This commit removes the method Strings#splitStringToArray and replaces
the call sites with invocations to String#split. There are only two
explanations for the existence of this method. The first is that
String#split is slightly tricky in that it accepts a regular expression
rather than a character to split on. This means that if s is a string,
s.split(".") does not split on the character '.', but rather splits on
the regular expression '.' which splits on every character (of course,
this is easily fixed by invoking s.split("\\.") instead). The second
possible explanation is that (again) String#split accepts a regular
expression. This means that there could be a performance concern
compared to just splitting on a single character. However, it turns out
that String#split has a fast path for the case of splitting on a single
character and microbenchmarks show that String#split has 1.5x--2x the
throughput of Strings#splitStringToArray. There is a slight behavior
difference between Strings#splitStringToArray and String#split: namely,
the former would return an empty array in cases when the input string
was null or empty but String#split will just NPE at the call site on
null and return a one-element array containing the empty string when the
input string is empty. There was only one place relying on this behavior
and the call site has been modified accordingly.
Lucene allows to create a ICUTokenizer with a special config argument
enabling the customization of the rule based iterator by providing
custom rules files.
This commit enable this feature. Users could provide a list of RBBI rule
files to ICU tokenizer.
closes#13146
Now that the current uses of magical camelCase support have been
deprecated, we can remove these in master (sans remaining issues like
BulkRequest). This change removes camel case support from ParseField,
query types, analysis, and settings lookup.
see #8988
* `rename` processor, renamed `to` to `target_field`
* `date` processor, renamed `match_field` to `field` and renamed `match_formats` to `formats`
* `geoip` processor, renamed `source_field` to `field` and renamed `fields` to `properties`
* `attachment` processor, renamed `source_field` to `field` and renamed `fields` to `properties`
Closes#17835
This makes all numeric fields including `date`, `ip` and `token_count` use
points instead of the inverted index as a lookup structure. This is expected
to perform worse for exact queries, but faster for range queries. It also
requires less storage.
Notes about how the change works:
- Numeric mappers have been split into a legacy version that is essentially
the current mapper, and a new version that uses points, eg.
LegacyDateFieldMapper and DateFieldMapper.
- Since new and old fields have the same names, the decision about which one
to use is made based on the index creation version.
- If you try to force using a legacy field on a new index or a field that uses
points on an old index, you will get an exception.
- IP addresses now support IPv6 via Lucene's InetAddressPoint and store them
in SORTED_SET doc values using the same encoding (fixed length of 16 bytes
and sortable).
- The internal MappedFieldType that is stored by the new mappers does not have
any of the points-related properties set. Instead, it keeps setting the index
options when parsing the `index` property of mappings and does
`if (fieldType.indexOptions() != IndexOptions.NONE) { // add point field }`
when parsing documents.
Known issues that won't fix:
- You can't use numeric fields in significant terms aggregations anymore since
this requires document frequencies, which points do not record.
- Term queries on numeric fields will now return constant scores instead of
giving better scores to the rare values.
Known issues that we could work around (in follow-up PRs, this one is too large
already):
- Range queries on `ip` addresses only work if both the lower and upper bounds
are inclusive (exclusive bounds are not exposed in Lucene). We could either
decide to implement it, or drop range support entirely and tell users to
query subnets using the CIDR notation instead.
- Since IP addresses now use a different representation for doc values,
aggregations will fail when running a terms aggregation on an ip field on a
list of indices that contains both pre-5.0 and 5.0 indices.
- The ip range aggregation does not work on the new ip field. We need to either
implement range aggs for SORTED_SET doc values or drop support for ip ranges
and tell users to use filters instead. #17700Closes#16751Closes#17007Closes#11513
When it comes to query parsing, either a field is tokenized and it would go
through analysis with its search_analyzer. Or it is not tokenized and the
raw string should be passed to termQuery(). Since numeric fields are not
tokenized and also declare a search analyzer, values would currently go through
analysis twice...
This commit removes `MappedFieldType.value` and simplifies
`MappedFieldType.valueforSearch`. `valueforSearch` was used to post-process
values that come for stored fields (eg. to convert a long back to a string
representation of a date in the case of a date field) and also values that
are extracted from the source but only in the case of GET calls: it would
not be called when performing source filtering on search requests.
`valueforSearch` is now only called for stored fields, since values that are
extracted from the source should already be formatted as expected.
