Removed `parse(String index, String type, String id, BytesReference source)` in DocumentMapper.java and replaced all of its use in Test files with `parse(SourceToParse source)`.
`parse(String index, String type, String id, BytesReference source)` was only used in test files and never in the main code so it was removed. All of the test files that used it was then modified to use `parse(SourceToParse source)` method that existing in DocumentMapper.java
* Remove a checked exception, replacing it with `ParsingException`.
* Remove all Parser classes for the yaml sections, replacing them with static methods.
* Remove `ClientYamlTestFragmentParser`. Isn't used any more.
* Remove `ClientYamlTestSuiteParseContext`, replacing it with some static utility methods.
I did not rewrite the parsers using `ObjectParser` because I don't think it is worth it right now.
Introduces `XContentParser#namedObject which works a little like
`StreamInput#readNamedWriteable`: on startup components register
parsers under names and a superclass. At runtime we look up the
parser and call it to parse the object.
Right now the parsers take a context object they use to help with
the parsing but I hope to be able to eliminate the need for this
context as most what it is used for at this point is to move
around parser registries which should be replaced by this method
eventually. I make no effort to do so in this PR because it is
big enough already. This is meant to the a start down a road that
allows us to remove classes like `QueryParseContext`,
`AggregatorParsers`, `IndicesQueriesRegistry`, and
`ParseFieldRegistry`.
The goal here is to reduce the amount of plumbing required to
allow parsing pluggable things. With this you don't have to pass
registries all over the place. Instead you must pass a super
registry to fewer places and use it to wrap the reader. This is
the same tradeoff that we use for NamedWriteable and it allows
much, much simpler binary serialization. We think we want that
same thing for xcontent serialization.
The only parsing actually converted to this method is parsing
`ScoreFunctions` inside of `FunctionScoreQuery`. I chose this
because it is relatively self contained.
For the record, I also had to remove the geo-hash cell and geo-distance range
queries to make the code compile. These queries already throw an exception in
all cases with 5.x indices, so that does not hurt any more.
I also had to rename all 2.x bwc indices from `index-${version}` to
`unsupported-${version}` to make `OldIndexBackwardCompatibilityIT`
happy.
Lucene 6.2 added index and query support for numeric ranges. This commit adds a new RangeFieldMapper for indexing numeric (int, long, float, double) and date ranges and creating appropriate range and term queries. The design is similar to NumericFieldMapper in that it uses a RangeType enumerator for implementing the logic specific to each type. The following range types are supported by this field mapper: int_range, float_range, long_range, double_range, date_range.
Lucene does not provide a DocValue field specific to RangeField types so the RangeFieldMapper implements a CustomRangeDocValuesField for handling doc value support.
When executing a Range query over a Range field, the RangeQueryBuilder has been enhanced to accept a new relation parameter for defining the type of query as one of: WITHIN, CONTAINS, INTERSECTS. This provides support for finding all ranges that are related to a specific range in a desired way. As with other spatial queries, DISJOINT can be achieved as a MUST_NOT of an INTERSECTS query.
At one point in the past when moving out the rest tests from core to
their own subproject, we had multiple test classes which evenly split up
the tests to run. However, we simplified this and went back to a single
test runner to have better reproduceability in tests. This change
removes the remnants of that multiplexing support.
The `IndexService#newQueryShardContext()` method creates a QueryShardContext on
shard `0`, with a `null` reader and that uses `System.currentTimeMillis()` to
resolve `now`. This may hide bugs, since the shard id is sometimes used for
query parsing (it is used to salt random score generation in `function_score`),
passing a `null` reader disables query rewriting and for some use-cases, it is
simply not ok to rely on the current timestamp (eg. percolation). So this pull
request removes this method and instead requires that all call sites provide
these parameters explicitly.
Today we hold on to all possible tokenizers, tokenfilters etc. when we create
an index service on a node. This was mainly done to allow the `_analyze` API to
directly access all these primitive. We fixed this in #19827 and can now get rid of
the AnalysisService entirely and replace it with a simple map like class. This
ensures we don't create a gazillion long living objects that are entirely useless since
they are never used in most of the indices. Also those objects might consume a considerable
amount of memory since they might load stopwords or synonyms etc.
