This changes adds the support to handle `nested` fields in the `composite`
aggregation. A `nested` aggregation can be used as parent of a `composite`
aggregation in order to target `nested` fields in the `sources`.
Closes#28611
Users may require the sequence number and primary terms to perform optimistic concurrency control operations. Currently, you can get the sequence number via the `docvalues_fields` API but the primary term is not accessible because it is maintained by the `SeqNoFieldMapper` and the infrastructure can't find it.
This commit adds a dedicated sub fetch phase to return both numbers that is connected to a new `seq_no_primary_term` parameter.
The "include_type_name" parameter was temporarily introduced in #37285 to facilitate
moving the default parameter setting to "false" in many places in the documentation
code snippets. Most of the places can simply be reverted without causing errors.
In this change I looked for asciidoc files that contained the
"include_type_name=true" addition when creating new indices but didn't look
likey they made use of the "_doc" type for mappings. This is mostly the case
e.g. in the analysis docs where index creating often only contains settings. I
manually corrected the use of types in some places where the docs still used an
explicit type name and not the dummy "_doc" type.
* Default include_type_name to false for get and put mappings.
* Default include_type_name to false for get field mappings.
* Add a constant for the default include_type_name value.
* Default include_type_name to false for get and put index templates.
* Default include_type_name to false for create index.
* Update create index calls in REST documentation to use include_type_name=true.
* Some minor clean-ups around the get index API.
* In REST tests, use include_type_name=true by default for index creation.
* Make sure to use 'expression == false'.
* Clarify the different IndexTemplateMetaData toXContent methods.
* Fix FullClusterRestartIT#testSnapshotRestore.
* Fix the ml_anomalies_default_mappings test.
* Fix GetFieldMappingsResponseTests and GetIndexTemplateResponseTests.
We make sure to specify include_type_name=true during xContent parsing,
so we continue to test the legacy typed responses. XContent generation
for the typeless responses is currently only covered by REST tests,
but we will be adding unit test coverage for these as we implement
each typeless API in the Java HLRC.
This commit also refactors GetMappingsResponse to follow the same appraoch
as the other mappings-related responses, where we read include_type_name
out of the xContent params, instead of creating a second toXContent method.
This gives better consistency in the response parsing code.
* Fix more REST tests.
* Improve some wording in the create index documentation.
* Add a note about types removal in the create index docs.
* Fix SmokeTestMonitoringWithSecurityIT#testHTTPExporterWithSSL.
* Make sure to mention include_type_name in the REST docs for affected APIs.
* Make sure to use 'expression == false' in FullClusterRestartIT.
* Mention include_type_name in the REST templates docs.
Adds an example on translating geohashes returned by geohashgrid
agg as bucket keys into geo bounding box filters in elasticsearch as well
as 3rd party applications.
Closes#36413
When executing terms aggregations we set the shard_size, meaning the
number of buckets to collect on each shard, to a value that's higher than
the number of requested buckets, to guarantee some basic level of
precision. We have an optimization in place so that we leave shard_size
set to size whenever we are searching against a single shard, in which
case maximum precision is guaranteed by definition.
Such optimization requires us access to the total number of shards that
the search is executing against. In the context of cross-cluster search,
once we will introduce multiple reduction steps (one per cluster) each
cluster will only know the number of local shards, which is problematic
as we should only optimize if we are searching against a single shard in a
single cluster. It could be that we are searching against one shard per cluster
in which case the current code would optimize number of terms causing
a loss of precision.
While discussing how to address the CCS scenario, we decided that we do
not want to introduce further complexity caused by this single shard
optimization, as it benefits only a minority of cases, especially when
the benefits are not so great.
This commit removes the single shard optimization, meaning that we will
always have heuristic enabled on how many number of buckets to collect
on the shards, even when searching against a single shard.
This will cause more buckets to be collected when searching against a single
shard compared to before. If that becomes a problem for some users, they
can work around that by setting the shard_size equal to the size.
