Remove the ability to specify search type ‘query_and_fetch’ and
‘df_query_and_fetch’ from the REST API.
- Adds REST tests
- Updates REST API spec to remove ‘query_and_fetch’ and
‘df_query_and_fetch’ as options
- Removes documentation for these options
Closes#9606
* Removed the docs for `index.compound_format` and `index.compound_on_flush` - these are expert settings which should probably be removed (see https://github.com/elastic/elasticsearch/issues/10778)
* Removed the docs for `index.index_concurrency` - another expert setting
* Labelled the segments verbose output as experimental
* Marked the `compression`, `precision_threshold` and `rehash` options as experimental in the cardinality and percentile aggs
* Improved the experimental text on `significant_terms`, `execution_hint` in the terms agg, and `terminate_after` param on count and search
* Removed the experimental flag on the `geobounds` agg
* Marked the settings in the `merge` and `store` modules as experimental, rather than the modules themselves
Closes#10782
The field stats api returns field level statistics such as lowest, highest values and number of documents that have at least one value for a field.
An api like this can be useful to explore a data set you don't know much about. For example you can figure at with the lowest and highest response times are, so that you can create a histogram or range aggregation with sane settings.
This api doesn't run a search to figure this statistics out, but rather use the Lucene index look these statics up (using Terms class in Lucene). So finding out these stats for fields is cheap and quick.
The min/max values are based on the type of the field. So for a numeric field min/max are numbers and date field the min/max date and other fields the min/max are term based.
Closes#10523
This commit adds a `rewrite` parameter to the validate API in order to shown
how the given query is re-written into primitive queries. For example, an MLT
query is re-written into a disjunction of the selected terms. Other use cases
include `fuzzy`, `common_terms`, or `match` query especially with a
`cutoff_frequency` parameter. Note that the explanation is only given for a
single randomly chosen shard only, so the output may vary from one shard to
another.
Relates #1412Closes#10147
Today we check every regular expression eagerly against every possible term.
This can be very slow if you have lots of unique terms, and even the bottleneck
if your query is selective.
This commit switches to Lucene regular expressions instead of Java (not exactly
the same syntax yet most existing regular expressions should keep working) and
uses the same logic as RegExpQuery to intersect the regular expression with the
terms dictionary. I wrote a quick benchmark (in the PR) to make sure it made
things faster and the same request that took 750ms on master now takes 74ms with
this change.
Close#7526
This commit brings the benefits of the `count` search type to search requests
that have a `size` of 0:
- a single round-trip to shards (no fetch phase)
- ability to use the query cache
Since `count` now provides no benefits over `query_then_fetch`, it has been
deprecated.
Close#7630
Allow to on/off scripting based on their source (where they get loaded from), the operation that executes them and their language.
The settings cover the following combinations:
- mode: on, off, sandbox
- source: indexed, dynamic, file
- engine: groovy, expressions, mustache, etc
- operation: update, search, aggs, mapping
The following settings are supported for every engine:
script.engine.groovy.indexed.update: sandbox/on/off
script.engine.groovy.indexed.search: sandbox/on/off
script.engine.groovy.indexed.aggs: sandbox/on/off
script.engine.groovy.indexed.mapping: sandbox/on/off
script.engine.groovy.dynamic.update: sandbox/on/off
script.engine.groovy.dynamic.search: sandbox/on/off
script.engine.groovy.dynamic.aggs: sandbox/on/off
script.engine.groovy.dynamic.mapping: sandbox/on/off
script.engine.groovy.file.update: sandbox/on/off
script.engine.groovy.file.search: sandbox/on/off
script.engine.groovy.file.aggs: sandbox/on/off
script.engine.groovy.file.mapping: sandbox/on/off
For ease of use, the following more generic settings are supported too:
script.indexed: sandbox/on/off
script.dynamic: sandbox/on/off
script.file: sandbox/on/off
script.update: sandbox/on/off
script.search: sandbox/on/off
script.aggs: sandbox/on/off
script.mapping: sandbox/on/off
These will be used to calculate the more specific settings, using the stricter setting of each combination. Operation based settings have precedence over conflicting source based ones.
Note that the `mustache` engine is affected by generic settings applied to any language, while native scripts aren't as they are static by definition.
Also, the previous `script.disable_dynamic` setting can now be deprecated.