* upgrades numerics to new Point format
* updates geo api changes
* adds GeoPointDistanceRangeQuery as XGeoPointDistanceRangeQuery
* cuts over to ES GeoHashUtils
CBOR is natively supported in Elasticsearch and allows for byte arrays.
This means, that by using CBOR the user can prevent base64 conversions
for the data being sent back and forth.
This PR adds support to extract data from a byte array in addition to
a string. This also required to add a ByteArrayValueSource class.
We have both `Settings.settingsBuilder` and `Settings.builder` that do exactly
the same thing, so we should keep only one. I kept `Settings.builder` since it
has my preference but also it is the one that we use in examples of the Java API.
This PR just adds a new test where we check that we forcing a value in the JSON document actually works as expected:
```json
{
"file": {
"_content": "BASE64"
"_name": "12-240.pdf",
"_language": "en",
"_content_type": "pdf"
}
}
```
Note that we don't support forcing all values. So sending:
```json
{
"file": {
"_content": "BASE64"
"_name": "12-240.pdf",
"_title": "12-240.pdf",
"_keywords": "Div42 Src580 LGE Mechtech",
"_language": "en",
"_content_type": "pdf"
}
}
```
Will have absolutely no effect on fields `title` and `keywords`.
Note that when `_language` is set, it only works if `index.mapping.attachment.detect_language` is set to `true`.
Related to https://discuss.elastic.co/t/mapper-attachments/46615/4
This removes the inconsistent output of IP addresses. The format was parsing-unfriendly and it makes it hard
to reason about API responses, such as to _nodes.
With this change in place, it will never print the hostname as part of the default format, which has the
added benefit that it can be used consistently for URIs, which was not the case when the hostname might
appear at the front with "hostname/ip:port".
`text` fields will have fielddata disabled by default. Fielddata can still be
enabled on an existing index by setting `fielddata=true` in the mappings.
Node roles are now serialized as well, they are not part of the node attributes anymore. DiscoveryNodeService takes care of dividing settings into attributes and roles. DiscoveryNode always requires to pass in attributes and roles separately.
We can be better at checking `buffer_size` and `chunk_size` for S3 repositories.
For example, we know that:
* `buffer_size` should be more than `5mb`
* `chunk_size` should be no more than `5tb`
* `buffer_size` should be lower than `chunk_size`
Otherwise, setting `buffer_size` is useless.
For the record:
`chunk_size` is a Snapshot setting whatever the implementation is.
`buffer_size` is an S3 implementation setting.
Let say that you are snapshotting a 500mb file. If you set `chunk_size` to `200mb`, then Snapshot service will call S3 repository to snapshot 3 files with the following sizes:
* `200mb`
* `200mb`
* `100mb`
If you set `buffer_size` to `100mb` (AWS maximum size recommendation), the first file of `200mb` will be uploaded on S3 using the multipart feature in 2 chunks and the workflow is basically the following:
* create the multipart request and get back an `id` from AWS S3 platform
* upload part1: `100mb`
* upload part2: `100mb`
* "commit" the full upload using the `id`.
Closes#17244.
Today we allow to set all kinds of index level settings on the node level which
is error prone and difficult to get right in a consistent manner.
For instance if some analyzers are setup in a yaml config file some nodes might
not have these analyzers and then index creation fails.
Nevertheless, this change allows some selected settings to be specified on a node level
for instance:
* `index.codec` which is used in a hot/cold node architecture and it's value is really per node or per index
* `index.store.fs.fs_lock` which is also dependent on the filesystem a node uses
All other index level setting must be specified on the index level. For existing clusters the index must be closed
and all settings must be updated via the API on each of the indices.
Closes#16799
The build currently uses the old maven support in gradle. This commit
switches to use the newer maven-publish plugin. This will allow future
changes, for example, easily publishing to artifactory.
An additional part of this change makes publishing of build-tools part
of the normal publishing, instead of requiring a separate upload step
from within buildSrc. That also sets us up for a follow up to enable
precomit checks on the buildSrc code itself.
Jason Tedor
Martijn van Groningen
Tal Levy
Yannick Welsch
David Pilato
Alexander Reelsen
Xu Zhang
Ryan Ernst
Jun Ohtani
Nik Everett
Adrien Grand
Chris Earle
javanna
Clinton Gormley
Nicolas Trésegnie
Simon Willnauer
