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Merge branch 'master' into feature/searchable-snapshots
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‎CONTRIBUTING.md

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -171,13 +171,13 @@ IntelliJ or Eclipse like describe above to use
171171
Elasticsearch typically uses singular nouns rather than plurals in URLs.
172172
For example:
173173

174-
/_ingest/pipline
175-
/_ingest/pipline/{id}
174+
/_ingest/pipeline
175+
/_ingest/pipeline/{id}
176176

177177
but not:
178178

179-
/_ingest/piplines
180-
/_ingest/piplines/{id}
179+
/_ingest/pipelines
180+
/_ingest/pipelines/{id}
181181

182182
You may find counterexamples, but new endpoints should use the singular
183183
form.

‎buildSrc/version.properties

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,5 +1,5 @@
11
elasticsearch = 8.0.0
2-
lucene = 8.5.0-snapshot-c4475920b08
2+
lucene = 8.5.0-snapshot-7f057455901
33

44
bundled_jdk_vendor = adoptopenjdk
55
bundled_jdk = 13.0.2+8

‎client/rest-high-level/src/main/java/org/elasticsearch/client/ml/dataframe/Classification.java

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -44,7 +44,7 @@ public static Builder builder(String dependentVariable) {
4444
static final ParseField LAMBDA = new ParseField("lambda");
4545
static final ParseField GAMMA = new ParseField("gamma");
4646
static final ParseField ETA = new ParseField("eta");
47-
static final ParseField MAXIMUM_NUMBER_TREES = new ParseField("maximum_number_trees");
47+
static final ParseField MAX_TREES = new ParseField("max_trees");
4848
static final ParseField FEATURE_BAG_FRACTION = new ParseField("feature_bag_fraction");
4949
static final ParseField NUM_TOP_FEATURE_IMPORTANCE_VALUES = new ParseField("num_top_feature_importance_values");
5050
static final ParseField PREDICTION_FIELD_NAME = new ParseField("prediction_field_name");
@@ -74,7 +74,7 @@ public static Builder builder(String dependentVariable) {
7474
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), LAMBDA);
7575
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), GAMMA);
7676
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), ETA);
77-
PARSER.declareInt(ConstructingObjectParser.optionalConstructorArg(), MAXIMUM_NUMBER_TREES);
77+
PARSER.declareInt(ConstructingObjectParser.optionalConstructorArg(), MAX_TREES);
7878
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), FEATURE_BAG_FRACTION);
7979
PARSER.declareInt(ConstructingObjectParser.optionalConstructorArg(), NUM_TOP_FEATURE_IMPORTANCE_VALUES);
8080
PARSER.declareString(ConstructingObjectParser.optionalConstructorArg(), PREDICTION_FIELD_NAME);
@@ -87,7 +87,7 @@ public static Builder builder(String dependentVariable) {
8787
private final Double lambda;
8888
private final Double gamma;
8989
private final Double eta;
90-
private final Integer maximumNumberTrees;
90+
private final Integer maxTrees;
9191
private final Double featureBagFraction;
9292
private final Integer numTopFeatureImportanceValues;
9393
private final String predictionFieldName;
@@ -96,14 +96,14 @@ public static Builder builder(String dependentVariable) {
9696
private final Long randomizeSeed;
9797

9898
private Classification(String dependentVariable, @Nullable Double lambda, @Nullable Double gamma, @Nullable Double eta,
99-
@Nullable Integer maximumNumberTrees, @Nullable Double featureBagFraction,
99+
@Nullable Integer maxTrees, @Nullable Double featureBagFraction,
100100
@Nullable Integer numTopFeatureImportanceValues, @Nullable String predictionFieldName,
101101
@Nullable Double trainingPercent, @Nullable Integer numTopClasses, @Nullable Long randomizeSeed) {
102102
this.dependentVariable = Objects.requireNonNull(dependentVariable);
103103
this.lambda = lambda;
104104
this.gamma = gamma;
105105
this.eta = eta;
106-
this.maximumNumberTrees = maximumNumberTrees;
106+
this.maxTrees = maxTrees;
107107
this.featureBagFraction = featureBagFraction;
108108
this.numTopFeatureImportanceValues = numTopFeatureImportanceValues;
109109
this.predictionFieldName = predictionFieldName;
@@ -133,8 +133,8 @@ public Double getEta() {
133133
return eta;
134134
}
135135

