By letting the fetch phase understand the nested docs structure we can serve nested docs as hits.
The `top_hits` aggregation can because of this commit be placed in a `nested` or `reverse_nested` aggregation.
Closes#7164
This change removes the script_type parameter form the Scripted Metric Aggregation and adds support for _file and _id suffixes to the init_script, map_script, combine_script and reduce_script parameters to make defining the source of the script consistent with the other APIs which use the ScriptService
Changes the name of the field in the scripted metrics aggregation from 'aggregation' to 'value' to be more in line with the other metrics aggregations like 'avg'
Percentile Rank Aggregation is the reverse of the Percetiles aggregation. It determines the percentile rank (the proportion of values less than a given value) of the provided array of values.
Closes#6386
The GeoBounds Aggregation is a new single bucket aggregation which outputs the coordinates of a bounding box containing all the points from all the documents passed to the aggregation as well as the doc count. Geobound Aggregation also use a wrap_logitude parameter which specifies whether the resulting bounding box is permitted to overlap the international date line. This option defaults to true.
This aggregation introduces the idea of MetricsAggregation which do not return double values and cannot be used for sorting. The existing MetricsAggregation has been renamed to NumericMetricsAggregation and is a subclass of MetricsAggregation. MetricsAggregations do not store doc counts and do not support child aggregations.
Closes#5634
Our improvements to t-digest have been pushed upstream and t-digest also got
some additional nice improvements around memory usage and speedups of quantile
estimation. So it makes sense to use it as a dependency now.
This also allows to remove the test dependency on Apache Mahout.
Close#6142
This aggregation computes unique term counts using the hyperloglog++ algorithm
which uses linear counting to estimate low cardinalities and hyperloglog on
higher cardinalities.
Since this algorithm works on hashes, it is useful for high-cardinality fields
to store the hash of values directly in the index, which is the purpose of
the new `murmur3` field type. This is less necessary on low-cardinality
string fields because the aggregator is smart enough to only compute the hash
once per unique value per segment thanks to ordinals, or on numeric fields
since hashing them is very fast.
Close#5426
* Make it clearer that `aggs` is an allowed synomym
for the `aggregations` key
* Fix broken example in for datehistogram, `1.5M` is
not an allowed interval
* Make use of colon before examples consistent
* Fix typos