / 3 * volume) OVER w / sum(volume) OVER w AS vwap
 FROM ohlc
+WINDOW w AS (ORDER BY ts CUMULATIVE)
 ORDER BY ts;
 ```
 
@@ -276,10 +284,11 @@ SELECT
     symbol,
     price,
     timestamp,
-    avg(price) OVER (PARTITION BY symbol) AS symbol_avg,
-    price - avg(price) OVER (PARTITION BY symbol) AS diff_from_avg
+    avg(price) OVER w AS symbol_avg,
+    price - avg(price) OVER w AS diff_from_avg
 FROM trades
-WHERE timestamp IN '[$today]';
+WHERE timestamp IN '[$today]'
+WINDOW w AS (PARTITION BY symbol);
 ```
 
 ### Rank within category
@@ -303,11 +312,11 @@ WHERE timestamp IN '[$today]';
 SELECT
     timestamp,
     price,
-    lag(price) OVER (ORDER BY timestamp) AS prev_price,
-    price - lag(price) OVER (ORDER BY timestamp) AS price_change
+    lag(price) OVER w AS prev_price,
+    price - lag(price) OVER w AS price_change
 FROM trades
-WHERE timestamp IN '[$today]'
-    AND symbol = 'BTC-USDT';
+WHERE timestamp IN '[$today]' AND symbol = 'BTC-USDT'
+WINDOW w AS (ORDER BY timestamp);
 ```
 
 ## Next steps

documentation/query/functions/window-functions/reference.md

@@ -912,24 +912,18 @@ WHERE timestamp IN '[$today]' AND symbol = 'GBPUSD';
 
 ### Trade frequency analysis
 
+This example uses a [named window](syntax.md#named-windows-window-clause) to avoid repeating the same window definition:
+
 ```questdb-sql title="Trades per minute by side" demo
 SELECT
     timestamp,
     symbol,
-    COUNT(*) OVER (
-        ORDER BY timestamp
-        RANGE BETWEEN 60000000 PRECEDING AND CURRENT ROW
-    ) AS updates_per_min,
-    COUNT(CASE WHEN side = 'buy' THEN 1 END) OVER (
-        ORDER BY timestamp
-        RANGE BETWEEN 60000000 PRECEDING AND CURRENT ROW
-    ) AS buys_per_minute,
-    COUNT(CASE WHEN side = 'sell' THEN 1 END) OVER (
-        ORDER BY timestamp
-        RANGE BETWEEN 60000000 PRECEDING AND CURRENT ROW
-    ) AS sells_per_minute
+    COUNT(*) OVER w AS updates_per_min,
+    COUNT(CASE WHEN side = 'buy' THEN 1 END) OVER w AS buys_per_minute,
+    COUNT(CASE WHEN side = 'sell' THEN 1 END) OVER w AS sells_per_minute
 FROM trades
-WHERE timestamp IN '[$today]' AND symbol = 'BTC-USDT';
+WHERE timestamp IN '[$today]' AND symbol = 'BTC-USDT'
+WINDOW w AS (ORDER BY timestamp RANGE BETWEEN 60000000 PRECEDING AND CURRENT ROW);
 ```
 
 ---