136-
public Integer getMaximumNumberTrees() {
137-
return maximumNumberTrees;
136+
public Integer getMaxTrees() {
137+
return maxTrees;
138138
}
139139

140140
public Double getFeatureBagFraction() {
@@ -174,8 +174,8 @@ public XContentBuilder toXContent(XContentBuilder builder, Params params) throws
174174
if (eta != null) {
175175
builder.field(ETA.getPreferredName(), eta);
176176
}
177-
if (maximumNumberTrees != null) {
178-
builder.field(MAXIMUM_NUMBER_TREES.getPreferredName(), maximumNumberTrees);
177+
if (maxTrees != null) {
178+
builder.field(MAX_TREES.getPreferredName(), maxTrees);
179179
}
180180
if (featureBagFraction != null) {
181181
builder.field(FEATURE_BAG_FRACTION.getPreferredName(), featureBagFraction);
@@ -201,7 +201,7 @@ public XContentBuilder toXContent(XContentBuilder builder, Params params) throws
201201

202202
@Override
203203
public int hashCode() {
204-
return Objects.hash(dependentVariable, lambda, gamma, eta, maximumNumberTrees, featureBagFraction, numTopFeatureImportanceValues,
204+
return Objects.hash(dependentVariable, lambda, gamma, eta, maxTrees, featureBagFraction, numTopFeatureImportanceValues,
205205
predictionFieldName, trainingPercent, randomizeSeed, numTopClasses);
206206
}
207207

@@ -214,7 +214,7 @@ public boolean equals(Object o) {
214214
&& Objects.equals(lambda, that.lambda)
215215
&& Objects.equals(gamma, that.gamma)
216216
&& Objects.equals(eta, that.eta)
217-
&& Objects.equals(maximumNumberTrees, that.maximumNumberTrees)
217+
&& Objects.equals(maxTrees, that.maxTrees)
218218
&& Objects.equals(featureBagFraction, that.featureBagFraction)
219219
&& Objects.equals(numTopFeatureImportanceValues, that.numTopFeatureImportanceValues)
220220
&& Objects.equals(predictionFieldName, that.predictionFieldName)
@@ -233,7 +233,7 @@ public static class Builder {
233233
private Double lambda;
234234
private Double gamma;
235235
private Double eta;
236-
private Integer maximumNumberTrees;
236+
private Integer maxTrees;
237237
private Double featureBagFraction;
238238
private Integer numTopFeatureImportanceValues;
239239
private String predictionFieldName;
@@ -260,8 +260,8 @@ public Builder setEta(Double eta) {
260260
return this;
261261
}
262262

263-
public Builder setMaximumNumberTrees(Integer maximumNumberTrees) {
264-
this.maximumNumberTrees = maximumNumberTrees;
263+
public Builder setMaxTrees(Integer maxTrees) {
264+
this.maxTrees = maxTrees;
265265
return this;
266266
}
267267

@@ -296,7 +296,7 @@ public Builder setNumTopClasses(Integer numTopClasses) {
296296
}
297297

298298
public Classification build() {
299-
return new Classification(dependentVariable, lambda, gamma, eta, maximumNumberTrees, featureBagFraction,
299+
return new Classification(dependentVariable, lambda, gamma, eta, maxTrees, featureBagFraction,
300300
numTopFeatureImportanceValues, predictionFieldName, trainingPercent, numTopClasses, randomizeSeed);
301301
}
302302
}

‎client/rest-high-level/src/main/java/org/elasticsearch/client/ml/dataframe/Regression.java

