Requesting a million hits, or page 100,000 is always a bad idea, but users
may not be aware of this. This adds a per-index limit on the maximum size +
from that can be requested which defaults to 10,000.
This should not interfere with deep-scrolling.
Closes#9311
* Dropped ScoreType in favour of Lucene's ScoreMode
* Removed `score_type` option from `has_child` and `has_parent` queries in favour for the already existing `score_mode` option.
* Removed the score mode `sum` in favour for the already existing `total` score mode. (`sum` doesn't exist in Lucene's ScoreMode class)
* If `max_children` is set to `0` it now really means that zero children are allowed to match.
Allocation filtering by IP only works today using the node host address. But in some cases, you might want to filter using the publish address which could be different.
Previously the parser could take any Term Vectors request, but this would be
not the case of the builder which would still use MultiGetRequest.Item. This
introduces a new Item class which is used by both the builder and parser.
Beyond that the rest is mostly cleanups such as:
1) Deprecating the ignoreLike methods, in favor to using unlike.
2) Deprecating and renaming MoreLikeThisBuilder#addItem to addLikeItem.
3) Ordering the methods of MoreLikeThisBuilder more logically.
This change is needed for the upcoming query refactoring of MLT.
Closes#13372
This pipeline will calculate percentiles over a set of sibling buckets. This is an exact
implementation, meaning it needs to cache a copy of the series in memory and sort it to determine
the percentiles.
This comes with a few limitations: to prevent serializing data around, only the requested percentiles
are calculated (unlike the TDigest version, which allows the java API to ask for any percentile).
It also needs to store the data in-memory, resulting in some overhead if the requested series is
very large.
Until now we had a cloud-aws plugin which is providing 2 disctinct features:
* discovery on EC2
* snapshot/restore on S3
This commit splits the plugin by feature so people can use either one or the other or both features.
Doc is updated accordingly.
The shaded version of elasticsearch was built at the very beginning to avoid dependency conflicts in a specific case where:
* People use elasticsearch from Java
* People needs to embed elasticsearch jar within their own application (as it's today the only way to get a `TransportClient`)
* People also embed in their application another (most of the time older) version of dependency we are using for elasticsearch, such as: Guava, Joda, Jackson...
This conflict issue can be solved within the projects themselves by either upgrade the dependency version and use the one provided by elasticsearch or by shading elasticsearch project and relocating some conflicting packages.
Example
-------
As an example, let's say you want to use within your project `Joda 2.1` but elasticsearch `2.0.0-beta1` provides `Joda 2.8`.
Let's say you also want to run all that with shield plugin.
Create a new maven project or module with:
```xml
<groupId>fr.pilato.elasticsearch.test</groupId>
<artifactId>es-shaded</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<elasticsearch.version>2.0.0-beta1</elasticsearch.version>
</properties>
<dependencies>
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch</artifactId>
<version>${elasticsearch.version}</version>
</dependency>
<dependency>
<groupId>org.elasticsearch.plugin</groupId>
<artifactId>shield</artifactId>
<version>${elasticsearch.version}</version>
</dependency>
</dependencies>
```
And now shade and relocate all packages which conflicts with your own application:
```xml
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<version>2.4.1</version>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<relocations>
<relocation>
<pattern>org.joda</pattern>
<shadedPattern>fr.pilato.thirdparty.joda</shadedPattern>
</relocation>
</relocations>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
```
You can create now a shaded version of elasticsearch + shield by running `mvn clean install`.
In your project, you can now depend on:
```xml
<dependency>
<groupId>fr.pilato.elasticsearch.test</groupId>
<artifactId>es-shaded</artifactId>
<version>1.0-SNAPSHOT</version>
</dependency>
<dependency>
<groupId>joda-time</groupId>
<artifactId>joda-time</artifactId>
<version>2.1</version>
</dependency>
```
Build then your TransportClient as usual:
```java
TransportClient client = TransportClient.builder()
.settings(Settings.builder()
.put("path.home", ".")
.put("shield.user", "username:password")
.put("plugin.types", "org.elasticsearch.shield.ShieldPlugin")
)
.build();
client.addTransportAddress(new InetSocketTransportAddress(new InetSocketAddress("localhost", 9300)));
// Index some data
client.prepareIndex("test", "doc", "1").setSource("foo", "bar").setRefresh(true).get();
SearchResponse searchResponse = client.prepareSearch("test").get();
```
If you want to use your own version of Joda, then import for example `org.joda.time.DateTime`. If you want to access to the shaded version (not recommended though), import `fr.pilato.thirdparty.joda.time.DateTime`.
You can run a simple test to make sure that both classes can live together within the same JVM:
```java
CodeSource codeSource = new org.joda.time.DateTime().getClass().getProtectionDomain().getCodeSource();
System.out.println("unshaded = " + codeSource);
codeSource = new fr.pilato.thirdparty.joda.time.DateTime().getClass().getProtectionDomain().getCodeSource();
System.out.println("shaded = " + codeSource);
```
It will print:
```
unshaded = (file:/path/to/joda-time-2.1.jar <no signer certificates>)
shaded = (file:/path/to/es-shaded-1.0-SNAPSHOT.jar <no signer certificates>)
```
This PR also removes fully-loaded module.
By the way, the project can now build with Maven 3.3.3 so we can relax a bit our maven policy.
Shaunak Kashyap
Boaz Leskes
Lee Hinman
Nik Everett
Shane Connelly
Alexander Pepper
Adrien Grand
Masaru Hasegawa
Paul Echeverri
Alexander Reelsen
Martijn van Groningen
Paul Echeverri
David Pilato
Alex Ksikes
Nicholas Knize
Ryan Ernst
Clinton Gormley
xuzha
Zachary Tong
Robert Muir
Britta Weber
Britta Weber
Lee Hinman
Colin Goodheart-Smithe
Robert Muir
Tanguy Leroux