Relates to #32125
This commit changes the format of the `hits.total` in the search response to be an object with
a `value` and a `relation`. The `value` indicates the number of hits that match the query and the
`relation` indicates whether the number is accurate (in which case the relation is equals to `eq`)
or a lower bound of the total (in which case it is equals to `gte`).
This change also adds a parameter called `rest_total_hits_as_int` that can be used in the
search APIs to opt out from this change (retrieve the total hits as a number in the rest response).
Note that currently all search responses are accurate (`track_total_hits: true`) or they don't contain
`hits.total` (`track_total_hits: true`). We'll add a way to get a lower bound of the total hits in a
follow up (to allow numbers to be passed to `track_total_hits`).
Relates #33028
`ScriptDocValues#getValues` was added for backwards compatibility but no
longer needed. Scripts using the syntax `doc['foo'].values` when
`doc['foo']` is a list should be using `doc['foo']` instead.
Closes#22919
This commit adds a new single value metric aggregation that calculates
the statistic called median absolute deviation, which is a measure of
variability that works on more types of data than standard deviation
Our calculation of MAD is approximated using t-digests. In the collect
phase, we collect each value visited into a t-digest. In the reduce
phase, we merge all value t-digests, then create a t-digest of
deviations using the first t-digest's median and centroids
When combine_script and reduce_script were made into required
parameters for Scripted Metric aggregations in #33452, the docs were
not updated to reflect that. This marks those parameters as required
in the documentation.
* Replace custom type names with _doc in REST examples.
* Avoid using two mapping types in the percolator docs.
* Rename doc -> _doc in the main repository README.
* Also replace some custom type names in the HLRC docs.
We generate tests from our documentation, including assertions about the
responses returned by a particular API. But sometimes we *can't* assert
that the response is correct because of some defficiency in our tooling.
Previously we marked the response `// NOTCONSOLE` to skip it, but this
is kind of odd because `// NOTCONSOLE` is really to mark snippets that
are json but aren't requests or responses. This introduces a new
construct to skip response assertions:
```
// TESTRESPONSE[skip:reason we skipped this]
```
This commit switches the joda time backcompat in scripting to use
augmentation over ZonedDateTime. The augmentation methods provide
compatibility with the missing methods between joda's DateTime and
java's ZonedDateTime. Due to getDayOfWeek returning an enum in the java
API, ZonedDateTime is wrapped so that the method can return int like the
joda time does. The java time api version is renamed to
getDayOfWeekEnum, which will be kept through 7.x for compatibility while
users switch back to getDayOfWeek once joda compatibility is removed.
The main benefit of the upgrade for users is the search optimization for top scored documents when the total hit count is not needed. However this optimization is not activated in this change, there is another issue opened to discuss how it should be integrated smoothly.
Some comments about the change:
* Tests that can produce negative scores have been adapted but we need to forbid them completely: #33309Closes#32899
We used to set `maxScore` to `0` within `TopDocs` in situations where there is really no score as the size was set to `0` and scores were not even tracked. In such scenarios, `Float.Nan` is more appropriate, which gets converted to `max_score: null` on the REST layer. That's also more consistent with lucene which set `maxScore` to `Float.Nan` when merging empty `TopDocs` (see `TopDocs#merge`).
This commit adds a boolean system property, `es.scripting.use_java_time`,
which controls the concrete return type used by doc values within
scripts. The return type of accessing doc values for a date field is
changed to Object, essentially duck typing the type to allow
co-existence during the transition from joda time to java time.
Adds a new single-value metrics aggregation that computes the weighted
average of numeric values that are extracted from the aggregated
documents. These values can be extracted from specific numeric
fields in the documents.
When calculating a regular average, each datapoint has an equal "weight"; it
contributes equally to the final value. In contrast, weighted averages
scale each datapoint differently. The amount that each datapoint contributes
to the final value is extracted from the document, or provided by a script.
As a formula, a weighted average is the `∑(value * weight) / ∑(weight)`
A regular average can be thought of as a weighted average where every value has
an implicit weight of `1`.