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -44,7 +44,7 @@ public static Builder builder(String dependentVariable) {
4444
static final ParseField LAMBDA = new ParseField("lambda");
4545
static final ParseField GAMMA = new ParseField("gamma");
4646
static final ParseField ETA = new ParseField("eta");
47-
static final ParseField MAXIMUM_NUMBER_TREES = new ParseField("maximum_number_trees");
47+
static final ParseField MAX_TREES = new ParseField("max_trees");
4848
static final ParseField FEATURE_BAG_FRACTION = new ParseField("feature_bag_fraction");
4949
static final ParseField NUM_TOP_FEATURE_IMPORTANCE_VALUES = new ParseField("num_top_feature_importance_values");
5050
static final ParseField PREDICTION_FIELD_NAME = new ParseField("prediction_field_name");
@@ -72,7 +72,7 @@ public static Builder builder(String dependentVariable) {
7272
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), LAMBDA);
7373
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), GAMMA);
7474
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), ETA);
75-
PARSER.declareInt(ConstructingObjectParser.optionalConstructorArg(), MAXIMUM_NUMBER_TREES);
75+
PARSER.declareInt(ConstructingObjectParser.optionalConstructorArg(), MAX_TREES);
7676
PARSER.declareDouble(ConstructingObjectParser.optionalConstructorArg(), FEATURE_BAG_FRACTION);
7777
PARSER.declareInt(ConstructingObjectParser.optionalConstructorArg(), NUM_TOP_FEATURE_IMPORTANCE_VALUES);
7878
PARSER.declareString(ConstructingObjectParser.optionalConstructorArg(), PREDICTION_FIELD_NAME);
@@ -84,22 +84,22 @@ public static Builder builder(String dependentVariable) {
8484
private final Double lambda;
8585
private final Double gamma;
8686
private final Double eta;
87-
private final Integer maximumNumberTrees;
87+
private final Integer maxTrees;
8888
private final Double featureBagFraction;
8989
private final Integer numTopFeatureImportanceValues;
9090
private final String predictionFieldName;
9191
private final Double trainingPercent;
9292
private final Long randomizeSeed;
9393

9494
private Regression(String dependentVariable, @Nullable Double lambda, @Nullable Double gamma, @Nullable Double eta,
95-
@Nullable Integer maximumNumberTrees, @Nullable Double featureBagFraction,
95+
@Nullable Integer maxTrees, @Nullable Double featureBagFraction,
9696
@Nullable Integer numTopFeatureImportanceValues, @Nullable String predictionFieldName,
9797
@Nullable Double trainingPercent, @Nullable Long randomizeSeed) {
9898
this.dependentVariable = Objects.requireNonNull(dependentVariable);
9999
this.lambda = lambda;
100100
this.gamma = gamma;
101101
this.eta = eta;
102-
this.maximumNumberTrees = maximumNumberTrees;
102+
this.maxTrees = maxTrees;
103103
this.featureBagFraction = featureBagFraction;
104104
this.numTopFeatureImportanceValues = numTopFeatureImportanceValues;
105105
this.predictionFieldName = predictionFieldName;
@@ -128,8 +128,8 @@ public Double getEta() {
128128
return eta;
129129
}
130130

131-
public Integer getMaximumNumberTrees() {
132-
return maximumNumberTrees;
131+
public Integer getMaxTrees() {
132+
return maxTrees;
133133
}
134134

135135
public Double getFeatureBagFraction() {
@@ -165,8 +165,8 @@ public XContentBuilder toXContent(XContentBuilder builder, Params params) throws
165165
if (eta != null) {
166166
builder.field(ETA.getPreferredName(), eta);
167167
}
168-
if (maximumNumberTrees != null) {
169-
builder.field(MAXIMUM_NUMBER_TREES.getPreferredName(), maximumNumberTrees);
168+
if (maxTrees != null) {
169+
builder.field(MAX_TREES.getPreferredName(), maxTrees);
170170
}
171171
if (featureBagFraction != null) {
172172
builder.field(FEATURE_BAG_FRACTION.getPreferredName(), featureBagFraction);
@@ -189,7 +189,7 @@ public XContentBuilder toXContent(XContentBuilder builder, Params params) throws
189189

