This PR adds factory methods for the most common implementations:
* `SourceValueFetcher.identity` to pass through the source value untouched.
* `SourceValueFetcher.toString` to simply convert the source value to a string.
When constructing a value fetcher, the 'parsesArrayValue' flag must match
`FieldMapper#parsesArrayValue`. However there is nothing in code or tests to
help enforce this.
This PR reworks the value fetcher constructors so that `parsesArrayValue` is
'false' by default. Just as for `FieldMapper#parsesArrayValue`, field types must
explicitly set it to true and ensure the behavior is covered by tests.
Follow-up to #62974.
An invalid void expression type from a null safe operator caused ClassFormatError for the script Map
x= ['0': 0]; x?.0 > 1. This change sets and propagates the correct expression type for the null safe
operator to be written out.
This PR adds deprecation warnings when accessing System Indices via the REST layer. At this time, these warnings are only enabled for Snapshot builds by default, to allow projects external to Elasticsearch additional time to adjust their access patterns.
Deprecation warnings will be triggered by all REST requests which access registered System Indices, except for purpose-specific APIs which access System Indices as an implementation detail a few specific APIs which will continue to allow access to system indices by default:
- `GET _cluster/health`
- `GET {index}/_recovery`
- `GET _cluster/allocation/explain`
- `GET _cluster/state`
- `POST _cluster/reroute`
- `GET {index}/_stats`
- `GET {index}/_segments`
- `GET {index}/_shard_stores`
- `GET _cat/[indices,aliases,health,recovery,shards,segments]`
Deprecation warnings for accessing system indices take the form:
```
this request accesses system indices: [.some_system_index], but in a future major version, direct access to system indices will be prevented by default
```
MapperService carries a lot of weight and is only used to determine if loading of field data for the id field is enabled, which can be done in a different way.
In #62509 we already plugged faster sequential access for stored fields in the fetch phase.
This PR now adds using the potentially better field reader also in SourceLookup.
Rally exeriments are showing that this speeds up e.g. when runtime fields that are using
"_source" are added e.g. via "docvalue_fields" or are used in queries or aggs.
Closes#62621
* Setting `script.painless.regex.enabled` has a new option,
`use-factor`, the default. This defaults to using regular
expressions but limiting the complexity of the regular
expressions.
In addition to `use-factor`, the setting can be `true`, as
before, which enables regular expressions without limiting them.
`false` totally disables regular expressions, which was the
old default.
* New setting `script.painless.regex.limit-factor`. This limits
regular expression complexity by limiting the number characters
a regular expression can consider based on input length.
The default is `6`, so a regular expression can consider
`6` * input length number of characters. With input
`foobarbaz` (length `9`), for example, the regular expression
can consider `54` (`6 * 9`) characters.
This reduces the impact of exponential backtracking in Java's
regular expression engine.
* add `@inject_constant` annotation to whitelist.
This annotation signals that a compiler settings will
be injected at the beginning of a whitelisted method.
The format is `argnum=settingname`:
`1=foo_setting 2=bar_setting`.
Argument numbers must start at one and must be sequential.
* Augment
`Pattern.split(CharSequence)`
`Pattern.split(CharSequence, int)`,
`Pattern.splitAsStream(CharSequence)`
`Pattern.matcher(CharSequence)`
to take the value of `script.painless.regex.limit-factor` as a
an injected parameter, limiting as explained above when this
setting is in use.
Fixes: #49873
Backport of: 93f29a4
This change makes Location a final member of IRNode as opposed to possibly changing it. This
ensures that all ir nodes have a Location for error information upon creation that cannot be updated
so each node can be tracked as where it came from originally.
We only ever use this with `XContentParser` no need to make it inline
worse by forcing the lambda and hence dynamic callsite here.
=> Extraced the exception formatting code path that is likely very cold
to a separate method and removed the lambda usage in hot loops by simplifying
the signature here.
For runtime fields, we will want to do all search-time interaction with
a field definition via a MappedFieldType, rather than a FieldMapper, to
avoid interfering with the logic of document parsing. Currently, fetching
values for runtime scripts and for building top hits responses need to
call a method on FieldMapper. This commit moves this method to
MappedFieldType, incidentally simplifying the current call sites and freeing
us up to implement runtime fields as pure MappedFieldType objects.