Closes#6418Closes#10116Closes#10274
The behaviour is better in the case someone has multiple levels of nested object fields defined in the mapping and like to define a single inner_hits definition that is two or more levels deep.
If someone wants inner hits on a nested field that is 2 levels deep the following would need to be defined:
```
{
...
"inner_hits" : {
"path" : {
"level1" : {
"inner_hits" : {
"path" : {
"level2" : {
"query" : { .... }
}
}
}
}
}
}
}
```
With this change the above can be defined as:
```
{
...
"inner_hits" : {
"path" : {
"level1.level2" : {
"query" : { .... }
}
}
}
}
```
Closes#9251
The analysis chain should be used instead of relying on this, as it is
confusing when dealing with different per-field analysers.
The `locale` option was only used for `lowercase_expanded_terms`, which,
once removed, is no longer needed, so it was removed as well.
Fixes#9978
Relates to #9973
This commit adds scripting capability to significant_terms.
Custom heuristics can be implemented with a script that provides
parameters subset_freq, superset_freq,subset_size, superset_size.
closes#7850
Changed search_type docs to reflect that the `(dfs_)query_and_fetch` modes are an internal optimization and should not be specified explicitly by the user.
Relates to #9606
Removed the existing `pre_zone` and `post_zone` option in `date_histogram` in favor of
the simpler `time_zone` option. Previously, specifying different values for these could
lead to confusing scenarios where ES would return bucket keys that are not UTC.
Now `time_zone` is the only option setting, the calculation of date buckets to take place in the
preferred time zone, but after rounding converting the bucket key values back to UTC.
Closes#9062Closes#9637
Add offset option to 'date_histogram' replacing and simplifying the previous 'pre_offset' and 'post_offset' options.
This change is part of a larger clean up task for `date_histogram` from issue #9062.
We now have a very useful annotation to mark features or parameters as
experimental. Let's use it! This commit replaces some custom text warnings with
this annotation and adds this annotation to some existing features/parameters:
- inner_hits (unreleased yet)
- terminate_after (released in 1.4)
- per-bucket doc count errors in the terms agg (released in 1.4)
I also tagged with this annotation settings which should either be not needed
(like the ability to evict entries from the filter cache based on time) or that
are too deep into the way that Elasticsearch works like the Directory
implementation or merge settings.
Close#9563
These aggregations are not experimental anymore but some of their parameters
still are:
- `precision_threshold` and `rehash` on `cardinality`
- `compression` on percentiles(-ranks)
Close#9560
Histogram aggregation supports an 'offset' option to move bucket boundaries.
In a histogram with buckets of size X these can be moved from 0, X, 2X, 3X,...
by an offset value of Y to Y, X+Y, 2X+Y, 3X+Y... by using the 'offset' option.
The previous 'pre_offset' and 'post_offset' options are removed in favour of
the simplified 'offset' option.
Closes#9417Closes#9505
The `analyzer` setting is now the base setting, and `search_analyzer`
is simply an override of the search time analyzer. When setting
`search_analyzer`, `analyzer` must be set.
closes#9371
Extended_stats now displays the upper and lower bounds on standard deviations (e.g. avg +/- std).
Default is to show 2 std above/below, but can be changed using the `sigma` parameter.
Accepts non-negative doubles
Closes#9356
Inner hits allows to embed nested inner objects, children documents or the parent document that contributed to the matching of the returned search hit as inner hits, which would otherwise be hidden.
Closes#8153Closes#3022Closes#3152
This commit adds the ability to associate a bit of state with each
individual aggregation.
The aggregation response can be hard to stitch back together without
having a reference to the aggregation request. In many cases this is not
available, many json serializer frameworks cache types globally or have a
static deserialisation override mechanism. In these cases making the
original request available, if at all possible, would be a hack.
The old facets returned `_type` which was just enough metadata to know
what the originating facet type in the request was.
This PR takes `_type` one step further by introducing ANY arbitrary meta
data. This could be further <strike>ab</strike>used for instance by
generic/automated aggregations that include UI state (color information,
thresholds, user input states, etc) per aggregation.
This commit adds a new field to the response of the terms aggregation called
`sum_other_doc_count` which is equal to the sum of the doc counts of the buckets
that did not make it to the list of top buckets. It is typically useful to have
a sector called eg. `other` when using terms aggregations to build pie charts.