Closes#15731
* Adds a new auto-interval date histogram
This change adds a new type of histogram aggregation called `auto_date_histogram` where you can specify the target number of buckets you require and it will find an appropriate interval for the returned buckets. The aggregation works by first collecting documents in buckets at second interval, when it has created more than the target number of buckets it merges these buckets into minute interval bucket and continues collecting until it reaches the target number of buckets again. It will keep merging buckets when it exceeds the target until either collection is finished or the highest interval (currently years) is reached. A similar process happens at reduce time.
This aggregation intentionally does not support min_doc_count, offest and extended_bounds to keep the already complex logic from becoming more complex. The aggregation accepts sub-aggregations but will always operate in `breadth_first` mode deferring the computation of sub-aggregations until the final buckets from the shard are known. min_doc_count is effectively hard-coded to zero meaning that we will insert empty buckets where necessary.
Closes#9572
* Adds documentation
* Added sub aggregator test
* Fixes failing docs test
* Brings branch up to date with master changes
* trying to get tests to pass again
* Fixes multiBucketConsumer accounting
* Collects more buckets than needed on shards
This gives us more options at reduce time in terms of how we do the
final merge of the buckeets to produce the final result
* Revert "Collects more buckets than needed on shards"
This reverts commit 993c782d117892af9a3c86a51921cdee630a3ac5.
* Adds ability to merge within a rounding
* Fixes nonn-timezone doc test failure
* Fix time zone tests
* iterates on tests
* Adds test case and documentation changes
Added some notes in the documentation about the intervals that can bbe
returned.
Also added a test case that utilises the merging of conseecutive buckets
* Fixes performance bug
The bug meant that getAppropriate rounding look a huge amount of time
if the range of the data was large but also sparsely populated. In
these situations the rounding would be very low so iterating through
the rounding values from the min key to the max keey look a long time
(~120 seconds in one test).
The solution is to add a rough estimate first which chooses the
rounding based just on the long values of the min and max keeys alone
but selects the rounding one lower than the one it thinks is
appropriate so the accurate method can choose the final rounding taking
into account the fact that intervals are not always fixed length.
Thee commit also adds more tests
* Changes to only do complex reduction on final reduce
* merge latest with master
* correct tests and add a new test case for 10k buckets
* refactor to perform bucket number check in innerBuild
* correctly derive bucket setting, update tests to increase bucket threshold
* fix checkstyle
* address code review comments
* add documentation for default buckets
* fix typo
* Migrate scripted metric aggregation scripts to ScriptContext design #29328
* Rename new script context container class and add clarifying comments to remaining references to params._agg(s)
* Misc cleanup: make mock metric agg script inner classes static
* Move _score to an accessor rather than an arg for scripted metric agg scripts
This causes the score to be evaluated only when it's used.
* Documentation changes for params._agg -> agg
* Migration doc addition for scripted metric aggs _agg object change
* Rename "agg" Scripted Metric Aggregation script context variable to "state"
* Rename a private base class from ...Agg to ...State that I missed in my last commit
* Clean up imports after merge
This change adds a new option to the composite aggregation named `missing_bucket`.
This option can be set by source and dictates whether documents without a value for the
source should be ignored. When set to true, documents without a value for a field emits
an explicit `null` value which is then added in the composite bucket.
The `missing` option that allows to set an explicit value (instead of `null`) is deprecated in this change and will be removed in a follow up (only in 7.x).
This commit also changes how the big arrays are allocated, instead of reserving
the provided `size` for all sources they are created with a small intial size and they grow
depending on the number of buckets created by the aggregation:
Closes#29380
Jim Ferenczi
Christoph Büscher
Boaz Leskes
Julie Tibshirani
Josh Soref
Igor Motov
Luca Cavanna
João Barbosa
Jeff Hajewski
William Desportes
Jim Ferenczi
Dominik Stadler
Russ Cam
Sue Gallagher
Andy Bristol
Gordon Brown
Zachary Tong
markharwood
Nik Everett
Serge Populov
ben5556
Ryan Ernst
Paul Sanwald
lipsill
Colm O'Shea
Sandeep Kanabar
Colin Goodheart-Smithe
Jimi Ford
Peter Evers
Jonathan Little