* Add System Indices check to AutoCreateIndex
By default, Elasticsearch auto-creates indices when a document is
submitted to a non-existent index. There is a setting that allows users
to disable this behavior. However, this setting should not apply to
system indices, so that Elasticsearch modules and plugins are able to
use auto-create behavior whether or not it is exposed to users.
This commit constructs the AutoCreateIndex object with a reference to
the SystemIndices object so that we bypass the check for the user-facing
autocreate setting when it's a system index that is being autocreated.
We also modify the logic in TransportBulkAction to make sure that if a
system index is included in a bulk request, we don't skip the
autocreation step.
Currently we read in 64KB blocks from the network. When TLS is not
enabled, these bytes are normally passed all the way to the application
layer (some exceptions: compression). For the HTTP layer this means that
these bytes can live throughout the entire lifecycle of an indexing
request.
The problem is that if the reads from the socket are small, this means
that 64KB buffers can be consumed by 1KB or smaller reads. If the socket
buffer or TCP buffer sizes are small, the leads to massive memory
waste. It has been identified as a major source of OOMs on coordinating
nodes as Elasticsearch easily exhausts the heap for these network bytes.
This commit resolves the problem by placing a handler after the TLS
handler to copy these bytes to a more appropriate buffer size as
necessary. This comes after TLS, because TLS is a framing layer which
often resolves this problem for us (the 64KB buffer will be decoded
into a more appropriate buffer size). However, this extra handler will
solve it for the non-TLS pipelines.
This adds the network property from the MaxMind Geo ASN database.
This enables analysis of IP data based on the subnets that MaxMind have
previously identified for ASN networks.
closes#60942
Co-authored-by: Peter Ansell <p_ansell@yahoo.com>
Unmute DeleteByQueryConcurrentTests
testConcurrentDeleteByQueriesOnDifferentDocs test.
LUCENE-9449 introduced a bug in sorting on _doc,
which resulted in failure of this test. As Lucene bug
has been fixed, this reenables the test.
Closes#62609
This converts RankFeatureFieldMapper, RankFeaturesFieldMapper,
SearchAsYouTypeFieldMapper and TokenCountFieldMapper to
parametrized forms. It also adds a TextParams utility class to core
containing functions that help declare text parameters - mainly shared
between SearchAsYouTypeFieldMapper and KeywordFieldMapper at
the moment, but it will come in handy when we convert TextFieldMapper
and friends.
Relates to #62988
Currently Netty will batch compression an entire HTTP response
regardless of its content size. It allocates a byte array at least of
the same size as the uncompressed content. This causes issues with our
attempts to remove humungous G1GC allocations. This commit resolves the
issue by split responses into 128KB chunks.
This has the side-effect of making large outbound HTTP responses that
are compressed be send as chunked transfer-encoding.
Currently we duplicate our specialized cors logic in all transport
plugins. This is unnecessary as it could be implemented in a single
place. This commit moves the logic to server. Additionally it fixes a
but where we are incorrectly closing http channels on early Cors
responses.
Introduce 64-bit unsigned long field type
This field type supports
- indexing of integer values from [0, 18446744073709551615]
- precise queries (term, range)
- precise sort and terms aggregations
- other aggregations are based on conversion of long values
to double and can be imprecise for large values.
Backport for #60050Closes#32434
This commit adds a mechanism to MapperTestCase that allows implementing
test classes to check that their parameters can be updated, or throw conflict
errors as advertised. Child classes override the registerParameters method
and tell the passed-in UpdateChecker class about their parameters. Simple
conflicts can be checked, using the existing minimal mappings as a base to
compare against, or alternatively a particular initial mapping can be provided
to check edge cases (eg, norms can be updated from true to false, but not
vice versa). Updates are registered with a predicate that checks that the update
has in fact been applied to the resulting FieldMapper.
Fixes#61631
Most of our field types have the same implementation for their `existsQuery` method which relies on doc_values if present, otherwise it queries norms if available or uses a term query against the _field_names meta field. This standard implementation is repeated in many different mappers.
There are field types that only query doc_values, because they always have them, and field types that always query _field_names, because they never have norms nor doc_values. We could apply the same standard logic to all of these field types as `MappedFieldType` has the knowledge about what data structures are available.
