lagInFrame

Returns a value evaluated at the row that is at a specified physical offset row before the current row within the ordered frame.

Danger

lagInFrame behavior differs from the standard SQL lag window function. Clickhouse window function lagInFrame respects the window frame. To get behavior identical to the lag, use ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING.

Syntax

lagInFrame(x[, offset[, default]])
  OVER ([[PARTITION BY grouping_column] [ORDER BY sorting_column]
        [ROWS or RANGE expression_to_bound_rows_withing_the_group]] | [window_name])
FROM table_name
WINDOW window_name as ([[PARTITION BY grouping_column] [ORDER BY sorting_column])

For more detail on window function syntax see: Window Functions - Syntax.

Parameters

• x — Column name.
• offset — Offset to apply. (U)Int*. (Optional - 1 by default).
• default — Value to return if calculated row exceeds the boundaries of the window frame. (Optional - default value of column type when omitted).

Returned value

• Value evaluated at the row that is at a specified physical offset before the current row within the ordered frame.

Example

This example looks at historical data for a specific stock and uses the lagInFrame function to calculate a day-to-day delta and percentage change in the closing price of the stock.

Query:

CREATE TABLE stock_prices
(
    `date`   Date,
    `open`   Float32, -- opening price
    `high`   Float32, -- daily high
    `low`    Float32, -- daily low
    `close`  Float32, -- closing price
    `volume` UInt32   -- trade volume
)
Engine = Memory;

INSERT INTO stock_prices FORMAT Values
    ('2024-06-03', 113.62, 115.00, 112.00, 115.00, 438392000),
    ('2024-06-04', 115.72, 116.60, 114.04, 116.44, 403324000),
    ('2024-06-05', 118.37, 122.45, 117.47, 122.44, 528402000),
    ('2024-06-06', 124.05, 125.59, 118.32, 121.00, 664696000),
    ('2024-06-07', 119.77, 121.69, 118.02, 120.89, 412386000);

SELECT
    date,
    close,
    lagInFrame(close, 1, close) OVER (ORDER BY date ASC
       ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
     ) AS previous_day_close,
    COALESCE(ROUND(close - previous_day_close, 2)) AS delta,
    COALESCE(ROUND((delta / previous_day_close) * 100, 2)) AS percent_change
FROM stock_prices
ORDER BY date DESC

Result:

   ┌───────date─┬──close─┬─previous_day_close─┬─delta─┬─percent_change─┐
1. │ 2024-06-07 │ 120.89 │                121 │ -0.11 │          -0.09 │
2. │ 2024-06-06 │    121 │             122.44 │ -1.44 │          -1.18 │
3. │ 2024-06-05 │ 122.44 │             116.44 │     6 │           5.15 │
4. │ 2024-06-04 │ 116.44 │                115 │  1.44 │           1.25 │
5. │ 2024-06-03 │    115 │                115 │     0 │              0 │
   └────────────┴────────┴────────────────────┴───────┴────────────────┘