Add a MovingFunction pipeline aggregation, deprecate MovingAvg agg (#29594)

This pipeline aggregation gives the user the ability to script functions that "move" across a window
of data, instead of single data points.  It is the scripted version of MovingAvg pipeline agg.

Through custom script contexts, we expose a number of convenience methods:

 - MovingFunctions.max()
 - MovingFunctions.min()
 - MovingFunctions.sum()
 - MovingFunctions.unweightedAvg()
 - MovingFunctions.linearWeightedAvg()
 - MovingFunctions.ewma()
 - MovingFunctions.holt()
 - MovingFunctions.holtWinters()
 - MovingFunctions.stdDev()

The user can also define any arbitrary logic via their own scripting, or combine with the above methods.

Author: polyfractal

docs/reference/aggregations/pipeline.asciidoc

@@ -72,6 +72,7 @@ POST /_search
 }
 --------------------------------------------------
 // CONSOLE
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 <1> The metric is called `"the_sum"`
 <2> The `buckets_path` refers to the metric via a relative path `"the_sum"`
 
@@ -136,6 +137,7 @@ POST /_search
 }
 --------------------------------------------------
 // CONSOLE
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 <1> By using `_count` instead of a metric name, we can calculate the moving average of document counts in the histogram
 
 The `buckets_path` can also use `"_bucket_count"` and path to a multi-bucket aggregation to use the number of buckets
@@ -231,6 +233,7 @@ include::pipeline/stats-bucket-aggregation.asciidoc[]
 include::pipeline/extended-stats-bucket-aggregation.asciidoc[]
 include::pipeline/percentiles-bucket-aggregation.asciidoc[]
 include::pipeline/movavg-aggregation.asciidoc[]
+include::pipeline/movfn-aggregation.asciidoc[]
 include::pipeline/cumulative-sum-aggregation.asciidoc[]
 include::pipeline/bucket-script-aggregation.asciidoc[]
 include::pipeline/bucket-selector-aggregation.asciidoc[]

docs/reference/aggregations/pipeline/movavg-aggregation.asciidoc

@@ -1,6 +1,10 @@
 [[search-aggregations-pipeline-movavg-aggregation]]
 === Moving Average Aggregation
 
+deprecated[6.4.0, The Moving Average aggregation has been deprecated in favor of the more general
+<<search-aggregations-pipeline-movfn-aggregation,Moving Function Aggregation>>.  The new Moving Function aggregation provides
+all the same functionality as the Moving Average aggregation, but also provides more flexibility.]
+
 Given an ordered series of data, the Moving Average aggregation will slide a window across the data and emit the average
 value of that window.  For example, given the data `[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]`, we can calculate a simple moving
 average with windows size of `5` as follows:
@@ -74,6 +78,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 <1> A `date_histogram` named "my_date_histo" is constructed on the "timestamp" field, with one-day intervals
 <2> A `sum` metric is used to calculate the sum of a field.  This could be any metric (sum, min, max, etc)
@@ -180,6 +185,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 A `simple` model has no special settings to configure
 
@@ -233,6 +239,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 A `linear` model has no special settings to configure
 
@@ -295,7 +302,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
-
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 [[single_0.2alpha]]
 .EWMA with window of size 10, alpha = 0.2
@@ -355,6 +362,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 In practice, the `alpha` value behaves very similarly in `holt` as `ewma`: small values produce more smoothing
 and more lag, while larger values produce closer tracking and less lag.  The value of `beta` is often difficult
@@ -446,7 +454,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
-
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 [[holt_winters_add]]
 .Holt-Winters moving average with window of size 120, alpha = 0.5, beta = 0.7, gamma = 0.3, period = 30
@@ -508,6 +516,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 ==== Prediction
 
@@ -550,6 +559,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 The `simple`, `linear` and `ewma` models all produce "flat" predictions: they essentially converge on the mean
 of the last value in the series, producing a flat:
@@ -631,6 +641,7 @@ POST /_search
 --------------------------------------------------
 // CONSOLE
 // TEST[setup:sales]
+// TEST[warning:The moving_avg aggregation has been deprecated in favor of the moving_fn aggregation.]
 
 <1> Minimization is enabled with the `minimize` parameter