chore: regenerate bigquery client (googleapis#23538)

Generated in GitHub action: https://togithub.com/googleapis/googleapis/google-api-java-client-services/actions/workflows/codegen.yaml

Author: yoshi-code-bot

clients/google-api-services-bigquery/v2/2.0.0/README.md

@@ -22,7 +22,7 @@ Add the following lines to your `pom.xml` file:
     <dependency>
       <groupId>com.google.apis</groupId>
       <artifactId>google-api-services-bigquery</artifactId>
-      <version>v2-rev20240905-2.0.0</version>
+      <version>v2-rev20240919-2.0.0</version>
     </dependency>
   </dependencies>
 </project>
@@ -35,7 +35,7 @@ repositories {
   mavenCentral()
 }
 dependencies {
-  implementation 'com.google.apis:google-api-services-bigquery:v2-rev20240905-2.0.0'
+  implementation 'com.google.apis:google-api-services-bigquery:v2-rev20240919-2.0.0'
 }
 ```
 

clients/google-api-services-bigquery/v2/2.0.0/com/google/api/services/bigquery/model/TrainingOptions.java

@@ -151,6 +151,15 @@ public final class TrainingOptions extends com.google.api.client.json.GenericJso
   @com.google.api.client.util.Key
   private java.lang.Double colsampleBytree;
 
+  /**
+   * The contribution metric. Applies to contribution analysis models. Allowed formats supported are
+   * for summable and summable ratio contribution metrics. These include expressions such as
+   * "SUM(x)" or "SUM(x)/SUM(y)", where x and y are column names from the base table.
+   * The value may be {@code null}.
+   */
+  @com.google.api.client.util.Key
+  private java.lang.String contributionMetric;
+
   /**
    * Type of normalization algorithm for boosted tree models using dart booster.
    * The value may be {@code null}.
@@ -201,6 +210,13 @@ public final class TrainingOptions extends com.google.api.client.json.GenericJso
   @com.google.api.client.util.Key
   private java.lang.Boolean decomposeTimeSeries;
 
+  /**
+   * Optional. Names of the columns to slice on. Applies to contribution analysis models.
+   * The value may be {@code null}.
+   */
+  @com.google.api.client.util.Key
+  private java.util.List<java.lang.String> dimensionIdColumns;
+
   /**
    * Distance type for clustering models.
    * The value may be {@code null}.
@@ -315,6 +331,14 @@ public final class TrainingOptions extends com.google.api.client.json.GenericJso
   @com.google.api.client.util.Key @com.google.api.client.json.JsonString
   private java.lang.Long integratedGradientsNumSteps;
 
+  /**
+   * Name of the column used to determine the rows corresponding to control and test. Applies to
+   * contribution analysis models.
+   * The value may be {@code null}.
+   */
+  @com.google.api.client.util.Key
+  private java.lang.String isTestColumn;
+
   /**
    * Item column specified for matrix factorization models.
    * The value may be {@code null}.
@@ -417,6 +441,13 @@ public final class TrainingOptions extends com.google.api.client.json.GenericJso
   @com.google.api.client.util.Key @com.google.api.client.json.JsonString
   private java.lang.Long maxTreeDepth;
 
+  /**
+   * The apriori support minimum. Applies to contribution analysis models.
+   * The value may be {@code null}.
+   */
+  @com.google.api.client.util.Key
+  private java.lang.Double minAprioriSupport;
+
   /**
    * When early_stop is true, stops training when accuracy improvement is less than
    * 'min_relative_progress'. Used only for iterative training algorithms.
@@ -963,6 +994,27 @@ public TrainingOptions setColsampleBytree(java.lang.Double colsampleBytree) {
     return this;
   }
 
+  /**
+   * The contribution metric. Applies to contribution analysis models. Allowed formats supported are
+   * for summable and summable ratio contribution metrics. These include expressions such as
+   * "SUM(x)" or "SUM(x)/SUM(y)", where x and y are column names from the base table.
+   * @return value or {@code null} for none
+   */
+  public java.lang.String getContributionMetric() {
+    return contributionMetric;
+  }
+
+  /**
+   * The contribution metric. Applies to contribution analysis models. Allowed formats supported are