Example query and response:
```json
GET test/_search?search_type=count
{
"aggs": {
"colors": {
"terms": {
"field": "color",
"size": 3
}
}
}
}
```
```json
{
[...],
"aggregations": {
"colors": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 4,
"buckets": [
{
"key": "blue",
"doc_count": 65
},
{
"key": "red",
"doc_count": 14
},
{
"key": "brown",
"doc_count": 3
}
]
}
}
}
```
Close#8213
This is functionally equivalent to before, so there should be no
user-visible impact, except I added a NOTE in the docs warning about
the interaction of pagination and rescoring.
Closes#6232Closes#7707
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'
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
Aggregations are collection-wide statistics, which is incompatible with the
collection mode of search_type=SCAN since it doesn't collect all matches on
calls to the search API.
Close#7429
Aggregations are collection-wide statistics so they would always be the same.
In order to save CPU/bandwidth, we can just return them on the first page.
Same as #1642 but for aggregations.
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
Implements a new Exists API allowing users to do fast exists check on any matched documents for a given query.
This API should be faster then using the Count API as it will:
- early terminate the search execution once any document is found to exist
- return the response as soon as the first shard reports matched documents
closes#6995
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
Allow users to control document collection termination, if a specified terminate_after number is
set. Upon setting the newly added parameter, the response will include a boolean terminated_early
flag, indicating if the document collection for any shard terminated early.
closes#6876
A new option `prune` has been added to allow users to control phrase suggestion pruning when `collate`
is set. If the new option is set, the phrase suggestion option will contain a boolean `collate_match`
indicating whether the respective result had hits in collation.
CLoses#6927
The newly added collate option will let the user provide a template query/filter which will be executed for every phrase suggestions generated to ensure that the suggestion matches at least one document for the filter/query.
The user can also add routing preference `preference` to route the collate query/filter and additional `params` to inject into the collate template.
Closes#3482
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 existing Note about the shorthand suggest syntax was poorly worded and confusing. Please check whether the way I've phrased it now is still correct as to what the shorthand form actually does and doesn't do: the original wording did not provide me enough information to be sure.
Thanks!
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
Because json objects are unordered this also adds an explicit order syntax
that looks like
"highlight": {
"fields": [
{"title":{ /*params*/ }},
{"text":{ /*params*/ }}
]
}
This is not useful for any of the builtin highlighters but will be useful
in plugins.
Closes#4649
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
By default More Like This API excludes the queried document from the response.
However, when debugging or when comparing scores across different queries, it
could be useful to have the best possible matched hit. So this option lets users
explicitly specify the desired behavior.
Closes#6067
In the Google Groups forum there appears to be some confusion as to what mlt
does. This documentation update should hopefully help demystifying this
feature, and provide some understanding as to how to use its parameters.
Closes#6092
- Randomized integration tests for the benchmark API.
- Negative tests for cases where the cluster cannot run benchmarks.
- Return 404 on missing benchmark name.
- Allow to specify 'types' as an array in the JSON syntax when describing a benchmark competition.
- Don't record slowest for single-request competitions.
Closes#6003, #5906, #5903, #5904
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
The default precision was way too exact and could lead people to
think that geo context suggestions are not working. This patch now
requires you to set the precision in the mapping, as elasticsearch itself
can never tell exactly, what the required precision for the users
suggestions are.
Closes#5621
By default the date_/histogram returns all the buckets within the range of the data itself, that is, the documents with the smallest values (on which with histogram) will determine the min bucket (the bucket with the smallest key) and the documents with the highest values will determine the max bucket (the bucket with the highest key). Often, when when requesting empty buckets (min_doc_count : 0), this causes a confusion, specifically, when the data is also filtered.
To understand why, let's look at an example:
Lets say the you're filtering your request to get all docs from the last month, and in the date_histogram aggs you'd like to slice the data per day. You also specify min_doc_count:0 so that you'd still get empty buckets for those days to which no document belongs. By default, if the first document that fall in this last month also happen to fall on the first day of the **second week** of the month, the date_histogram will **not** return empty buckets for all those days prior to that second week. The reason for that is that by default the histogram aggregations only start building buckets when they encounter documents (hence, missing on all the days of the first week in our example).
With extended_bounds, you now can "force" the histogram aggregations to start building buckets on a specific min values and also keep on building buckets up to a max value (even if there are no documents anymore). Using extended_bounds only makes sense when min_doc_count is 0 (the empty buckets will never be returned if the min_doc_count is greater than 0).
