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Merge branch '6.4' of github.com:elastic/elasticsearch into 6.4
2 parents 2677d64 + 0411f86 commit 925b224

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buildSrc/version.properties

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@@ -1,4 +1,4 @@
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elasticsearch = 6.4.2
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elasticsearch = 6.4.3
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lucene = 7.4.0
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# optional dependencies

client/rest-high-level/src/main/java/org/elasticsearch/client/IngestClient.java

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import org.elasticsearch.action.ingest.WritePipelineResponse;
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import java.io.IOException;
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import java.util.Collections;
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import static java.util.Collections.emptySet;
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@@ -83,7 +84,7 @@ public void putPipelineAsync(PutPipelineRequest request, RequestOptions options,
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*/
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public GetPipelineResponse getPipeline(GetPipelineRequest request, RequestOptions options) throws IOException {
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return restHighLevelClient.performRequestAndParseEntity( request, RequestConverters::getPipeline, options,
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GetPipelineResponse::fromXContent, emptySet());
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GetPipelineResponse::fromXContent, Collections.singleton(404));
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}
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/**
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*/
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public void getPipelineAsync(GetPipelineRequest request, RequestOptions options, ActionListener<GetPipelineResponse> listener) {
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restHighLevelClient.performRequestAsyncAndParseEntity( request, RequestConverters::getPipeline, options,
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GetPipelineResponse::fromXContent, listener, emptySet());
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GetPipelineResponse::fromXContent, listener, Collections.singleton(404));
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}
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/**

client/rest-high-level/src/test/java/org/elasticsearch/client/ESRestHighLevelClientTestCase.java

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import org.elasticsearch.common.settings.Settings;
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import org.elasticsearch.common.xcontent.XContentBuilder;
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import org.elasticsearch.common.xcontent.XContentType;
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import org.elasticsearch.core.internal.io.IOUtils;
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import org.elasticsearch.ingest.Pipeline;
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import org.elasticsearch.test.rest.ESRestTestCase;
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import org.junit.AfterClass;
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@AfterClass
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public static void cleanupClient() throws IOException {
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restHighLevelClient.close();
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IOUtils.close(restHighLevelClient);
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restHighLevelClient = null;
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}
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client/rest-high-level/src/test/java/org/elasticsearch/client/IngestClientIT.java

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assertEquals(expectedConfig.getConfigAsMap(), response.pipelines().get(0).getConfigAsMap());
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}
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public void testGetNonexistentPipeline() throws IOException {
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String id = "nonexistent_pipeline_id";
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GetPipelineRequest request = new GetPipelineRequest(id);
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GetPipelineResponse response =
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execute(request, highLevelClient().ingest()::getPipeline, highLevelClient().ingest()::getPipelineAsync);
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assertFalse(response.isFound());
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}
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public void testDeletePipeline() throws IOException {
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String id = "some_pipeline_id";
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{

docs/Versions.asciidoc

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:version: 6.4.0
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:version: 6.4.2
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:major-version: 6.x
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:lucene_version: 7.4.0
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:lucene_version_path: 7_4_0

docs/build.gradle

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exclude 'reference/rollup/apis/delete-job.asciidoc'
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exclude 'reference/rollup/apis/get-job.asciidoc'
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exclude 'reference/rollup/apis/rollup-caps.asciidoc'
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exclude 'reference/graph/explore.asciidoc'
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}
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listSnippets.docs = buildRestTests.docs

docs/plugins/integrations.asciidoc

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* https://github.com/jprante/elasticsearch-jdbc[JDBC importer]:
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The Java Database Connection (JDBC) importer allows to fetch data from JDBC sources for indexing into Elasticsearch (by Jörg Prante)
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* https://github.com/reachkrishnaraj/kafka-elasticsearch-standalone-consumer/tree/branch2.0[Kafka Standalone Consumer(Indexer)]:
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Kafka Standalone Consumer [Indexer] will read messages from Kafka in batches, processes(as implemented) and bulk-indexes them into Elasticsearch. Flexible and scalable. More documentation in above GitHub repo's Wiki.(Please use branch 2.0)!
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* https://github.com/BigDataDevs/kafka-elasticsearch-consumer [Kafka Standalone Consumer(Indexer)]:
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Kafka Standalone Consumer [Indexer] will read messages from Kafka in batches, processes(as implemented) and bulk-indexes them into Elasticsearch. Flexible and scalable. More documentation in above GitHub repo's Wiki.
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* https://github.com/ozlerhakan/mongolastic[Mongolastic]:
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A tool that clones data from Elasticsearch to MongoDB and vice versa

docs/reference/aggregations/bucket/composite-aggregation.asciidoc

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Note that fractional time values are not supported, but you can address this by shifting to another
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time unit (e.g., `1.5h` could instead be specified as `90m`).
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====== Format
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*Format*
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Internally, a date is represented as a 64 bit number representing a timestamp in milliseconds-since-the-epoch.
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These timestamps are returned as the bucket keys. It is possible to return a formatted date string instead using
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<1> Supports expressive date <<date-format-pattern,format pattern>>
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====== Time Zone
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*Time Zone*
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Date-times are stored in Elasticsearch in UTC. By default, all bucketing and
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rounding is also done in UTC. The `time_zone` parameter can be used to indicate

docs/reference/aggregations/bucket/terms-aggregation.asciidoc

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"aggs" : {
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"genres" : {
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"terms" : {
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"field" : "gender",
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"field" : "genre",
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"script" : {
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"source" : "'Genre: ' +_value",
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"lang" : "painless"

docs/reference/analysis/analyzers/custom-analyzer.asciidoc

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"analysis": {
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"analyzer": {
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"my_custom_analyzer": {
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"type": "custom",
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"type": "custom", <1>
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"tokenizer": "standard",
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"char_filter": [
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"html_strip"
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--------------------------------
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// CONSOLE
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<1> Setting `type` to `custom` tells Elasticsearch that we are defining a custom analyzer.
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Compare this to how <<configuring-analyzers,built-in analyzers can be configured>>:
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`type` will be set to the name of the built-in analyzer, like
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<<analysis-standard-analyzer,`standard`>> or <<analysis-simple-analyzer,`simple`>>.
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/////////////////////
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[source,js]

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