With the removal of mapping types and the immutability of FieldTypeLookup in #58162, we no longer
have any cause to compare MappedFieldType instances. This means that we can remove all equals
and hashCode implementations, and in addition we no longer need the clone implementations which
were required for equals/hashcode testing. This greatly simplifies implementing new MappedFieldTypes,
which will be particularly useful for the runtime fields project.
Now that MappedFieldType no longer extends lucene's FieldType, we need to have a
way of getting the index information about a field necessary for building text queries,
building term vectors, highlighting, etc. This commit introduces a new TextSearchInfo
abstraction that holds this information, and a getTextSearchInfo() method to
MappedFieldType to make it available. Field types that do not support text search can
just return null here.
This allows us to remove the MapperService.getLuceneFieldType() shim method.
Fixes a bug in TextFieldMapper serialization when index is false, and adds a
base-class test to ensure that all field mappers are tested against all variations
with defaults both included and excluded.
Fixes#58188
This is currently used to set the indexVersionCreated parameter on FieldMapper.
However, this parameter is only actually used by two implementations, and clutters
the API considerably. We should just remove it, and use it directly in the
implementations that require it.
MappedFieldType is a combination of two concerns:
* an extension of lucene's FieldType, defining how a field should be indexed
* a set of query factory methods, defining how a field should be searched
We want to break these two concerns apart. This commit is a first step to doing this, breaking
the inheritance relationship between MappedFieldType and FieldType. MappedFieldType
instead has a series of boolean flags defining whether or not the field is searchable or
aggregatable, and FieldMapper has a separate FieldType passed to its constructor defining
how indexing should be done.
Relates to #56814
* Remove usage of deprecated testCompile configuration
* Replace testCompile usage by testImplementation
* Make testImplementation non transitive by default (as we did for testCompile)
* Update CONTRIBUTING about using testImplementation for test dependencies
* Fail on testCompile configuration usage
This PR replaces the marker interface with the method
FieldMapper#parsesArrayValue. I find this cleaner and it will help with the
fields retrieval work (#55363).
The refactor also ensures that only field mappers can declare they parse array
values. Previously other types like ObjectMapper could implement the marker
interface and be passed array values, which doesn't make sense.
Merging logic is currently split between FieldMapper, with its merge() method, and
MappedFieldType, which checks for merging compatibility. The compatibility checks
are called from a third class, MappingMergeValidator. This makes it difficult to reason
about what is or is not compatible in updates, and even what is in fact updateable - we
have a number of tests that check compatibility on changes in mapping configuration
that are not in fact possible.
This commit refactors the compatibility logic so that it all sits on FieldMapper, and
makes it called at merge time. It adds a new FieldMapperTestCase base class that
FieldMapper tests can extend, and moves the compatibility testing machinery from
FieldTypeTestCase to here.
Relates to #56814
Mapper.Builder currently has some complex generics on it to allow fluent builder
construction. However, the second parameter, a return type from the build() method,
is unnecessary, as we can use covariant return types. This commit removes this second
generic parameter.
`FieldMapper#parseCreateField` accepts the parse context, plus a list of fields
as an output parameter. These fields are immediately added to the document
through `ParseContext#doc()`.
This commit simplifies the signature by removing the list of fields, and having
the mappers add the fields directly to `ParseContext#doc()`. I think this is
nicer for implementors, because previously fields could be added either through
the list, or the context (through `add`, `addWithKey`, etc.)
The following settings are now no-ops:
* xpack.flattened.enabled
* xpack.logstash.enabled
* xpack.rollup.enabled
* xpack.slm.enabled
* xpack.sql.enabled
* xpack.transform.enabled
* xpack.vectors.enabled
Since these settings no longer need to be checked, we can remove settings
parameters from a number of constructors and methods, and do so in this
commit.
We also update documentation to remove references to these settings.
This commit converts the remaining isXXXAllowed methods to instead of
use isAllowed with a Feature value. There are a couple other methods
that are static, as well as some licensed features that check the
license directly, but those will be dealt with in other followups.
We believe there's no longer a need to be able to disable basic-license
features completely using the "xpack.*.enabled" settings. If users don't
want to use those features, they simply don't need to use them. Having
such features always available lets us build more complex features that
assume basic-license features are present.
This commit deprecates settings of the form "xpack.*.enabled" for
basic-license features, excluding "security", which is a special case.
It also removes deprecated settings from integration tests and unit
tests where they're not directly relevant; e.g. monitoring and ILM are
no longer disabled in many integration tests.
This is a simple naming change PR, to fix the fact that "metadata" is a
single English word, and for too long we have not followed general
naming conventions for it. We are also not consistent about it, for
example, METADATA instead of META_DATA if we were trying to be
consistent with MetaData (although METADATA is correct when considered
in the context of "metadata"). This was a simple find and replace across
the code base, only taking a few minutes to fix this naming issue
forever.
