Elasticsearch accepts multiple content-type formats, hence scripts can be stored/provided in json, yaml, cbor or smile. Yet the format that should be used internally is json. This is a problem mainly around search templates, as they only support json out of the four content-types, so instead of maintaining the content-type of the request we should rather convert the scripts/templates to json.
Binary formats were not previously supported. If you stored a template in yaml format, you'd get back an error "No encoder found for MIME type [application/yaml]" when trying to execute it. With this commit the request content-type is independent from the template, which always gets converted to json internally. That is transparent to users and doesn't affect the content type of the response obtained when executing the template.
Both PRs below have been backported to 5.4 such that we can enable
BWC tests of this feature as well as remove version dependend serialization
for search request / responses.
Relates to #23288
Relates to #23253
* Make document write requests immutable
Previously, write requests were mutated at the
transport level to update request version, version type
and sequence no before replication.
Now that all write requests go through the shard bulk
transport action, we can use the primary response stored
in item level bulk requests to pass the updated version,
seqence no. to replicas.
* incorporate feedback
* minor cleanup
* Add bwc test to ensure correct index version propagates to replica
* Fix bwc for propagating write operation versions
* Add assertion on replica request version type
* fix tests using internal version type for replica op
* Fix assertions to assert version type in replica and recovery
* add bwc tests for version checks in concurrent indexing
* incorporate feedback
Fixes Painless to properly implement scripts that return primitives
and void. Adds some simple tests that we emit sane opcodes and some
other tests that we implement primitives as expected.
Mostly this is just a fix following up from #22983 but there is one
thing I did really worth talking about, I think. So, before this script
Painless scripts could only ever return Object and they did would always
return null for paths that didn't return any values. Now that they
can return primitives the question is "what should Painless return
from paths that don't return any values?" And I answered that with
"whatever the JLS default value is". So 0/0L/0f/0d/false.
The assertion that if there are buffered aggs at least one incremental
reduce phase should have happened doens't hold if there are shard failure.
This commit removes this assertion.
Relates to #23288
Generalizes three previously hard coded things in painless into
generic concepts:
1. The "main method" is no longer hardcoded to:
```
public abstract Object execute(Map<String, Object> params,
Scorer scorer, LeafDocLookup doc, Object value);
```
Instead Painless's compiler takes an interface and implements it. It looks like:
```
public interface SomeScript {
// Argument names we expose to Painless scripts
String[] ARGUMENTS = new String[] {"a", "b"};
// Method implemented by Painless script. Must be named execute but can have any parameters or return any value.
Object execute(String a, int b);
// Is the "a" argument used by the script?
boolean uses$a();
}
SomeScript script = scriptEngine.compile(SomeScript.class, null, "the_script_here", emptyMap());
Object result = script.execute("a", 1);
```
`PainlessScriptEngine` now compiles all scripts to the new
`GenericElasticsearchScript` interface by default for compatibility
with the rest of Elasticsearch until it is able to use this new
ability.
2. `_score` and `ctx` are no longer hardcoded to be extracted from
`#score` and `params` respectively. Instead Painless's default
implementation of Elasticsearch scripts uses the `uses$_score` and
`uses$ctx` methods to determine if it is used and gives them
dummy values if they are not used.
3. Throwing the `ScriptException` is now handled by the Painless
script itself. That way Painless doesn't have to leak the metadata
that is required to build the fancy stack trace. And all painless scripts
get the fancy stack trace.
In #23253 we added an the ability to incrementally reduce search results.
This change exposes the parameter to control the batch since and therefore
the memory consumption of a large search request.
InternalTopHits uses "==" to compare hit scores and fails when score is NaN.
This commit changes the comparaison to always use Double.compare.
Relates #23253
We can and should randomly reduce down to a single result before
we passing the aggs to the final reduce. This commit changes the logic
to do that and ensures we don't trip the assertions the previous imple tripped.
Relates to #23253
Previously we calculated Netty' receive predictor size for HTTP and transport
traffic based on available memory and worker nodes. This resulted in a receive
predictor size between 64kb and 512kb. In our benchmarks this leads to increased
GC pressure.
With this commit we set Netty's receive predictor size to 32kb. This value is in
a sweet spot between heap memory waste (-> GC pressure) and effect on request
metrics (achieved throughput and latency numbers).
Closes#23185
Today all query results are buffered up until we received responses of
all shards. This can hold on to a significant amount of memory if the number of
shards is large. This commit adds a first step towards incrementally reducing
aggregations results if a, per search request, configurable amount of responses
are received. If enough query results have been received and buffered all so-far
received aggregation responses will be reduced and released to be GCed.
In the packaging tests we make some requests to Elasticsearch as part of
the tests. These requests were not setting the content-type header. This
commit addresses this.
In the packaging tests we make some requests to Elasticsearch as part of
the tests. These requests were not setting the content-type header. This
commit addresses this.
Today, the relationship between Lucene and the translog is rather
simple: every document not in Lucene is guaranteed to be in the
translog. We need a stronger guarantee from the translog though, namely
that it can replay all operations after a certain sequence number. For
this to be possible, the translog has to made sequence-number aware. As
a first step, we introduce the min and max sequence numbers into the
translog so that each generation knows the possible range of operations
contained in the generation. This will enable future work to keep around
all generations containing operations after a certain sequence number
(e.g., the global checkpoint).
Relates #22822
A follow up to #23202, this adds parsing from xContent and tests to the four Suggestion implementations
and the top level suggest element to be used later when parsing the entire SearchResponse.
This commit cleans up some parsing tests added from the High Level Rest Client: IndexResponseTests, DeleteResponseTests, UpdateResponseTests, BulkItemResponseTests.
These tests are now more uniform with the others test-from-to-XContent tests we have, they now shuffle the XContent fields before parsing, the asserting method for parsed objects does not used a Map<String, Object> anymore, and buggy equals/hasCode methods in ShardInfo and ShardInfo.Failure have been removed.
This commit enforces the requirement of Content-Type for the REST layer and removes the deprecated methods in transport
requests and their usages.
While doing this, it turns out that there are many places where *Entity classes are used from the apache http client
libraries and many of these usages did not specify the content type. The methods that do not specify a content type
explicitly have been added to forbidden apis to prevent more of these from entering our code base.
Relates #19388
The elastic images used for testing different systems now have java
installed in the base image. This commit removes the installation of
java, which should make the packagingTest runs more stable, as they will
not depend on flaky system repository mirrors.
javanna
Simon Willnauer
Tanguy Leroux
Christopher Best
Alexander Reelsen
mms-programming
Areek Zillur
Nik Everett
Martijn van Groningen
Jack Conradson
Jim Ferenczi
Daniel Mitterdorfer
Martin Scholz
Jason Tedor
Glen Smith
Christoph Büscher
Ryan Ernst
Jay Modi
Adrien Grand
Yuhao Bi