This commit introduces a standard implementation that does the right thing depending on the data structure that is available. With that only field types that require a different behaviour need to override the existsQuery method.
At the same time, this no longer forces subclasses to override `existsQuery`, which could be forgotten when needed. To address this we introduced a new test method in `MapperTestCase` that verifies the `existsQuery` being generated and its consistency with the available data structures.
* Make for each processor resistant to field modification (#62791)
This change provides consistent view of field that foreach processor is iterating over. That prevents it to go into infinite loop and put great pressure on the cluster.
Closes#62790
* fix compilation
This reworks the code around grok's built-in patterns to name things
more like the rest of the code. Its not a big deal, but I'm just more
used to having `public static final` constants in SHOUTING_SNAKE_CASE.
The dense vector field is not aggregatable although it produces fielddata through its BinaryDocValuesField. It should pass up hasDocValues set to true to its parent class in its constructor, and return isAggregatable false. Same for the sparse vector field (only in 7.x).
This may not have consequences today, but it will be important once we try to share the same exists query implementation throughout all of the mappers with #57607.
Currently we log the NettyAllocator description when the netty plugin is
created. Unfortunately, this hits certain static fields in Netty which
triggers the settings of the number of CPU processors. This conflicts
with out Elasticsearch behavior to override this based on a setting.
This commit resolves the issue by logging after the processors have been
set.
Currently the netty pool chunk size defaults to 16MB. The number does
not play well with the G1GC which causes this to consume entire regions.
Additionally, we normally allocated arrays of size 64KB or less. This
means that Elasticsearch could handle a smaller pool chunk size to play
nicer with the G1GC.
Backports #61590 to 7.x
So far we don't allow metadata fields in the document _source. However, in the case of the _doc_count field mapper (#58339) we want to be able to set
This PR adds a method to the metadata field parsers that exposes if the field can be included in the document source or not.
This way each metadata field can configure if it can be included in the document _source
FetchSubPhase#getProcessor currently takes a SearchLookup parameter. This
however is only needed by a couple of subphases, and will almost certainly change in
future as we want to simplify how fetch phases retrieve values for individual hits.
To future-proof against further signature changes, this commit moves the SearchLookup
reference into FetchContext instead.
We currently pass a SearchContext around to share configuration among
FetchSubPhases. With the introduction of runtime fields, it would be useful
to start storing some state on this context to be shared between different
subphases (for example, stored fields or search lookups can be loaded lazily
but referred to by many different subphases). However, SearchContext is a
very large and unwieldy class, and adding more methods or state here feels
like a bridge too far.
This commit introduces a new FetchContext class that exposes only those
methods on SearchContext that are required for fetch phases. This reduces
the API surface area for fetch phases considerably, and should give us some
leeway to add further state.
This new snapshot contains the following JIRAs that we're interested in:
- [LUCENE-9525](https://issues.apache.org/jira/browse/LUCENE-9525)
Better handling of small documents. This should improve retrieval times
when documents are less than ~1kB.
- [LUCENE-9510](https://issues.apache.org/jira/browse/LUCENE-9510)
Faster flushes when index sorting is enabled by not compressing the
temporary files that store stored fields and term vectors.
This backport incorporates all the changes to improve compiler extensibility. The reason for this
backport is the changes are now required to support runtime fields.
This implements the `fields` API in `_search` for runtime fields using
doc values. Most of that implementation is stolen from the
`docvalue_fields` fetch sub-phase, just moved into the same API that the
`fields` API uses. At this point the `docvalue_fields` fetch phase looks
like a special case of the `fields` API.
While I was at it I moved the "which doc values sub-implementation
should I use for fetching?" question from a bunch of `instanceof`s to a
method on `LeafFieldData` so we can be much more flexible with what is
returned and we're not forced to extend certain classes just to make the
fetch phase happy.
Relates to #59332
Julie Tibshirani
Dan Hermann
Mayya Sharipova
Stuart Tettemer
Jack Conradson
Gordon Brown
Luca Cavanna
Christoph Büscher
Nhat Nguyen
Armin Braun
Alan Woodward
William Brafford
Tim Brooks
Jake Landis
Przemko Robakowski
Nik Everett
markharwood
David Roberts
Christos Soulios
Adrien Grand
Ignacio Vera