# User defined analytics

***

This example computes the exponential moving average using a Joule OOTB function packaged as a jar using the Joule SDK. 

## Use case configuration

*File:* app-ema-analytics-and-influx.env

```bash
SOURCEFILE=conf/sources/stockQuoteStream.yaml
ENGINEFILE=conf/usecases/slidingEventWindowEMAAnalytics.yaml
PUBLISHFILE=conf/publishers/influxdbStandardAnalytics.yaml
```

## Pipeline configuration <a href="#processor-configuration" id="processor-configuration"></a>

This pipeline will compute a sliding window function on a single event type based on the symbol `CVCO`

{% code overflow="wrap" %}

```
processing unit:
  pipeline:
    - filter:
      expression: "symbol == 'CVCO'"
    - sliding window analytics:
        function: com.fractalworks.streams.processors.analytics.functions.ExponentialMovingAverage
        window size: 5
        fields: [ ask, bid ]
        parameters:
          emaFactor: 0.33333
```

{% endcode %}

## Function Implementation

This function is interesting as it uses the previous ema value to compute the next value, Joule manages this process on behalf of the developer.

{% code overflow="wrap" %}

```java
public class ExponentialMovingAverage implements AnalyticsFunction<Double> {

    public final static String EMA_FACTOR = "emaFactor";
    double emaFactor = 0.333;

    public ExponentialMovingAverage() {
    }

    @Override
    public void setParameters(Properties parameters) {
        if (parameters != null && parameters.containsKey(EMA_FACTOR)) {
            emaFactor = Double.parseDouble(parameters.get(EMA_FACTOR).toString());
        }
    }

    @Override
    public String getVariablePostFixID() {
        return "EMA";
    }

    @Override
    public Double compute(Number[] values, Number previousValue) {

        if (previousValue != null && Double.isNaN(previousValue.doubleValue())) {
            previousValue = values[values.length - 1];
        }

        for (Number d : values) {
            previousValue = (d.doubleValue() * emaFactor) + (previousValue.doubleValue() * (1 - emaFactor));
        }
        return previousValue.doubleValue();
    }
}

```

{% endcode %}


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