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'
The terms aggregation can now support sorting on multiple criteria by replacing the sort object with an array or sort object whose order signifies the priority of the sort. The existing syntax for sorting on a single criteria also still works.
Contributes to #6917
Replaces #7588
The terms aggregation can now support sorting on multiple criteria by replacing the sort object with an array or sort object whose order signifies the priority of the sort. The existing syntax for sorting on a single criteria also still works.
Contributes to #6917
The current implementation of 'date_histogram' does not understand
the `factor` parameter. Since the docs shouldn't raise false hopes,
I removed the section.
Closes#7277
A multi-bucket aggregation where multiple filters can be defined (each filter defines a bucket). The buckets will collect all the documents that match their associated filter.
This aggregation can be very useful when one wants to compare analytics between different criterias. It can also be accomplished using multiple definitions of the single filter aggregation, but here, the user will only need to define the sub-aggregations only once.
Closes#6118
This is only applicable when the order is set to _count. The upper bound of the error in the doc count is calculated by summing the doc count of the last term on each shard which did not return the term. The implementation calculates the error by summing the doc count for the last term on each shard for which the term IS returned and then subtracts this value from the sum of the doc counts for the last term from ALL shards.
Closes#6696
This commit adds the infrastructure to allow pluging in different
measures for computing the significance of a term.
Significance measures can be provided externally by overriding
- SignificanceHeuristic
- SignificanceHeuristicBuilder
- SignificanceHeuristicParser
closes#6561
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
A new "breadth_first" results collection mode allows upper branches of aggregation tree to be calculated and then pruned
to a smaller selection before advancing into executing collection on child branches.
Closes#6128
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
Significant terms internally maintain a priority queue per shard with a size potentially
lower than the number of terms. This queue uses the score as criterion to determine if
a bucket is kept or not. If many terms with low subsetDF score very high
but the `min_doc_count` is set high, this might result in no terms being
returned because the pq is filled with low frequent terms which are all sorted
out in the end.
This can be avoided by increasing the `shard_size` parameter to a higher value.
However, it is not immediately clear to which value this parameter must be set
because we can not know how many terms with low frequency are scored higher that
the high frequent terms that we are actually interested in.
On the other hand, if there is no routing of docs to shards involved, we can maybe
assume that the documents of classes and also the terms therein are distributed evenly
across shards. In that case it might be easier to not add documents to the pq that have
subsetDF <= `shard_min_doc_count` which can be set to something like
`min_doc_count`/number of shards because we would assume that even when summing up
the subsetDF across shards `min_doc_count` will not be reached.
closes#5998closes#6041
Colin Goodheart-Smithe
Jordan Snodgrass
markharwood
Lee Hinman
smayzak
David Pilato
Clinton Gormley
shrinidhichaudhari
Adrien Grand
londocr
Martijn van Groningen
Konrad Feldmeier
Britta Weber
uboness
Simon Willnauer
Florian Hopf
Andrii Gakhov
Chris
Rashid Khan
gabriel-tessier