The date_histogram accepts an interval which can be either a calendar
interval (DST-aware, leap seconds, arbitrary length of months, etc) or
fixed interval (strict multiples of SI units). Unfortunately this is inferred
by first trying to parse as a calendar interval, then falling back to fixed
if that fails.
This leads to confusing arrangement where `1d` == calendar, but
`2d` == fixed. And if you want a day of fixed time, you have to
specify `24h` (e.g. the next smallest unit). This arrangement is very
error-prone for users.
This PR adds `calendar_interval` and `fixed_interval` parameters to any
code that uses intervals (date_histogram, rollup, composite, datafeed, etc).
Calendar only accepts calendar intervals, fixed accepts any combination of
units (meaning `1d` can be used to specify `24h` in fixed time), and both
are mutually exclusive.
The old interval behavior is deprecated and will throw a deprecation warning.
It is also mutually exclusive with the two new parameters. In the future the
old dual-purpose interval will be removed.
The change applies to both REST and java clients.
Adds some validation to prevent duplicate source names from being
used in the composite agg.
Also refactored to use a ConstructingObjectParser and removed the
private ctor and setter for sources, making it mandatory.
This section should be at the same sub-level as other sections in the
auto date-histogram docs, otherwise it is rendered on to another page
and is confusing for users to understand what it's in reference to.
This helps avoid memory issues when computing deep sub-aggregations. Because it
should be rare to use sub-aggregations with significant terms, we opted to always
choose breadth first as opposed to exposing a `collect_mode` option.
Closes#28652.
Implements `geotile_grid` aggregation
This patch refactors previous implementation https://github.com/elastic/elasticsearch/pull/30240
This code uses the same base classes as `geohash_grid` agg, but uses a different hashing
algorithm to allow zoom consistency. Each grid bucket is aligned to Web Mercator tiles.
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
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
* 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.
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 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
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
This commit changes the default out-of-the-box configuration for the
number of shards from five to one. We think this will help address a
common problem of oversharding. For users with time-based indices that
need a different default, this can be managed with index templates. For
users with non-time-based indices that find they need to re-shard with
the split API in place they no longer need to resort only to
reindexing.
Since this has the impact of changing the default number of shards used
in REST tests, we want to ensure that we still have coverage for issues
that could arise from multiple shards. As such, we randomize (rarely)
the default number of shards in REST tests to two. This is managed via a
global index template. However, some tests check the templates that are
in the cluster state during the test. Since this template is randomly
there, we need a way for tests to skip adding the template used to set
the number of shards to two. For this we add the default_shards feature
skip. To avoid having to write our docs in a complicated way because
sometimes they might be behind one shard, and sometimes they might be
behind two shards we apply the default_shards feature skip to all docs
tests. That is, these tests will always run with the default number of
shards (one).
Adding some allowed abbreviated values for intervals in date histograms
as well as documenting the limitations of intervals larger than days.
Closes#23294
This change refactors the composite aggregation to add an execution mode that visits documents in the order of the values
present in the leading source of the composite definition. This mode does not need to visit all documents since it can early terminate
the collection when the leading source value is greater than the lowest value in the queue.
Instead of collecting the documents in the order of their doc_id, this mode uses the inverted lists (or the bkd tree for numerics) to collect documents
in the order of the values present in the leading source.
For instance the following aggregation:
```
"composite" : {
"sources" : [
{ "value1": { "terms" : { "field": "timestamp", "order": "asc" } } }
],
"size": 10
}
```
... can use the field `timestamp` to collect the documents with the 10 lowest values for the field instead of visiting all documents.
For composite aggregation with more than one source the execution can early terminate as soon as one of the 10 lowest values produces enough
composite buckets. For instance if visiting the first two lowest timestamp created 10 composite buckets we can early terminate the collection since it
is guaranteed that the third lowest timestamp cannot create a composite key that compares lower than the one already visited.
This mode can execute iff:
* The leading source in the composite definition uses an indexed field of type `date` (works also with `date_histogram` source), `integer`, `long` or `keyword`.
* The query is a match_all query or a range query over the field that is used as the leading source in the composite definition.
* The sort order of the leading source is the natural order (ascending since postings and numerics are sorted in ascending order only).
If these conditions are not met this aggregation visits each document like any other agg.
Paul Sanwald
Zachary Tong
James Rodewig
Zachary Tong
Jason Tedor
Antonio Matarrese
Lisa Cawley
Ian
Samuel Cifuentes García
Hannes Van De Vreken
Alexander Reelsen
Yuri Astrakhan
Jim Ferenczi
Christoph Büscher
Julie Tibshirani
Igor Motov
Luca Cavanna
Jeff Hajewski
William Desportes
Jim Ferenczi
Dominik Stadler
Sue Gallagher
markharwood
Nik Everett
Serge Populov
Ryan Ernst
lipsill
Colm O'Shea
Colin Goodheart-Smithe
Jimi Ford
Piotr Prądzyński
Adrien Grand