DOCAPI-7415: Docs for the -Resample aggregate function combinator.

docs/en/query_language/agg_functions/combinators.md

@@ -44,5 +44,71 @@ Merges the intermediate aggregation states in the same way as the -Merge combina
 
 Converts an aggregate function for tables into an aggregate function for arrays that aggregates the corresponding array items and returns an array of results. For example, `sumForEach` for the arrays `[1, 2]`, `[3, 4, 5]`and`[6, 7]`returns the result `[10, 13, 5]` after adding together the corresponding array items.
 
+## -Resample
+
+Allows to divide data by groups, and then separately aggregates the data in those groups. Groups are created by splitting the values of one of the columns into intervals.
+
+```
+<aggFunction>Resample(start, end, step)(<aggFunction_params>, resampling_key)
+```
+
+**Parameters**
+
+- `start` — Starting value of the whole required interval for the values of `resampling_key`. 
+- `stop` — Ending value of the whole required interval for the values of `resampling_key`. The whole interval doesn't include the `stop` value `[start, stop)`.
+- `step` — Step for separating the whole interval by subintervals. The `aggFunction` is executed over each of those subintervals independently.
+- `resampling_key` — Column, which values are used for separating data by intervals.
+- `aggFunction_params` — Parameters of `aggFunction`.
+
+
+**Returned values**
+
+- Array of `aggFunction` results for each of subintervals.
+
+**Example**
+
+Consider the `people` table with the following data:
+
+```text
+┌─name───┬─age─┬─wage─┐
+│ John   │  16 │   10 │
+│ Alice  │  30 │   15 │
+│ Mary   │  35 │    8 │
+│ Evelyn │  48 │ 11.5 │
+│ David  │  62 │  9.9 │
+│ Brian  │  60 │   16 │
+└────────┴─────┴──────┘
+```
+
+Let's get the names of the persons which age lies in the intervals of `[30,60)` and `[60,75)`. As we use integer representation of age, then there are ages of `[30, 59]` and `[60,74]`.
+
+For aggregating names into the array, we use the aggregate function [groupArray](reference.md#agg_function-grouparray). It takes a single argument. For our case, it is the `name` column. The `groupArrayResample` function should use the `age` column to aggregate names by age. To define required intervals, we pass the `(30, 75, 30)` arguments into the `groupArrayResample` function.
+
+```sql
+SELECT groupArrayResample(30, 75, 30)(name, age) from people
+```
+```text
+┌─groupArrayResample(30, 75, 30)(name, age)─────┐
+│ [['Alice','Mary','Evelyn'],['David','Brian']] │
+└───────────────────────────────────────────────┘
+```
+
+Consider the results.
+
+`Jonh` is out of the sample because he is too young. Other people are distributed according to the specified age intervals.
+
+Now, let's count the total number of people and their average wage in the specified age intervals.
+
+```sql
+SELECT
+    countResample(30, 75, 30)(name, age) AS amount,
+    avgResample(30, 75, 30)(wage, age) AS avg_wage
+FROM people
+```
+```text
+┌─amount─┬─avg_wage──────────────────┐
+│ [3,2]  │ [11.5,12.949999809265137] │
+└────────┴───────────────────────────┘
+```
 
 [Original article](https://clickhouse.yandex/docs/en/query_language/agg_functions/combinators/) <!--hide-->

docs/en/query_language/agg_functions/reference.md

@@ -650,7 +650,7 @@ The function takes a variable number of parameters. Parameters can be `Tuple`, `
 - [uniqHLL12](#agg_function-uniqhll12)
 
 
-## groupArray(x), groupArray(max_size)(x)
+## groupArray(x), groupArray(max_size)(x) {#agg_function-grouparray}
 
 Creates an array of argument values.
 Values can be added to the array in any (indeterminate) order.