Note that (as the name suggest) extended_bounds is **not** filtering buckets. Meaning, if the min bounds is higher than the values extracted from the documents, the documents will still dictate what the min bucket will be (and the same goes to the extended_bounds.max and the max bucket). For filtering buckets, one should nest the histogram agg under a range filter agg with the appropriate min/max.
Closes#5224
Significance is related to the changes in document frequency observed between everyday use in the corpus and
frequency observed in the result set. The asciidocs include extensive details on the applications of this feature.
Closes#5146
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
================
This commit extends the `CompletionSuggester` by context
informations. In example such a context informations can
be a simple string representing a category reducing the
suggestions in order to this category.
Three base implementations of these context informations
have been setup in this commit.
- a Category Context
- a Geo Context
All the mapping for these context informations are
specified within a context field in the completion
field that should use this kind of information.
Supports sorting on sub-aggs down the current hierarchy. This is supported as long as the aggregation in the specified order path are of a single-bucket type, where the last aggregation in the path points to either a single-bucket aggregation or a metrics one. If it's a single-bucket aggregation, the sort will be applied on the document count in the bucket (i.e. doc_count), and if it is a metrics type, the sort will be applied on the pointed out metric (in case of a single-metric aggregations, such as avg, the sort will be applied on the single metric value)
NOTE: this commit adds a constraint on what should be considered a valid aggregation name. Aggregations names must be alpha-numeric and may contain '-' and '_'.
Closes#5253
In #4052 we added support for highlighting multi term queries using the postings highlighter. That worked only for top-level queries though, and not for multi term queries that are nested for instance within a bool query, or filtered query, or a constant score query.
The way we make this work is by walking the query structure and temporarily overriding the query rewrite method with a method that allows for multi terms extraction.
Closes#5102
* Mostly minor things like typos and grammar stuff
* Some clarifications
* The note on the deprecation was ambiguous. I've removed the problematic part so that it now definitely says it's deprecated
Detects if rescores arrive as an array instead of a plain object. If so
then parse each element of the array as a separate rescore to be executed
one after another. It looks like this:
"rescore" : [ {
"window_size" : 100,
"query" : {
"rescore_query" : {
"match" : {
"field1" : {
"query" : "the quick brown",
"type" : "phrase",
"slop" : 2
}
}
},
"query_weight" : 0.7,
"rescore_query_weight" : 1.2
}
}, {
"window_size" : 10,
"query" : {
"score_mode": "multiply",
"rescore_query" : {
"function_score" : {
"script_score": {
"script": "log10(doc['numeric'].value + 2)"
}
}
}
}
} ]
Rescores as a single object are still supported.
Closes#4748
Antonio Bonuccelli
aleph-zero
Zachary Tong
Clinton Gormley
Mehdi Mollaverdi
Mal Curtis
Martijn van Groningen
Jun Ohtani
Colin Goodheart-Smithe
markharwood
Adrien Grand
Honza Král
Alex Ksikes
marko asplund
olivier bourgain
javanna
Boaz Leskes
Simon Willnauer
Asimov4
Lee Hinman
Britta Weber
Geoff Bourne
Christoph Büscher
Oliver
Ryan Ernst
eBuildy
sweetest
David Pilato
Yasir Bamarni
Ayush
Adam Menges
David Haney
barbasa
Joel Taddei
Veres Lajos
Martijn Laarman
Areek Zillur
Brian Kim
Michael McCandless
Sergii Golubev
Andrew O'Brien
Son
mdzor
Jordan Snodgrass
smayzak
shrinidhichaudhari
londocr
Konrad Feldmeier
Mpampis Kostas
uboness
Stefan Antoni
Kurt Hurtado
Brian Murphy
Florian Hopf
Andrii Gakhov
Carsten Brandt
Duncan Angus Wilkie
Chris
stephlag
Luke Fender
fransflippo
Jad Naous
leonardo menezes
Nik Everett
Tiago Alves Macambira
Rashid Khan
Andrew Selden
gabriel-tessier
Audrey
Scott Wilkerson
Malte Schirnacher
Karl Meisterheim
Alexander Reelsen
Hannes Korte
Randy Stauner
rphadake
Florian Schilling
Kurt Hurtado
Benjamin Devèze
Binh Ly
Lars Francke