---
title: RollingAvg
---

`RollingAvg` calculates a window-based rolling average in an [`updateBy`](./updateBy.md) table operation. The rolling average can be calculated using forward and/or backward windows.

$SMA = \frac{\sum_{1}^{n}x_{i}}{n}$

Where:

- $n$ is the number window size in ticks.
- $x_{i}$ is the current value.

For a tick-based (row-based) SMA, `n` is the window size, determined by [`fwdTicks`](#parameters) and [`revTicks`](#parameters).

For a time-based SMA, `n` is the number of observations in the window, determined by [`fwdTime`](#parameters) and [`revTime`](#parameters).

## Syntax

```
RollingAvg(revTicks, fwdTicks, pairs)
RollingAvg(revTicks, pairs)
RollingAvg(timestampCol, revTime, fwdTime, pairs)
RollingAvg(timestampCol, revTime, pairs)
RollingAvg(timestampCol, revDuration, pairs)
RollingAvg(timestampCol, revDuration, fwdDuration, pairs)
```

## Parameters

<ParamTable>
<Param name="revTicks" type="long">

The look-behind window size in ticks (rows). If positive, it defines the maximum number of rows _before_ the current row that will be used. If negative, it defines the minimum number of rows _after_ the current row that will be used.

</Param>
<Param name="fwdTicks" type="long">

The look-forward window size in ticks (rows). If positive, it defines the maximum number of rows _after_ the current row that will be used. If negative, it defines the minimum number of rows _before_ the current row that will be used.

</Param>
<Param name="pairs" type="String...">

The input/output column name pairs.

</Param>
<Param name="timestampCol" type="String">

The name of the timestamp column.

</Param>
<Param name="revDuration" type="Duration">

The look-behind window size in Duration.

</Param>
<Param name="fwdDuration" type="Duration">

The look-forward window size in Duration.

</Param>
<Param name="revTime" type="long">

The look-behind window size in nanoseconds.

</Param>
<Param name="fwdTime" type="long">

The look-forward window size in nanoseconds.

</Param>
</ParamTable>

## Returns

An [`UpdateByOperation`](./updateBy.md#parameters) to be used in an [`updateBy`](./updateBy.md) table operation.

## Examples

The following example performs an [`updateBy`](./updateBy.md) on the `source` table using four row-based `RollingAvg` operations. Each operation uses different `revTicks` and `fwdTicks` values to show how they affect the output. Note that the first operation only uses `revTicks`.

```groovy order=source,result
rng = new Random()

source = emptyTable(10).update("X = rng.nextInt(25)")

opRollAvg = RollingAvg(3, "RollingAverage = X")
opPrior = RollingAvg(3, -1, "WindowPrior = X")
opPosterior = RollingAvg(-1, 3, "WindowPosterior = X")
opMiddle = RollingAvg(1, 1, "WindowMiddle = X")

result = source.updateBy([opRollAvg, opPrior, opPosterior, opMiddle])
```

## Related documentation

- [How to create an empty table](../../../how-to-guides/new-and-empty-table.md#emptytable)
- [How to use `updateBy`](../../../how-to-guides/rolling-aggregations.md)
- [ternary conditional operator](../../../how-to-guides/ternary-if-how-to.md)
- [`update`](../select/update.md)
- [`updateBy`](./updateBy.md)
- [Javadoc](https://deephaven.io/core/javadoc/io/deephaven/api/updateby/UpdateByOperation.html#RollingAvg(long,long,java.lang.String...))