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
This commit adds an optional field, `description`, to all ingest processors
so that users can explain the purpose of the specific processor instance.
Closes#56000.
This commit introduces an optimization for inline scripts.
It keeps the compiled ingest script that the ScriptProcessor.Factory
has been creating for validation purposes. Previously, the Script Service's
cache was leveraged because it was the best way to handle caching of both
stored and inline scripts. Since inline scripts are so widely used in
Ingest Node, it is probably best to ensure we are using the pre-compiled version
from the beginning.
* 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
Backport of #57870 to 7.x branch.
This change now also copies the op_type from the reindex request's destination index request to the actual index request being used in the bulk request.
For ensuring no document exists, the op_type create doesn't need to be copied, since Versions.MATCH_DELETED will copied from the 'mainRequest.getDestination().version()'.
The `version()` method on IndexRequest only returns Versions.MATCH_DELETED if op_type=create and no specific version has been specified.
However in order to be able to index into a data stream, the op_type must be create. So in order to support that the op_type must be copied from the reindex request's destination index request to the actual index request being used in the bulk request.
Relates to #53100 and #57788
Reworks the `parent` and `child` aggregation are not at the top level
using the optimization from #55873. Instead of wrapping all
non-top-level `parent` and `child` aggregators we now handle being a
child aggregator in the aggregator, specifically by adding recording
which global ordinals show up in the parent and then checking if they
match the child.
Adds assertions to Netty to make sure that its threads are not polluted by thread contexts (and
also that thread contexts are not leaked). Moves the ClusterApplierService to use the system
context (same as we do for MasterService), which allows to remove a hack from
TemplateUgradeService and makes it clearer that applying CS updates is fully executing under
system context.
When Joni, the regex engine that powers grok emits a warning it
does so by default to System.err. System.err logs are all bucketed
together in the server log at WARN level. When Joni emits a warning,
it can be extremely verbose, logging a message for each execution
again that pattern. For ingest node that means for every document
that is run that through Grok. Fortunately, Joni provides a call
back hook to push these warnings to a custom location.
This commit implements Joni's callback hook to push the Joni warning
to the Elasticsearch server logger (logger.org.elasticsearch.ingest.common.GrokProcessor)
at debug level. Generally these warning indicate a possible issue with
the regular expression and upon creation of the Grok processor will
do a "test run" of the expression and log the result (if any) at WARN
level. This WARN level log should only occur on pipeline creation which
is a much lower frequency then every document.
Additionally, the documentation is updated with instructions for how
to set the logger to debug level.
Allow for optimistic concurrency control during ingest by checking the
sequence number and primary term. This is accomplished by defining
_if_seq_no and _if_primary_term in the pipeline, similarly to _version
and _version_type.
Closes#41255
Co-authored-by: Maria Ralli <mariai.ralli@gmail.com>
Adds assertions to Netty to make sure that its threads are not polluted by thread contexts (and
also that thread contexts are not leaked). Moves the ClusterApplierService to use the system
context (same as we do for MasterService), which allows to remove a hack from
TemplateUgradeService and makes it clearer that applying CS updates is fully executing under
system context.
Before to determine if a field is meta-field, a static method of MapperService
isMetadataField was used. This method was using an outdated static list
of meta-fields.
This PR instead changes this method to the instance method that
is also aware of meta-fields in all registered plugins.
Related #38373, #41656Closes#24422
Follow up to #56961:
We can be a little more efficient than just serializing at the IO loop by serializing
only when we flush to a channel. This has the advantage that we don't serialize a long
queue of messages for a channel that isn't writable for a longer period of time (unstable network,
actually writing large volumes of data, etc.).
Also, this further reduces the time for which we hold on to the write buffer for a message,
making allocations because of an empty page cache recycler pool less likely.
Pulls the way that the `ParentJoinAggregator` collects global ordinals
into a strategy object so it is a little simpler to reason about and
it'll be simpler to save memory by removing `asMultiBucketAggregator` in
the future.
Relates to #56487
Almost every outbound message is serialized to buffers of 16k pagesize.
