This commit adds a new metric aggregator for computing the geo_centroid over a set of geo_point fields. This can be combined with other aggregators (e.g., geohash_grid, significant_terms) for computing the geospatial centroid based on the document sets from other aggregation results.
This pipeline will calculate percentiles over a set of sibling buckets. This is an exact
implementation, meaning it needs to cache a copy of the series in memory and sort it to determine
the percentiles.
This comes with a few limitations: to prevent serializing data around, only the requested percentiles
are calculated (unlike the TDigest version, which allows the java API to ask for any percentile).
It also needs to store the data in-memory, resulting in some overhead if the requested series is
very large.
This move the `murmur3` field to the `mapper-murmur3` plugin and fixes its
defaults so that values will not be indexed by default, as the only purpose
of this field is to speed up `cardinality` aggregations on high-cardinality
string fields, which only requires doc values.
I also removed the `rehash` option from the `cardinality` aggregation as it
doesn't bring much value (rehashing is cheap) and allowed to remove the
coupling between the `cardinality` aggregation and the `murmur3` field.
Close#12874
HDRHistogram has been added as an option in the percentiles and percentile_ranks aggregation. It has one option `number_significant_digits` which controls the accuracy and memory size for the algorithm
Closes#8324
This pipeline aggregation runs a script on each bucket in the parent aggregation to determine whether the bucket is kept in the final aggregation tree. If the script returns true the bucket is retained, if it returns false the bucket is dropped
The filters aggregation now has an option to add an 'other' bucket which will, when turned on, contain all documents which do not match any of the defined filters. There is also an option to change the name of the 'other' bucket from the default of '_other_'
Closes#11289
In order to be more consistent with what they do, the query cache has been
renamed to request cache and the filter cache has been renamed to query
cache.
A known issue is that package/logger names do no longer match settings names,
please speak up if you think this is an issue.
Here are the settings for which I kept backward compatibility. Note that they
are a bit different from what was discussed on #11569 but putting `cache` before
the name of what is cached has the benefit of making these settings consistent
with the fielddata cache whose size is configured by
`indices.fielddata.cache.size`:
* index.cache.query.enable -> index.requests.cache.enable
* indices.cache.query.size -> indices.requests.cache.size
* indices.cache.filter.size -> indices.queries.cache.size
Close#11569
This adds a new pipeline aggregation, the cumulative sum aggregation. This is a parent aggregation which must be specified as a sub-aggregation to a histogram or date_histogram aggregation. It will add a new aggregation to each bucket containing the sum of a specified metrics over this and all previous buckets.
Replace the previous example which leveraged a range filter, which causes unnecessary confusion about when to use a range filter to create a single bucket or a range aggregation with exactly one member in ranges.
Closes#11704
This change unifies the way scripts and templates are specified for all instances in the codebase. It builds on the Script class added previously and adds request building and parsing support as well as the ability to transfer script objects between nodes. It also adds a Template class which aims to provide the same functionality for template APIs
Closes#11091
Most aggregations (terms, histogram, stats, percentiles, geohash-grid) now
support a new `missing` option which defines the value to consider when a
field does not have a value. This can be handy if you eg. want a terms
aggregation to handle the same way documents that have "N/A" or no value
for a `tag` field.
This works in a very similar way to the `missing` option on the `sort`
element.
One known issue is that this option sometimes cannot make the right decision
in the unmapped case: it needs to replace all values with the `missing` value
but might not know what kind of values source should be produced (numerics,
strings, geo points?). For this reason, we might want to add an `unmapped_type`
option in the future like we did for sorting.
Related to #5324
This commit makes queries and filters parsed the same way using the
QueryParser abstraction. This allowed to remove duplicate code that we had
for similar queries/filters such as `range`, `prefix` or `term`.
Previously, we were using the "statistical", technically accurate name. Instead, we
should probably use the name that people are familiar with, e.g. "Holt Winters" instead
of "triple exponential". To that end:
- `single_exp` becomes `ewma` (exponentially weighted moving average)
- `double_exp` becomes `holt`
When the `triple_exp` is added, it will be called `holt_winters`.
Colin Goodheart-Smithe
Dongjoon Hyun
Clinton Gormley
Kevin Adams
Eugene Pirogov
omiend
KangYongKyun
Nicholas Knize
Alex
Taehee Kim
Adrien Grand
Zachary Tong
Lee Hinman
Shane Connelly
Murilo Pereira
Ian Truslove
Asimov4
Sylvain Zimmer
Ryan Ernst
William Li
Christoph Büscher
caldwecr
Colin Goodheart-Smithe
Pascal Borreli