* `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 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.
Add infrastructure to run REST tests on a multi-version cluster
This change adds the infrastructure to run the rest tests on a multi-node
cluster that users 2 different minor versions of elasticsearch. It doesn't implement
any dedicated BWC tests but rather leverages the existing REST tests.
Since we don't have a real version to test against, the tests uses the current version
until the first minor / RC is released to ensure the infrastructure works.
Given the amount of problems this change already found I think it's worth having this run with our test suite by default. The structure of this infra will likely change over time but for now it's a step into the right direction. We will likely want to split it up into integTests and integBwcTests etc. so each plugin can have it's own bwc tests but that's left for future refactoring.
Today, certain bootstrap properties are set and read via system
properties. This action-at-distance way of managing these properties is
rather confusing, and completely unnecessary. But another problem exists
with setting these as system properties. Namely, these system properties
are interpreted as Elasticsearch settings, not all of which are
registered. This leads to Elasticsearch failing to startup if any of
these special properties are set. Instead, these properties should be
kept as local as possible, and passed around as method parameters where
needed. This eliminates the action-at-distance way of handling these
properties, and eliminates the need to register these non-setting
properties. This commit does exactly that.
Additionally, today we use the "-D" command line flag to set the
properties, but this is confusing because "-D" is a special flag to the
JVM for setting system properties. This creates confusion because some
"-D" properties should be passed via arguments to the JVM (so via
ES_JAVA_OPTS), and some should be passed as arguments to
Elasticsearch. This commit changes the "-D" flag for Elasticsearch
settings to "-E".
Martijn van Groningen
Jun Ohtani
Ryan Ernst
Nik Everett
Adrien Grand
Yannick Welsch
Alexander Reelsen
Chris Earle
javanna
Clinton Gormley
Jason Tedor
Xu Zhang
Nicolas Trésegnie
David Pilato
Simon Willnauer
Simon Willnauer
Areek Zillur