We were serializing these messages off the IO loop (and retaining the concrete message
instance as well) and would then enqueue it on the IO loop to be dealt with as soon as the
channel is ready.
1. This would cause buffers to be held onto for longer than necessary, causing less reuse on average.
2. If a channel was slow for some reason, not only would concrete message instances queue up for it, but also 16k of buffers would be reserved for each message until it would be written+flushed physically.
With this change, the serialization happens on the event loop which effectively limits the number of buffers that `N` IO-threads will ever use so long as messages are small and channels writable.
Also, this change dereferences the reference to the concrete outbound message as soon as it has been serialized to save some more on GC.
This reduces the GC time for a default PMC run by about 50% in experiments (3 nodes, 2G heap each, loopback ... obvious caveat is that GC isn't that heavy in the first place with recent changes but still a measurable gain).
I also expect it to be helpful for master node stability by causing less of a spike if master is e.g. hit by a large number of requests that are processed batched (e.g. shard snapshot status updates) and responded to in a short time frame all at once.
Obviously, the downside to this change is that it introduces more latency on the IO loop for the serialization. But since we read all of these messages on the IO loop as well I don't see it as much of a qualitative change really and the more predictable buffer use seems much more valuable relatively.
Previously we'd get a `ClassCastException` when you tried to use
`numeric_type` on `scaled_float`. Oops! This cleans up the CCE and moves
some code around so the casting actually works.
This commit adds support for rules with multiple tokens on LHS, also
known as "contraction rules", into stemmer override token
filter. Contraction rules are handy into translating multiple
inflected words into the same root form. One side effect of this change is
that it brings stemmer override rules format closer to synonym rules
format so that it makes it easier to translate one into another.
This change also makes stemmer override rules parser more strict so
that it should catch more errors which were previously accepted.
Closes#56113
When the parameter `max_docs` is less than `slices` in update_by_query,
delete_by_query or reindex API, `max_docs ` is set to 0 and we throw an
action_request_validation_exception with confused error message:
"maxDocs should be greater than 0...".
This change checks that whether `max_docs` is less than `slices` and
throw an illegal_argument_exception with clear message.
Relates to #52786.
Co-authored-by: bellengao <gbl_long@163.com>
When we had multiple mapping types, an update to a field in one type had to be
propagated to the same field in all other types. This was done using the
Mapper.updateFieldType() method, called at the end of a merge. However, now
that we only have a single type per index, this method is unnecessary and can
be removed.
Relates to #41059
Backport of #56986
We don't need to hold on to the request body past the beginning of sending
the response. There is no need to keep a reference to it until after the response
has been sent fully and we can eagerly release it here.
Note, this can be optimized further to release the contents even earlier but for now
this is an easy increment to saving some memory on the IO pool.
* Update DeprecationMap to DynamicMap (#56149)
This renames DeprecationMap to DynamicMap, and changes the deprecation
messages Map to accept a Map of String (keys) to Functions (updated values)
instead. This creates more flexibility in either logging or updating values from
params within a script. This change is required to fix (#52103) in a future PR.
* Fix Source Return Bug in Scripting (#56831)
This change ensures that when a user returns _source directly no matter where
accessed within scripting, the value is a Map of the converted source as
opposed to a SourceLookup.
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
Elasticsearch requires that a HttpRequest abstraction be implemented
by http modules before server processing. This abstraction controls when
underlying resources are released. This commit moves this abstraction to
be created immediately after content aggregation. This change will
enable follow-up work including moving Cors logic into the server
package and tracking bytes as they are aggregated from the network
level.
In most cases we are seeing a `PooledHeapByteBuf` here now. No need to
redundantly create an new `ByteBuffer` and single element array for it
here when we can just directly unwrap its internal `byte[]`.
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.
This is another part of the breakup of the massive BuildPlugin. This PR
moves the code for configuring publications to a separate plugin. Most
of the time these publications are jar files, but this also supports the
zip publication we have for integ tests.
We never do any file IO or other blocking work on the transport threads
so no tangible benefit can be derived from using more threads than CPUs
for IO.
