PR #51260 moved usage counts about mapping field types and analysis to
the `_cluster/stats` API.
This documents those stats in the response section of the cluster stats
API docs.
Implement the use of scalar functions inside aggregate functions.
This allows for complex expressions inside aggregations, with or without
GROUBY as well as with or without a HAVING clause. e.g.:
```
SELECT MAX(CASE WHEN a IS NULL then -1 ELSE abs(a * 10) + 1 END) AS max, b
FROM test
GROUP BY b
HAVING MAX(CASE WHEN a IS NULL then -1 ELSE abs(a * 10) + 1 END) > 5
```
Scalar functions are still not allowed for `KURTOSIS` and `SKEWNESS` as
this is currently not implemented on the ElasticSearch side.
Fixes: #29980Fixes: #36865Fixes: #37271
(cherry picked from commit 506d1beea7abb2b45de793bba2e349090a78f2f9)
The main changes are:
1. Throw an error when updating `include_in_parent` or `include_in_root` attribute of nested field dynamically by the PUT mapping API.
2. Add a test for the change.
Closes#53792
Co-authored-by: bellengao <gbl_long@163.com>
* [DOCS] Reformat `flatten_graph` token filter
Makes the following changes to the `flatten_graph` token filter docs:
* Rewrites description and adds Lucene link
* Adds detailed analyze example
* Adds analyzer example
* Add the change log for 7.7
Add the change log for 7.7
* Update rel. notes to latest state (BC5)
Update the release notes to current state (i.e. BC5).
* Update docs/reference/release-notes/7.7.asciidoc
Co-Authored-By: James Rodewig <james.rodewig@elastic.co>
Upgrade to lucene 8.5.1 release that contains a bug fix for a bug that might introduce index corruption when deleting data from an index that was previously shrunk.
* [ML] adding prediction_field_type to inference config (#55128)
Data frame analytics dynamically determines the classification field type. This field type then dictates the encoded JSON that is written to Elasticsearch.
Inference needs to know about this field type so that it may provide the EXACT SAME predicted values as analytics.
Here is added a new field `prediction_field_type` which indicates the desired type. Options are: `string` (DEFAULT), `number`, `boolean` (where close_to(1.0) == true, false otherwise).
Analytics provides the default `prediction_field_type` when the model is created from the process.
Updates the supported upgrade path table in [Upgrade Elasticsearch][0]
to include a new row for maintenance releases. For example, this row
covers upgrading from 7.6.0 to 7.6.2.
The new table row only displays for releases greater than n.x.0. For
example, the new row will display for the 7.7.1 release but not the
7.7.0 release.
[0]: https://www.elastic.co/guide/en/elasticsearch/reference/master/setup-upgrade.html
Provides basic repository-level stats that will allow us to get some insight into how many
requests are actually being made by the underlying SDK. Currently only tracks GET and LIST
calls for S3 repositories. Most of the code is unfortunately boiler plate to add a new endpoint
that will help us better understand some of the low-level dynamics of searchable snapshots.
With this change, when a task is canceled, the task manager will cancel
not only its direct child tasks but all also its descendant tasks.
Closes#50990
Adds support for filters to T-Test aggregation. The filters can be used to
select populations based on some criteria and use values from the same or
different fields.
Closes#53692
This change converts the module and plugin parameters
for testClusters to be lazy. Meaning that the values
are not resolved until they are actually used. This
removes the requirement to use project.afterEvaluate to
be able to resolve the bundle artifact.
Note - this does not completely remove the need for afterEvaluate
since it is still needed for the custom resource extension.
The secure_settings_password was never taken into consideration in
the ReloadSecureSettings API. This commit fixes that and adds
necessary REST layer testing. Doing so, it also:
- Allows TestClusters to have a password protected keystore
so that it can be set for tests.
- Adds a parameter to the run task so that elastisearch can
be run with a password protected keystore from source.
The usage of local parameter for GetFieldMappingRequest has been removed from the underlying transport action since v2.0.
This PR deprecates the parameter from rest layer. It will be removed in next major version.
Changes boilerplate sentence of "If using a field as the argument, this
parameter only supports..." to "...this parameter supports only...".
The latter is a bit more clear and readable.
Some of these characters are special to Asciidoctor and they ruin the
rendering on this page. Instead, we use a macro to passthrough these
characters without Asciidoctor applying any subtitutions to them. This
commit then addresses some rendering issues in the thread pool docs.
Co-authored-by: James Rodewig <james.rodewig@elastic.co>
We found some problems during the test.
Data: 200Million docs, 1 shard, 0 replica
hits | avg | sum | value_count |
----------- | ------- | ------- | ----------- |
20,000 | .038s | .033s | .063s |
200,000 | .127s | .125s | .334s |
2,000,000 | .789s | .729s | 3.176s |
20,000,000 | 4.200s | 3.239s | 22.787s |
200,000,000 | 21.000s | 22.000s | 154.917s |
The performance of `avg`, `sum` and other is very close when performing
statistics, but the performance of `value_count` has always been poor,
even not on an order of magnitude. Based on some common-sense knowledge,
we think that `value_count` and sum are similar operations, and the time
consumed should be the same. Therefore, we have discussed the agg
of `value_count`.
