Add rate aggregation

docs/reference/aggregations/metrics.asciidoc

@@ -51,6 +51,7 @@ include::metrics/valuecount-aggregation.asciidoc[]
 
 include::metrics/t-test-aggregation.asciidoc[]
 
+include::metrics/rate-aggregation.asciidoc[]
 
 
 

docs/reference/aggregations/metrics/rate-aggregation.asciidoc

@@ -0,0 +1,257 @@
+[role="xpack"]
+[testenv="basic"]
+[[search-aggregations-metrics-rate-aggregation]]
+=== Rate Aggregation
+
+A `rate` metrics aggregation can be used only inside a `date_histogram` and calculates a rate of documents or a field in each
+`date_histogram` bucket.
+
+==== Syntax
+
+A `rate` aggregation looks like this in isolation:
+
+[source,js]
+--------------------------------------------------
+{
+  "rate": {
+    "unit": "month",
+    "field": "requests"
+  }
+}
+--------------------------------------------------
+// NOTCONSOLE
+
+The following request will group all sales records into monthly bucket and than convert the number of sales transaction in each bucket
+into per annual sales rate.
+
+[source,console]
+--------------------------------------------------
+GET sales/_search
+{
+  "size": 0,
+  "aggs": {
+    "by_date": {
+      "date_histogram": {
+        "field": "date",
+        "calendar_interval": "month"  <1>
+      },
+      "aggs": {
+        "my_rate": {
+          "rate": {
+            "unit": "year"  <2>
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// TEST[setup:sales]
+<1> Histogram is grouped by month.
+<2> But the rate is converted into annual rate.
+
+The response will return the annual rate of transaction in each bucket. Since there are 12 months per year, the annual rate will
+be automatically calculated by multiplying monthly rate by 12.
+
+[source,console-result]
+--------------------------------------------------
+{
+  ...
+  "aggregations" : {
+    "by_date" : {
+      "buckets" : [
+        {
+          "key_as_string" : "2015/01/01 00:00:00",
+          "key" : 1420070400000,
+          "doc_count" : 3,
+          "my_rate" : {
+            "value" : 36.0
+          }
+        },
+        {
+          "key_as_string" : "2015/02/01 00:00:00",
+          "key" : 1422748800000,
+          "doc_count" : 2,
+          "my_rate" : {
+            "value" : 24.0
+          }
+        },
+        {
+          "key_as_string" : "2015/03/01 00:00:00",
+          "key" : 1425168000000,
+          "doc_count" : 2,
+          "my_rate" : {
+            "value" : 24.0
+          }
+        }
+      ]
+    }
+  }
+}
+--------------------------------------------------
+// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
+
+Instead of counting the number of documents, it is also possible to calculate a sum of all values of the fields in the documents in each
+bucket. The following request will group all sales records into monthly bucket and than calculate the total monthly sales and convert them
+into average daily sales.
+
+[source,console]
+--------------------------------------------------
+GET sales/_search
+{
+  "size": 0,
+  "aggs": {
+    "by_date": {
+      "date_histogram": {
+        "field": "date",
+        "calendar_interval": "month"  <1>
+      },
+      "aggs": {
+        "avg_price": {
+          "rate": {
+            "field": "price", <2>
+            "unit": "day"  <3>
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// TEST[setup:sales]
+<1> Histogram is grouped by month.
+<2> Calculate sum of all sale prices
+<3> Convert to average daily sales
+
+The response will contain the average daily sale prices for each month.
+
+[source,console-result]
+--------------------------------------------------
+{
+  ...
+  "aggregations" : {
+    "by_date" : {
+      "buckets" : [
+        {
+          "key_as_string" : "2015/01/01 00:00:00",
+          "key" : 1420070400000,
+          "doc_count" : 3,
+          "avg_price" : {
+            "value" : 17.741935483870968
+          }
+        },
+        {
+          "key_as_string" : "2015/02/01 00:00:00",
+          "key" : 1422748800000,
+          "doc_count" : 2,
+          "avg_price" : {
+            "value" : 2.142857142857143
+          }
+        },
+        {
+          "key_as_string" : "2015/03/01 00:00:00",
+          "key" : 1425168000000,
+          "doc_count" : 2,
+          "avg_price" : {
+            "value" : 12.096774193548388
+          }
+        }
+      ]
+    }
+  }
+}
+--------------------------------------------------
+// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
+
+
+==== Relationship between bucket sizes and rate
+
+The `rate` aggregation supports all rate that can be used <<calendar_intervals,calendar_intervals parameter>> of `date_histogram`
+aggregation. The specified rate should compatible with the `date_histogram` aggregation interval, i.e. it should be possible to
+convert the bucket size into the rate. By default the interval of the `date_histogram` is used.
+
+`"rate": "second"`:: compatible with all intervals
+`"rate": "minute"`:: compatible with all intervals
+`"rate": "hour"`:: compatible with all intervals
+`"rate": "day"`:: compatible with all intervals
+`"rate": "week"`:: compatible with all intervals
+`"rate": "month"`:: compatible with only with `month`, `quarter` and `year` calendar intervals
+`"rate": "quarter"`:: compatible with only with `month`, `quarter` and `year` calendar intervals
+`"rate": "year"`:: compatible with only with `month`, `quarter` and `year` calendar intervals
+
+==== Script
+
+The `rate` aggregation also supports scripting. For example, if we need to adjust out prices before calculating rates, we could use
+a script to recalculate them on-the-fly:
+
+[source,console]
+--------------------------------------------------
+GET sales/_search
+{
+  "size": 0,
+  "aggs": {
+    "by_date": {
+      "date_histogram": {
+        "field": "date",
+        "calendar_interval": "month"
+      },
+      "aggs": {
+        "avg_price": {
+          "rate": {
+            "script": {  <1>
+              "lang": "painless",
+              "source": "doc['price'].value * params.adjustment",
+              "params": {
+                "adjustment": 0.9  <2>
+              }
+            }
+          }
+        }
+      }
+    }
+  }
+}
+--------------------------------------------------
+// TEST[setup:sales]
+
+<1> The `field` parameter is replaced with a `script` parameter, which uses the
+script to generate values which percentiles are calculated on.
+<2> Scripting supports parameterized input just like any other script.
+
+[source,console-result]
+--------------------------------------------------
+{
+  ...
+  "aggregations" : {
+    "by_date" : {
+      "buckets" : [
+        {
+          "key_as_string" : "2015/01/01 00:00:00",
+          "key" : 1420070400000,
+          "doc_count" : 3,
+          "avg_price" : {
+            "value" : 495.0
+          }
+        },
+        {
+          "key_as_string" : "2015/02/01 00:00:00",
+          "key" : 1422748800000,
+          "doc_count" : 2,
+          "avg_price" : {
+            "value" : 54.0
+          }
+        },
+        {
+          "key_as_string" : "2015/03/01 00:00:00",
+          "key" : 1425168000000,
+          "doc_count" : 2,
+          "avg_price" : {
+            "value" : 337.5
+          }
+        }
+      ]
+    }
+  }
+}
+--------------------------------------------------
+// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]

docs/reference/rest-api/usage.asciidoc

@@ -275,6 +275,7 @@ GET /_xpack/usage
       "normalize_usage" : 0,
       "cumulative_cardinality_usage" : 0,
       "t_test_usage" : 0,
+      "rate_usage" : 0,
       "string_stats_usage" : 0,
       "moving_percentiles_usage" : 0
     }