+   * for summable and summable ratio contribution metrics. These include expressions such as
+   * "SUM(x)" or "SUM(x)/SUM(y)", where x and y are column names from the base table.
+   * @param contributionMetric contributionMetric or {@code null} for none
+   */
+  public TrainingOptions setContributionMetric(java.lang.String contributionMetric) {
+    this.contributionMetric = contributionMetric;
+    return this;
+  }
+
   /**
    * Type of normalization algorithm for boosted tree models using dart booster.
    * @return value or {@code null} for none
@@ -1081,6 +1133,23 @@ public TrainingOptions setDecomposeTimeSeries(java.lang.Boolean decomposeTimeSer
     return this;
   }
 
+  /**
+   * Optional. Names of the columns to slice on. Applies to contribution analysis models.
+   * @return value or {@code null} for none
+   */
+  public java.util.List<java.lang.String> getDimensionIdColumns() {
+    return dimensionIdColumns;
+  }
+
+  /**
+   * Optional. Names of the columns to slice on. Applies to contribution analysis models.
+   * @param dimensionIdColumns dimensionIdColumns or {@code null} for none
+   */
+  public TrainingOptions setDimensionIdColumns(java.util.List<java.lang.String> dimensionIdColumns) {
+    this.dimensionIdColumns = dimensionIdColumns;
+    return this;
+  }
+
   /**
    * Distance type for clustering models.
    * @return value or {@code null} for none
@@ -1357,6 +1426,25 @@ public TrainingOptions setIntegratedGradientsNumSteps(java.lang.Long integratedG
     return this;
   }
 
+  /**
+   * Name of the column used to determine the rows corresponding to control and test. Applies to
+   * contribution analysis models.
+   * @return value or {@code null} for none
+   */
+  public java.lang.String getIsTestColumn() {
+    return isTestColumn;
+  }
+
+  /**
+   * Name of the column used to determine the rows corresponding to control and test. Applies to
+   * contribution analysis models.
+   * @param isTestColumn isTestColumn or {@code null} for none
+   */
+  public TrainingOptions setIsTestColumn(java.lang.String isTestColumn) {
+    this.isTestColumn = isTestColumn;
+    return this;
+  }
+
   /**
    * Item column specified for matrix factorization models.
    * @return value or {@code null} for none
@@ -1603,6 +1691,23 @@ public TrainingOptions setMaxTreeDepth(java.lang.Long maxTreeDepth) {
     return this;
   }
 
+  /**
+   * The apriori support minimum. Applies to contribution analysis models.
+   * @return value or {@code null} for none
+   */
+  public java.lang.Double getMinAprioriSupport() {
+    return minAprioriSupport;
+  }
+
+  /**
+   * The apriori support minimum. Applies to contribution analysis models.
+   * @param minAprioriSupport minAprioriSupport or {@code null} for none
+   */
+  public TrainingOptions setMinAprioriSupport(java.lang.Double minAprioriSupport) {
+    this.minAprioriSupport = minAprioriSupport;
+    return this;
+  }
+
   /**
    * When early_stop is true, stops training when accuracy improvement is less than
    * 'min_relative_progress'. Used only for iterative training algorithms.

clients/google-api-services-bigquery/v2/2.0.0/pom.xml

@@ -8,8 +8,8 @@
 
   <groupId>com.google.apis</groupId>
   <artifactId>google-api-services-bigquery</artifactId>
-  <version>v2-rev20240905-2.0.0</version>
-  <name>BigQuery API v2-rev20240905-2.0.0</name>
+  <version>v2-rev20240919-2.0.0</version>
+  <name>BigQuery API v2-rev20240919-2.0.0</name>
   <packaging>jar</packaging>
 
   <inceptionYear>2011</inceptionYear>

clients/google-api-services-bigquery/v2/README.md

@@ -22,7 +22,7 @@ Add the following lines to your `pom.xml` file:
     <dependency>
       <groupId>com.google.apis</groupId>
       <artifactId>google-api-services-bigquery</artifactId>
-      <version>v2-rev20240905-2.0.0</version>
+      <version>v2-rev20240919-2.0.0</version>
     </dependency>
   </dependencies>
 </project>
@@ -35,7 +35,7 @@ repositories {
   mavenCentral()
 }
 dependencies {
-  implementation 'com.google.apis:google-api-services-bigquery:v2-rev20240905-2.0.0'
+  implementation 'com.google.apis:google-api-services-bigquery:v2-rev20240919-2.0.0'
 }
 ```