Closes#19828
This makes GET operations more consistent with `_search` operations which expect
`(stored_)fields` to work on stored fields and source filtering to work on the
`_source` field. This is now possible thanks to the fact that GET operations
do not read from the translog anymore (#20102) and also allows to get rid of
`FieldMapper#isGenerated`.
The `_termvectors` API (and thus more_like_this too) was relying on the fact
that GET operations would extract fields from either stored fields or the source
so the logic to do this that used to exist in `ShardGetService` has been moved
to `TermVectorsService`. It would be nice that term vectors do not rely on this,
but this does not seem to be a low hanging fruit.
I also reduced the visibility of a couple classes and renamed/consolidated some
test classes for consistency, eg. removing the `Simple` prefix or using the
`<Type>FieldMapperTests` convention for testing field mappers.
This makes it obvious that these tests are for running the client yaml
suites. Now that there are other ways of running tests using the REST
client against a running cluster we can't go on calling the shared
client yaml tests "REST tests". They are rest tests, but they aren't
**the** rest tests.
This adds a header that looks like `Location: /test/test/1` to the
response for the index/create/update API. The requirement for the header
comes from https://www.w3.org/Protocols/rfc2616/rfc2616-sec10.htmlhttps://tools.ietf.org/html/rfc7231#section-7.1.2 claims that relative
URIs are OK. So we use an absolute path which should resolve to the
appropriate location.
Closes#19079
This makes large changes to our rest test infrastructure, allowing us
to write junit tests that test a running cluster via the rest client.
It does this by splitting ESRestTestCase into two classes:
* ESRestTestCase is the superclass of all tests that use the rest client
to interact with a running cluster.
* ESClientYamlSuiteTestCase is the superclass of all tests that use the
rest client to run the yaml tests. These tests are shared across all
official clients, thus the `ClientYamlSuite` part of the name.
This changes adds a MapperPlugin interface which allows pull style
retrieval of mappers and metadata mappers added by plugins. For now, I
have kept the MapperRegistry, but this should be removed in the future
as it is just a silly container for 2 maps which could themselves be
passed around.
In 2.0 we added plugin descriptors which require defining a name and
description for the plugin. However, we still have name() and
description() which must be overriden from the Plugin class. This still
exists for classpath plugins. But classpath plugins are mainly for
tests, and even then, referring to classpath plugins with their class is
a better idea. This change removes name() and description(), replacing
the name for classpath plugins with the full class name.
This change does the following:
- Queries that are currently unsupported such as prefix queries on numeric
fields or term queries on geo fields now throw an error rather than returning
a query that does not match anything.
- Fuzzy queries on numeric, date and ip fields are now unsupported: they used
to create range queries, we now expect users to use range queries directly.
Fuzzy, regexp and prefix queries are now only supported on text/keyword
fields (including `_all`).
- The `_uid` and `_id` fields do not support prefix or range queries anymore as
it would prevent us to store them more efficiently in the future, eg. by
using a binary encoding.
Note that it is still possible to ignore these errors by using the `lenient`
option of the `match` or `query_string` queries.
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 the ability to use string fields on indices created on or
after 5.0. Dynamic mappings now generate text fields by default for strings
but there are plans to also add a sub keyword field (in a future PR).
Most of the changes in this commit are just about replacing string with
keyword or text. Some tests have been removed because they existed because of
corner cases of string mappings like setting ignore-above on a text field or
enabling term vectors on a keyword field which are now impossible.
The plan is to remove strings entirely in 6.0.
IndexShard currently holds an arbitraritly used `getQueryShardContext` that comes
out of a ThreadLocal. It's usage is undefined and arbitraty since there is also
such a method with different semantics on `IndexService` This commit removes the threadLocal on
IndexShard as well as on the context itself. It's types are now a member and the QueryShardContext
lifecycle is managed byt SearchContext which passes the types on from the SearchRequest.
The rest test framework, because it used to be tightly integrated with
ESIntegTestCase, currently expects the addresses for the test cluster to
be passed using the transport protocol port. However, it only uses this
to then find the http address.