* Comprehensively test supported/unsupported field type:agg combinations (#52493)
This adds a test to AggregatorTestCase that allows us to programmatically
verify that an aggregator supports or does not support a particular
field type. It fetches the list of registered field type parsers,
creates a MappedFieldType from the parser and then attempts to run
a basic agg against the field.
A supplied list of supported VSTypes are then compared against the
output (success or exception) and suceeds or fails the test accordingly.
Co-Authored-By: Mark Tozzi <mark.tozzi@gmail.com>
* Skip fields that are not aggregatable
* Use newIndexSearcher() to avoid incompatible readers (#52723)
Lucene's `newSearcher()` can generate readers like ParallelCompositeReader
which we can't use. We need to instead use our helper `newIndexSearcher`
The `top_metrics` agg is kind of like `top_hits` but it only works on
doc values so it *should* be faster.
At this point it is fairly limited in that it only supports a single,
numeric sort and a single, numeric metric. And it only fetches the "very
topest" document worth of metric. We plan to support returning a
configurable number of top metrics, requesting more than one metric and
more than one sort. And, eventually, non-numeric sorts and metrics. The
trick is doing those things fairly efficiently.
Co-Authored by: Zachary Tong <zach@elastic.co>
Backport of #48849. Update `.editorconfig` to make the Java settings the
default for all files, and then apply a 2-space indent to all `*.gradle`
files. Then reformat all the files.
This PR performs the following changes:
* Split `ScoreScriptUtilsTests` into `DenseVectorFunctionTests` and
`SparseVectorFunctionTests`. This will make it easier to delete all sparse
vector function tests once we remove support on 8.x.
* As much as possible, break up the large test methods into individual tests
for each vector function (`cosineSimilarity`, `l2norm`, etc.).
Previously the functions accepted a doc values reference, whereas they now
accept the name of the vector field. Here's an example of how a vector function
was called before and after the change.
```
Before: cosineSimilarity(params.query_vector, doc['field'])
After: cosineSimilarity(params.query_vector, 'field')
```
This seems more intuitive, since we don't allow direct access to vector doc
values and the the meaning of `doc['field']` is unclear.
The PR makes the following changes (broken into distinct commits):
* Add new function signatures of the form `function(params.query_vector,
'field')` and deprecates the old ones. Because Painless doesn't allow two
methods with the same name and number of arguments, we allow a generic `Object`
to be passed in to the function and decide on the behavior through an
`instanceof` check.
* Refactor the class bindings so that the document field is passed to the
constructor instead of the instance method. This allows us to avoid retrieving
the vector doc values on every function invocation, which gives a tiny speed-up
in benchmarks.
Note that this PR adds new signatures for the sparse vector functions too, even
though sparse vectors are deprecated. It seemed simplest to understand (for both
us and users) to keep everything symmetric between dense and sparse vectors.
We have not seen much adoption of this experimental field type, and don't see a
clear use case as it's currently designed. This PR deprecates the field type in
7.x. It will be removed from 8.0 in a follow-up PR.
XPackPlugin holds data in statics and can only be initialized once. This
caused tests to fail primarily when running with a low max-workers.
Replaced usages with the LocalStateCompositeXPackPlugin, which handles
this properly for testing.
This PR merges the `vectors-optimize-brute-force` feature branch, which makes
the following changes to how vector functions are computed:
* Precompute the L2 norm of each vector at indexing time. (#45390)
* Switch to ByteBuffer for vector encoding. (#45936)
* Decode vectors and while computing the vector function. (#46103)
* Use an array instead of a List for the query vector. (#46155)
* Precompute the normalized query vector when using cosine similarity. (#46190)
Co-authored-by: Mayya Sharipova <mayya.sharipova@elastic.co>
Currently, when using script_score functions like cosineSimilarity, the query
vector is treated as an array of doubles. Since the stored document vectors use
floats, it seems like the least surprising behavior for the query vectors to
also be float arrays.
In addition to improving consistency, this change may help with some
optimizations we have been considering around vector dot product.
Currently when a document misses a vector value, vector function
returns 0 as a score for this document. We think this is incorrect
behaviour.
With this change, an error will be thrown if vector functions are
used with docs that are missing vector doc values.
Also VectorScriptDocValues is modified to allow size() function,
which can be used to check if a document has a value for the
vector field.
Typically, dense vectors of both documents and queries must have the same
number of dimensions. Different number of dimensions among documents
or query vector indicate an error. This PR enforces that all vectors
for the same field have the same number of dimensions. It also enforces
that query vectors have the same number of dimensions.
Alan Woodward
Alan Woodward
Rene Groeschke
Julie Tibshirani
Mark Tozzi
William Brafford
Ryan Ernst
Jason Tedor
Zachary Tong
Nik Everett
Mayya Sharipova
Rory Hunter
Henning Andersen