Include size of snapshot in snapshot metadata
Adds difference of number of files (and file sizes) between prev and current snapshot. Total number/size reflects total number/size of files in snapshot.
Closes#18543
Treats geohashes as grid cells instead of just points when the
geohashes are used to specify the edges in the geo_bounding_box
query. For example, if a geohash is used to specify the top_left
corner, the top left corner of the geohash cell will be used as the
corner of the bounding box.
Closes#25154
The current documentation isn't very clear about how incomplete dates are
treated when specifying custom formats in a `range` query. This change adds a
note explaining how missing month or year coordinates translate to dates that
have the missings slots filled with unix time start date (1970-01-01)
Closes#30634
This commit reintroduces 31251c9 and 63a5799. These commits introduced a
memory leak and were reverted. This commit brings those commits back
and fixes the memory leak by removing unnecessary retain method calls.
This reverts commit 31251c9 introduced in #30695.
We suspect this commit is causing the OOME's reported in #30811 and we will use this PR to test this assertion.
This commit adds the ability to configure how a docvalue field should be
formatted, so that it would be possible eg. to return a date field
formatted as the number of milliseconds since Epoch.
Closes#27740
Lucene has a new `FeatureField` which gives the ability to record numeric
features as term frequencies. Its main benefit is that it allows to boost
queries with the values of these features and efficiently skip non-competitive
documents at the same time using block-max WAND and indexed impacts.
Currently the first snippet in the documentation test in script-fields.asciidoc
isn't executed, although it has the CONSOLE annotation. Adding a test setup
annotation to it seems to fix the problem.
This is related to #29500 and #28898. This commit removes the abilitiy
to disable http pipelining. After this commit, any elasticsearch node
will support pipelined requests from a client. Additionally, it extracts
some of the http pipelining work to the server module. This extracted
work is used to implement pipelining for the nio plugin.
=== Char Group Tokenizer
The `char_group` tokenizer breaks text into terms whenever it encounters
a
character which is in a defined set. It is mostly useful for cases where
a simple
custom tokenization is desired, and the overhead of use of the
<<analysis-pattern-tokenizer, `pattern` tokenizer>>
is not acceptable.
=== Configuration
The `char_group` tokenizer accepts one parameter:
`tokenize_on_chars`::
A string containing a list of characters to tokenize the string on.
Whenever a character
from this list is encountered, a new token is started. Also supports
escaped values like `\\n` and `\\f`,
and in addition `\\s` to represent whitespace, `\\d` to represent
digits and `\\w` to represent letters.
Defaults to an empty list.
=== Example output
```The 2 QUICK Brown-Foxes jumped over the lazy dog's bone for $2```
When the configuration `\\s-:<>` is used for `tokenize_on_chars`, the
above sentence would produce the following terms:
```[ The, 2, QUICK, Brown, Foxes, jumped, over, the, lazy, dog's, bone,
for, $2 ]```
This commit fixes docs failure on language analyzers when compared to the built in analyzers.
The `elision` filters used by the rebuilt language analyzers should be case insensitive to match
the definition of the prebuilt analyzers.
Closes#30557
The getDate() and getDates() existed prior to 5.x on long fields in
scripting. In 5.x, a new Date type for ScriptDocValues was added. The
getDate() and getDates() methods were left on long fields and added to date
fields to ease the transition. This commit removes those methods for
7.0.
This pipeline aggregation gives the user the ability to script functions that "move" across a window
of data, instead of single data points. It is the scripted version of MovingAvg pipeline agg.
Through custom script contexts, we expose a number of convenience methods:
- MovingFunctions.max()
- MovingFunctions.min()
- MovingFunctions.sum()
- MovingFunctions.unweightedAvg()
- MovingFunctions.linearWeightedAvg()
- MovingFunctions.ewma()
- MovingFunctions.holt()
- MovingFunctions.holtWinters()
- MovingFunctions.stdDev()
The user can also define any arbitrary logic via their own scripting, or combine with the above methods.
The geo_bounding_box query might produce false positives alongside
the right and upper edges and false negatives alongside left and
bottom edges. This commit documents the behavior and defines the
maximum error.
Closes#29196
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).
We want copying settings to be the default behavior. This commit
deprecates not copying settings, and disallows explicitly not copying
settings. This gives users a transition path to the future default
behavior.
We have a pile of documentation describing how to rebuild the built in
language analyzers and, previously, our documentation testing framework
made sure that the examples successfully built *an* analyzer but they
didn't assert that the analyzer built by the documentation matches the
built in anlayzer. Unsuprisingly, some of the examples aren't quite
right.
This adds a mechanism that tests that the analyzers built by the docs.
The mechanism is fairly simple and brutal but it seems to be working:
build a hundred random unicode sequences and send them through the
`_analyze` API with the rebuilt analyzer and then again through the
built in analyzer. Then make sure both APIs return the same results.
Each of these calls to `_anlayze` takes about 20ms on my laptop which
seems fine.
We had been using `task_id:1` or `taskId:1` because it is parses as a
valid task identifier but the `:1` part is confusing. This replaces
those examples with `task_id` which matches the response from the list
tasks API.
Closes#28314
This change adds a new plugin called `analysis-nori` that exposes
Korean text analysis in es using the new Lucene Korean analyzer module named (`nori`).
The plugin adds:
* a Korean analyzer: `nori`
* a Korean tokenizer: `nori_tokenizer`
* a part of speech stop filter: `nori_part_of_speech`
* a filter that can replace Hanja characters with their Hangul transcription: `nori_readingform`