This change makes ESRestTestCase extend from ESTestCase instead of
ESIntegTestCase, and changes the sysprop used to tests.rest.cluster,
which now takes the http address.
closes#15459
* Added percolator field mapper that extracts the query terms and indexes these terms with the percolator query.
* At percolate time these extracted terms are used to query percolator queries that are like to be evaluated. This can significantly cut down the time it takes to percolate. Whereas before all percolator queries were evaluated if they matches with the document being percolated.
* Changes made to percolator queries are no longer immediately visible, a refresh needs to happen before the changes are visible.
* By default the percolate api only returns upto 10 matches instead of returning all matching percolator queries.
* Made percolate more modular, so that it is easier to add unit tests.
* Added unit tests for the percolator.
Closes#12664Closes#13646
DocumentMapperParser has both parse and parseCompressed methods. Except that the
parse methods are ONLY used from the unit tests. This commit removes the parse
method and moves all tests to parseCompressed so that they test more
realistically how mappings are managed.
Then I renamed parseCompressed to parse given that this is the only alternative
anyway.
Today mappings are mutable because of two APIs:
- Mapper.merge, which expects changes to be performed in-place
- IncludeInAll, which allows to change whether values should be put in the
`_all` field in place.
This commit changes both APIs to return a modified copy instead of modifying in
place so that mappings can be immutable. For now, only the type-level object is
immutable, but in the future we can imagine making them immutable at the
index-level so that mapping updates could be completely atomic at the index
level.
Close#9365
When importing dangling indices on a single node that is data and master eligable the async dangling index
call can still be in-flight when the cluster is checked for green / yellow. Adding a dedicated master node
and a data only node that does the importing fixes this issus just like we do in OldIndexBackwardsCompatibilityIT
This moves the registration of field mappers from the index level to the node
level and also ensures that mappers coming from plugins are treated no
differently from core mappers.
This change removes the leftover pom files. A couple files were left for
reference, namely in qa tests that have not yet been migrated (vagrant
and multinode). The deb and rpm assemblies also still exist for
reference when finishing their setup in gradle.
See #13930
The @IndexSettings annoationat has been used to differentiate between node-level
and index level settings. It was also decoupled from realtime-updates such that
the settings object that a class got injected when it was created was static and
not subject to change when an update was applied. This change removes the annoation
and replaces it with a full-fledged class that adds type-safety and encapsulates additional
functionality as well as checks on the settings.
Plugin tests require having rest-api tests, and currently copy that spec
from a directory in the root of the plugin source into the test
resources. This change moves the rest-api-spec dir into test resources
so it is like any other test resources. It also removes unnecessary
configuration for resources from the shared plugin pom.
When running a RestIT test from the IDE, you actually start an internal node which does not automatically load the plugin you would like to test.
We need to add:
```java
@Override
protected Collection<Class<? extends Plugin>> nodePlugins() {
return pluginList(PLUGIN_HERE.class);
}
```
Everything works fine when running from maven because each test basically:
* installs elasticsearch
* installs one plugin
* starts elasticsearch with this plugin loaded
* runs the test
Note that this PR only fixes the fact we run an internal cluster with the expected plugin.
Cloud tests will still fail when run from the IDE because is such a case you actually start an internal node with many mock plugins.
And REST test suite for cloud plugins basically checks if the plugin is running by checking the output of NodesInfo API.
And we check:
```yml
- match: { nodes.$master.plugins.0.name: cloud-azure }
- match: { nodes.$master.plugins.0.jvm: true }
```
But in that case, this condition is certainly false as we started also `mock-transport-service`, `mock-index-store`, `mock-engine-factory`, `node-mocks`, `asserting-local-transport`, `mock-search-service`.
Closes#13479
AdityaJNair
Nik Everett
Boaz Leskes
Adrien Grand
Nicholas Knize
Ryan Ernst
Simon Willnauer
Jun Ohtani
Alexander Reelsen
Areek Zillur
Simon Willnauer
Daniel Mitterdorfer
Martijn van Groningen
David Pilato