The principle of counting in es is to traverse the field of each
document. If the field is an ordinary value, the count value is
increased by 1. If it is an array type, the count value is increased
by n. However, the problem lies in traversing each document and taking
out the field, which changes from disk to an object in the Java
language. We summarize its current problems with Elasticsearch as:
- Number cast to string overhead, and GC problems caused by a large
number of strings
- After the number type is converted to string, sorting and other
unnecessary operations are performed
Here is the proof of type conversion overhead.
```
// Java long to string source code, getChars is very time-consuming.
public static String toString(long i) {
int size = stringSize(i);
if (COMPACT_STRINGS) {
byte[] buf = new byte[size];
getChars(i, size, buf);
return new String(buf, LATIN1);
} else {
byte[] buf = new byte[size * 2];
StringUTF16.getChars(i, size, buf);
return new String(buf, UTF16);
}
}
```
test type | average | min | max | sum
------------ | ------- | ---- | ----------- | -------
double->long | 32.2ns | 28ns | 0.024ms | 3.22s
long->double | 31.9ns | 28ns | 0.036ms | 3.19s
long->String | 163.8ns | 93ns | 1921 ms | 16.3s
particularly serious.
Our optimization code is actually very simple. It is to manage different
types separately, instead of uniformly converting to string unified
processing. We added type identification in ValueCountAggregator, and
made special treatment for number and geopoint types to cancel their
type conversion. Because the string type is reduced and the string
constant is reduced, the improvement effect is very obvious.
hits | avg | sum | value_count | value_count | value_count | value_count | value_count | value_count |
| | | double | double | keyword | keyword | geo_point | geo_point |
| | | before | after | before | after | before | after |
----------- | ------- | ------- | ----------- | ----------- | ----------- | ----------- | ----------- | ----------- |
20,000 | 38s | .033s | .063s | .026s | .030s | .030s | .038s | .015s |
200,000 | 127s | .125s | .334s | .078s | .116s | .099s | .278s | .031s |
2,000,000 | 789s | .729s | 3.176s | .439s | .348s | .386s | 3.365s | .178s |
20,000,000 | 4.200s | 3.239s | 22.787s | 2.700s | 2.500s | 2.600s | 25.192s | 1.278s |
200,000,000 | 21.000s | 22.000s | 154.917s | 18.990s | 19.000s | 20.000s | 168.971s | 9.093s |
- The results are more in line with common sense. `value_count` is about
the same as `avg`, `sum`, etc., or even lower than these. Previously,
`value_count` was much larger than avg and sum, and it was not even an
order of magnitude when the amount of data was large.
- When calculating numeric types such as `double` and `long`, the
performance is improved by about 8 to 9 times; when calculating the
`geo_point` type, the performance is improved by 18 to 20 times.
The use of available processors, the terminology, and the settings
around it have evolved over time. This commit cleans up some places in
the codes and in the docs to adjust to the current terminology.
Creates a reusable template for token filter reference documentation.
Contributors can make a copy of this template and customize it when
documenting new token filters.
Implement DATETIME_PARSE(<datetime_str>, <pattern_str>) function
which allows to parse a datetime string according to the specified
pattern into a datetime object. The patterns allowed are those of
java.time.format.DateTimeFormatter.
Relates to #53714
(cherry picked from commit 3febcd8f3cdf9fdda4faf01f23a5f139f38b57e0)
This commit includes a number of changes to reduce overall build
configuration time. These optimizations include:
- Removing the usage of the 'nebula.info-scm' plugin. This plugin
leverages jgit to load read various pieces of VCS information. This
is mostly overkill and we have our own minimal implementation for
determining the current commit id.
- Removing unnecessary build dependencies such as perforce and jgit
now that we don't need them. This reduces our classpath considerably.
- Expanding the usage lazy task creation, particularly in our
distribution projects. The archives and packages projects create
lots of tasks with very complex configuration. Avoiding the creation
of these tasks at configuration time gives us a nice boost.
Implement DATETIME_FORMAT(<date/datetime/time>, ) function
which allows for formatting a timestamp to the specified format. The
patterns allowed as those of java.time.format.DateTimeFormatter.
Related to #53714
(cherry picked from commit 72be0b54a9299e87e785469cdc9aafac2a48c046)
In 7.x, an index template will fail to apply if it contains a `_default_`
mapping. Several users have expressed confusion over the fact that loading the
template doesn't show any default mappings. This docs change clarifies that in
order to see all mappings in the template, you must pass `include_type_name`.
Adds a detailed example to the "Avoid scripts" section of the "Tune
for search speed" docs. The detail outlines how a script used to
transform indexed data can be moved to ingest.
The update also removes an outdated reference to supported script
languages.
Andrei Dan
James Rodewig
Adrien Grand
markharwood
Marios Trivyzas
Lisa Cawley
Julie Tibshirani
Bogdan Pintea
Ignacio Vera
Benjamin Trent
Jake Landis
Yang Wang
Igor Motov
Yannick Welsch
Nhat Nguyen
Peter Dyson
Vishal Patel
Ioannis Kakavas
Jason Tedor
Nik Everett
oneoneonepig
István Zoltán Szabó
Mark Vieira
Théophile Helleboid - chtitux