There are however significant downsides to using more threads than necessary
with Netty in particular. Since we use the default setting for
`io.netty.allocator.useCacheForAllThreads` which is `true` we end up
using up to `16MB` of thread local buffer cache for each transport thread.
Meaning we potentially waste CPUs * 16MB of heap for unnecessary IO threads in addition to obvious inefficiencies of artificially adding extra context switches.
This PR proposes to use `IndexSortSortedNumericDocValuesRangeQuery` when
possible to speed up certain range queries. Points-based queries are already
very efficient, the only time this query makes a difference is when the range
matches a large number of documents.
Relates to #48665.
If a conditional is added to a processor, and that processor fails, and
that processor has an on_failure handler, the full trace of all of the
executed processors may not be displayed in simulate verbose. The
information is correct, but misses displaying some of the steps used
to get there.
This happens because a processor that is conditional processor is a
wrapper around the real processor and a processor with an on_failure
handler is also a wrapper around the processor(s). When decorating for
simulation we treat compound processor specially, but if a compound processor
is wrapped by a conditional processor that compound processor's processors
can be missed for decoration resulting in the missing displayed steps.
The fix to this is to treat the conditional processor specially and
explicitly seperate it from the processor it is wrapping. This requires
us to keep track of 2 processors a possible conditional processor and
the actual processor it may be wrapping.
related: #56004
Currently Elasticsearch creates independent event loop groups for each
transport (http and internal) transport type. This is unnecessary and
can lead to contention when different threads access shared resources
(ex: allocators). This commit moves to a model where, by default, the
event loops are shared between the transports. The previous behavior can
be attained by specifically setting the http worker count.
Right now all implementations of the `terms` agg allocate a new
`Aggregator` per bucket. This uses a bunch of memory. Exactly how much
isn't clear but each `Aggregator` ends up making its own objects to read
doc values which have non-trivial buffers. And it forces all of it
sub-aggregations to do the same. We allocate a new `Aggregator` per
bucket for two reasons:
1. We didn't have an appropriate data structure to track the
sub-ordinals of each parent bucket.
2. You can only make a single call to `runDeferredCollections(long...)`
per `Aggregator` which was the only way to delay collection of
sub-aggregations.
This change switches the method that builds aggregation results from
building them one at a time to building all of the results for the
entire aggregator at the same time.
It also adds a fairly simplistic data structure to track the sub-ordinals
for `long`-keyed buckets.
It uses both of those to power numeric `terms` aggregations and removes
the per-bucket allocation of their `Aggregator`. This fairly
substantially reduces memory consumption of numeric `terms` aggregations
that are not the "top level", especially when those aggregations contain
many sub-aggregations. It also is a pretty big speed up, especially when
the aggregation is under a non-selective aggregation like
the `date_histogram`.
I picked numeric `terms` aggregations because those have the simplest
implementation. At least, I could kind of fit it in my head. And I
haven't fully understood the "bytes"-based terms aggregations, but I
imagine I'll be able to make similar optimizations to them in follow up
changes.
Another Jackson release is available. There are some CVEs addressed,
none of which impact us, but since we can now bump Jackson easily, let
us move along with the train to avoid the false positives from security
scanners.
`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.)
Backport of #56034.
Move includeDataStream flag from an IndicesOptions to IndexNameExpressionResolver.Context
as a dedicated field that callers to IndexNameExpressionResolver can set.
Also alter indices stats api to support data streams.
The rollover api uses this api and otherwise rolling over data stream does no longer work.
Relates to #53100
Alan Woodward
Tal Levy
Dan Hermann
Rene Groeschke
Martijn van Groningen
Mark Tozzi
Nik Everett
Yannick Welsch
Jake Landis
Mayya Sharipova
Tanguy Leroux
Armin Braun
Tomasz Elendt
Henning Andersen
Lee Hinman
Jack Conradson
markharwood
Andrei Balici
Tim Brooks
Ryan Ernst
Julie Tibshirani
Ignacio Vera
Mark Vieira
Jason Tedor
Nhat Nguyen