User-defined reducers

Juttle includes built-in reducers, but users can also define their own reducers by using the reducer keyword.

A custom reducer is composed of two required functions and two optional functions:

Function Description Required?
update This function is called once for each point in a stream. Yes
result This function is called at the end of a batch or stream in order to retrieve the final computed value from the reducer. Yes
expire This function is only needed if the reducer is to be used in a windowed reduce or put. No

In addition, a reducer can define local variables that are used in its computation.

Time windows with user-defined reducers

If a user-defined reducer is to be used with a moving time window (in a reduce, or put -over), then it may include an optional expire function.

An expire function is called once for each point as it leaves the window. It is considered the "opposite" of the update function, and it should undo what update did when the point entered the window.

It it not always possible to define an expire function (for example, there is no way to write expire for max or min functions). An expire function should be though of as an optimization -- without it, the computation is redone for all points in the current window each time result is called. The same result should be achieved whether or not expire is defined.

Example: this reducer counts the number of times a field has an odd value, and can be used with -over

reducer count_odd(fieldname) {
    var count = 0;

    function update() {
        if (*fieldname % 2 != 0) {
            count = count + 1;
    function expire() {
        if (*fieldname % 2 != 0) {
            count = count - 1;
    function result() {
        return count;

emit -from :-1d: -every :1m: -limit 100 | put value=count() 
| (
  reduce -every :10m: count_odd_last10m = count_odd(value);
  reduce -every :10m: -over :1h: count_odd_last1h = count_odd(value) 
| join
| view table

Example: let's define an exponentially weighted moving average (EWMA) reducer

reducer ewma(fieldname, alpha = 0.5) {
 var ma = 0;
 function update() {
    ma = ma * (1 - alpha) + * fieldname * alpha;
 function result() { 
    return ma; 
emit -limit 1 
| put cnt = Math.random() * 10 
| put ma_fast = ewma(cnt, 0.9), ma_slow = ewma(cnt, 0.1) 
| view table
  1. The first line declares the reducer name and indicates that the reducer takes two arguments: a field name (fieldname) and a weighting value (alpha). The alpha argument is optional because it is defined with a default value.

  2. The second line defines a variable (ma) that we'll use to store the running value of the moving average.

  3. The update() function updates the moving average each time it is invoked (for example, for each point passing through the reducer).

    See Field referencing for an explanation of why we used the * operator to reference *fieldname.

  4. The result() function simply returns that moving average.

  5. Then we have a flowgraph that emits a synthetic data point, sets the cnt field to a random number, invokes the ewma reducer twice, and outputs a point with two fields: ma_fast and ma_slow. Each is computed over the values of the cnt field, with a different alpha parameter.

    Note that ma_fast and ma_slow are computed independently, by separate instances of the reducer. A single reducer instance is created for each assignment expression, and each reducer instance has its own variables and state.

The alpha parameter is used by the reducer like a regular function argument. The fieldname parameter is used differently. Specifically, in the update() function, the fieldname parameter is de-referenced to obtain the value of the field whose name was passed in via the fieldname parameter. This allows reducers to be used generally over arbitrary field names, by having the user of a reducer specify which fields the reducer should use in its computation. In the above example, the field of interest is cnt, and is the first argument passed to the EWMA reducer.