190190
@Override
191191
public int hashCode() {
192-
return Objects.hash(dependentVariable, lambda, gamma, eta, maximumNumberTrees, featureBagFraction, numTopFeatureImportanceValues,
192+
return Objects.hash(dependentVariable, lambda, gamma, eta, maxTrees, featureBagFraction, numTopFeatureImportanceValues,
193193
predictionFieldName, trainingPercent, randomizeSeed);
194194
}
195195

@@ -202,7 +202,7 @@ public boolean equals(Object o) {
202202
&& Objects.equals(lambda, that.lambda)
203203
&& Objects.equals(gamma, that.gamma)
204204
&& Objects.equals(eta, that.eta)
205-
&& Objects.equals(maximumNumberTrees, that.maximumNumberTrees)
205+
&& Objects.equals(maxTrees, that.maxTrees)
206206
&& Objects.equals(featureBagFraction, that.featureBagFraction)
207207
&& Objects.equals(numTopFeatureImportanceValues, that.numTopFeatureImportanceValues)
208208
&& Objects.equals(predictionFieldName, that.predictionFieldName)
@@ -220,7 +220,7 @@ public static class Builder {
220220
private Double lambda;
221221
private Double gamma;
222222
private Double eta;
223-
private Integer maximumNumberTrees;
223+
private Integer maxTrees;
224224
private Double featureBagFraction;
225225
private Integer numTopFeatureImportanceValues;
226226
private String predictionFieldName;
@@ -246,8 +246,8 @@ public Builder setEta(Double eta) {
246246
return this;
247247
}
248248

249-
public Builder setMaximumNumberTrees(Integer maximumNumberTrees) {
250-
this.maximumNumberTrees = maximumNumberTrees;
249+
public Builder setMaxTrees(Integer maxTrees) {
250+
this.maxTrees = maxTrees;
251251
return this;
252252
}
253253

@@ -277,7 +277,7 @@ public Builder setRandomizeSeed(Long randomizeSeed) {
277277
}
278278

279279
public Regression build() {
280-
return new Regression(dependentVariable, lambda, gamma, eta, maximumNumberTrees, featureBagFraction,
280+
return new Regression(dependentVariable, lambda, gamma, eta, maxTrees, featureBagFraction,
281281
numTopFeatureImportanceValues, predictionFieldName, trainingPercent, randomizeSeed);
282282
}
283283
}

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

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1297,7 +1297,7 @@ public void testPutDataFrameAnalyticsConfig_GivenRegression() throws Exception {
12971297
.setLambda(1.0)
12981298
.setGamma(1.0)
12991299
.setEta(1.0)
1300-
.setMaximumNumberTrees(10)
1300+
.setMaxTrees(10)
13011301
.setFeatureBagFraction(0.5)
13021302
.setNumTopFeatureImportanceValues(3)
13031303
.build())
@@ -1340,7 +1340,7 @@ public void testPutDataFrameAnalyticsConfig_GivenClassification() throws Excepti
13401340
.setLambda(1.0)
13411341
.setGamma(1.0)
13421342
.setEta(1.0)
1343-
.setMaximumNumberTrees(10)
1343+
.setMaxTrees(10)
13441344
.setFeatureBagFraction(0.5)
13451345
.setNumTopFeatureImportanceValues(3)
13461346
.build())

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

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -2973,7 +2973,7 @@ public void testPutDataFrameAnalytics() throws Exception {
29732973
.setLambda(1.0) // <2>
29742974
.setGamma(5.5) // <3>
29752975
.setEta(5.5) // <4>
2976-
.setMaximumNumberTrees(50) // <5>
2976+
.setMaxTrees(50) // <5>
29772977
.setFeatureBagFraction(0.4) // <6>
29782978
.setNumTopFeatureImportanceValues(3) // <7>
29792979
.setPredictionFieldName("my_prediction_field_name") // <8>
@@ -2988,7 +2988,7 @@ public void testPutDataFrameAnalytics() throws Exception {
29882988
.setLambda(1.0) // <2>
29892989
.setGamma(5.5) // <3>
29902990
.setEta(5.5) // <4>
2991-
.setMaximumNumberTrees(50) // <5>
2991+
.setMaxTrees(50) // <5>
29922992
.setFeatureBagFraction(0.4) // <6>
29932993
.setNumTopFeatureImportanceValues(3) // <7>
29942994
.setPredictionFieldName("my_prediction_field_name") // <8>

