Open source

## Functions Variables

There are some built-in template variables available for using in functions:

• `\$__range_ms` - panel time range in ms
• `\$__range_s` - panel time range in seconds
• `\$__range` - panel time range, string representation (`30s`, `1m`, `1h`)
• `\$__range_series` - invoke function over all series values

Examples:

sh
``````groupBy(\$__range, avg)
percentile(\$__range_series, 95) - 95th percentile over all values``````

## Transform

### groupBy

sh
``groupBy(interval, function)``

Takes each timeseries and consolidate its points fallen in the given interval into one point using function, which can be one of: avg, min, max, median.

Examples:

sh
``````groupBy(10m, avg)
groupBy(1h, median)``````

### scale

sh
``scale(factor)``

Takes timeseries and multiplies each point by the given factor.

Examples:

sh
``````scale(100)
scale(0.01)``````

### delta

sh
``delta()``

Converts absolute values to delta. This function just calculate difference between values. For the per-second calculation use `rate()`.

### rate

sh
``rate()``

Calculates the per-second rate of increase of the time series. Resistant to counter reset. Suitable for converting of growing counters into the per-second rate.

### movingAverage

sh
``movingAverage(windowSize)``

Graphs the moving average of a metric over a fixed number of past points, specified by `windowSize` param.

Examples:

sh
``````movingAverage(60)
calculates moving average over 60 points (if metric has 1 second resolution it matches 1 minute window)``````

### exponentialMovingAverage

sh
``exponentialMovingAverage(windowSize)``

Takes a series of values and a window size and produces an exponential moving average utilizing the following formula:
`ema(current) = constant * (Current Value) + (1 - constant) * ema(previous)`

The Constant is calculated as:
`constant = 2 / (windowSize + 1)`

If windowSize < 1 (0.1, for instance), Constant wouldn’t be calculated and will be taken directly from windowSize (Constant = windowSize).

It’s a bit tricky to graph EMA from the first point of series (not from Nth = windowSize). In order to do it, plugin should fetch previous N points first and calculate simple moving average for it. To avoid it, plugin uses this hack: assume, previous N points have the same average values as first N (windowSize). So you should keep this fact in mind and don’t rely on first N points interval.

Examples:

sh
``````movingAverage(60)
calculates moving average over 60 points (if metric has 1 second resolution it matches 1 minute window)``````

### percentile

sh
``percentile(interval, N)``

Takes a series of values and a window size and consolidate all its points fallen in the given interval into one point by Nth percentile.

Examples:

sh
``````percentile(1h, 99)
percentile(\$__range_series, 95) - 95th percentile over all series values``````

### removeAboveValue

sh
``removeAboveValue(N)``

Replaces series values with `null` if value > N

Examples:

sh
``removeAboveValue(1)``

### removeBelowValue

sh
``removeBelowValue(N)``

Replaces series values with `null` if value < N

### transformNull

sh
``transformNull(N)``

Replaces `null` values with N

## Aggregate

### aggregateBy

sh
``aggregateBy(interval, function)``

Takes all timeseries and consolidate all its points fallen in the given interval into one point using function, which can be one of: avg, min, max, median.

Examples:

sh
``````aggregateBy(10m, avg)
aggregateBy(1h, median)``````

### sumSeries

sh
``sumSeries()``

This will add metrics together and return the sum at each datapoint. This method required interpolation of each timeseries so it may cause high CPU load. Try to combine it with groupBy() function to reduce load.

### percentileAgg

sh
``percentileAgg(interval, N)``

Takes all timeseries and consolidate all its points fallen in the given interval into one point by Nth percentile.

Examples:

sh
``````percentileAgg(1h, 99)
percentileAgg(\$__range_series, 95) - 95th percentile over all values``````

### average

sh
``average(interval)``

Deprecated, use `aggregateBy(interval, avg)` instead.

### min

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``min(interval)``

Deprecated, use `aggregateBy(interval, min)` instead.

### max

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``max(interval)``

Deprecated, use `aggregateBy(interval, max)` instead.

## Filter

### top

sh
``top(N, value)``

Returns top N series, sorted by value, which can be one of: avg, min, max, median.

Examples:

sh
``````top(10, avg)
top(5, max)``````

### bottom

sh
``bottom(N, value)``

Returns bottom N series, sorted by value, which can be one of: avg, min, max, median.

Examples:

sh
``bottom(5, avg)``

### trendValue

sh
``trendValue(valueType)``

Specifying type of trend value returned by Zabbix when trends are used (avg, min or max).

## Time

### timeShift

sh
``timeShift(interval)``

Draws the selected metrics shifted in time. If no sign is given, a minus sign ( - ) is implied which will shift the metric back in time. If a plus sign ( + ) is given, the metric will be shifted forward in time. Examples:

sh
``````timeShift(24h)  - shift metric back in 24h hours
timeShift(-24h) - the same result as for timeShift(24h)
timeShift(+1d)  - shift metric forward in 1 day``````

## Alias

Following template variables available for using in `setAlias()` and `replaceAlias()` functions:

• `\$__zbx_item`, `\$__zbx_item_name` - item name
• `\$__zbx_item_key` - item key
• `\$__zbx_host_name` - visible name of the host
• `\$__zbx_host` - technical name of the host

Examples:

sh
``````setAlias(\$__zbx_host_name: \$__zbx_item) -> backend01: CPU user time
setAlias(Item key: \$__zbx_item_key) -> Item key: system.cpu.load[percpu,avg1]
setAlias(\$__zbx_host_name) -> backend01``````

### setAlias

sh
``setAlias(alias)``

Returns given alias instead of the metric name.

Examples:

sh
``setAlias(load)``

### setAliasByRegex

sh
``setAliasByRegex(regex)``

Returns part of the metric name matched by regex.

Examples:

sh
``setAlias(Zabbix busy [a-zA-Z]+)``

### replaceAlias

sh
``replaceAlias(pattern, newAlias)``

Replace metric name using pattern. Pattern is regex or regular string. If regex is used, following special replacement patterns are supported:

PatternInserts
\$\$Inserts a “\$”.
\$&Inserts the matched substring.
\$`Inserts the portion of the string that precedes the matched substring.
\$'Inserts the portion of the string that follows the matched substring.
\$nWhere n is a non-negative integer less than 100, inserts the nth parenthesized submatch string, provided the first argument was a RegExp object.

For more details see String.prototype.replace() function.

NOTE: Other transforms in Grafana Dashboard, like “Join by label” will overwrite the alias functions. This will happen because the Grafana Dashboard transforms will be applied on the raw data returned by a query. If such issues arise, you can always use other Dashboard transforms, like:

Examples:

sh
``````CPU system time
replaceAlias(/CPU (.*) time/, \$1) -> system

backend01: CPU system time
replaceAlias(/CPU (.*) time/, \$1) -> backend01: system

backend01: CPU system time
replaceAlias(/.*CPU (.*) time/, \$1) -> system

backend01: CPU system time
replaceAlias(/(.*): CPU (.*) time/, \$1 - \$2) -> backend01 - system``````

## Special

### consolidateBy

sh
``consolidateBy(consolidationFunc)``

When a graph is drawn where width of the graph size in pixels is smaller than the number of datapoints to be graphed, plugin consolidates the values to prevent line overlap. The consolidateBy() function changes the consolidation function from the default of average to one of `sum`, `min`, `max` or `count`.

Valid function names are `sum`, `avg`, `min`, `max` and `count`.