‎client/rest-high-level/src/test/java/org/elasticsearch/client/ml/dataframe/ClassificationTests.java

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -30,7 +30,7 @@ public static Classification randomClassification() {
3030
.setLambda(randomBoolean() ? null : randomDoubleBetween(0.0, Double.MAX_VALUE, true))
3131
.setGamma(randomBoolean() ? null : randomDoubleBetween(0.0, Double.MAX_VALUE, true))
3232
.setEta(randomBoolean() ? null : randomDoubleBetween(0.001, 1.0, true))
33-
.setMaximumNumberTrees(randomBoolean() ? null : randomIntBetween(1, 2000))
33+
.setMaxTrees(randomBoolean() ? null : randomIntBetween(1, 2000))
3434
.setFeatureBagFraction(randomBoolean() ? null : randomDoubleBetween(0.0, 1.0, false))
3535
.setNumTopFeatureImportanceValues(randomBoolean() ? null : randomIntBetween(0, Integer.MAX_VALUE))
3636
.setPredictionFieldName(randomBoolean() ? null : randomAlphaOfLength(10))

‎client/rest-high-level/src/test/java/org/elasticsearch/client/ml/dataframe/RegressionTests.java

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -30,7 +30,7 @@ public static Regression randomRegression() {
3030
.setLambda(randomBoolean() ? null : randomDoubleBetween(0.0, Double.MAX_VALUE, true))
3131
.setGamma(randomBoolean() ? null : randomDoubleBetween(0.0, Double.MAX_VALUE, true))
3232
.setEta(randomBoolean() ? null : randomDoubleBetween(0.001, 1.0, true))
33-
.setMaximumNumberTrees(randomBoolean() ? null : randomIntBetween(1, 2000))
33+
.setMaxTrees(randomBoolean() ? null : randomIntBetween(1, 2000))
3434
.setFeatureBagFraction(randomBoolean() ? null : randomDoubleBetween(0.0, 1.0, false))
3535
.setNumTopFeatureImportanceValues(randomBoolean() ? null : randomIntBetween(0, Integer.MAX_VALUE))
3636
.setPredictionFieldName(randomBoolean() ? null : randomAlphaOfLength(10))

‎docs/plugins/integrations.asciidoc

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -145,8 +145,8 @@ releases 2.0 and later do not support rivers.
145145
* https://micronaut-projects.github.io/micronaut-elasticsearch/latest/guide/index.html[Micronaut Elasticsearch Integration]:
146146
Integration of Micronaut with Elasticsearch
147147

148-
* https://docs.streampipes.org/docs/user-guide-introduction[StreamPipes]:
149-
StreamPipes is a framework that enables users to work with data streams allowing to store data in Elasticsearch.
148+
* https://streampipes.apache.org[Apache StreamPipes]:
149+
StreamPipes is a framework that enables users to work with IoT data streams allowing to store data in Elasticsearch.
150150

151151
* https://metamodel.apache.org/[Apache MetaModel]:
152152
Providing a common interface for discovery, exploration of metadata and querying of different types of data sources.

‎docs/python/index.asciidoc

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -5,12 +5,12 @@
55
Official low-level client for Elasticsearch. Its goal is to provide common
66
ground for all Elasticsearch-related code in Python; because of this it tries
77
to be opinion-free and very extendable. The full documentation is available at
8-
http://elasticsearch-py.rtfd.org/
8+
http://elasticsearch-py.readthedocs.org/
99

1010
.Elasticsearch DSL
1111
************************************************************************************
1212
For a more high level client library with more limited scope, have a look at
13-
http://elasticsearch-dsl.rtfd.org/[elasticsearch-dsl] - a more pythonic library
13+
http://elasticsearch-dsl.readthedocs.org/[elasticsearch-dsl] - a more pythonic library
1414
sitting on top of `elasticsearch-py`.
1515
1616
It provides a more convenient and idiomatic way to write and manipulate

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