chore: regenerate dataproc client (googleapis#29942)

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-dataproc/v1/2.0.0/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-dataproc</artifactId>
-      <version>v1-rev20251015-2.0.0</version>
+      <version>v1-rev20251021-2.0.0</version>
     </dependency>
   </dependencies>
 </project>
@@ -35,7 +35,7 @@ repositories {
   mavenCentral()
 }
 dependencies {
-  implementation 'com.google.apis:google-api-services-dataproc:v1-rev20251015-2.0.0'
+  implementation 'com.google.apis:google-api-services-dataproc:v1-rev20251021-2.0.0'
 }
 ```
 

clients/google-api-services-dataproc/v1/2.0.0/com/google/api/services/dataproc/model/PySparkJob.java

@@ -33,7 +33,9 @@ public final class PySparkJob extends com.google.api.client.json.GenericJson {
 
   /**
    * Optional. HCFS URIs of archives to be extracted into the working directory of each executor.
-   * Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
+   * Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.Note: Spark applications must be
+   * deployed in cluster mode (https://spark.apache.org/docs/latest/cluster-overview.html) for
+   * correct environment propagation.
    * The value may be {@code null}.
    */
   @com.google.api.client.util.Key
@@ -96,7 +98,9 @@ public final class PySparkJob extends com.google.api.client.json.GenericJson {
 
   /**
    * Optional. HCFS URIs of archives to be extracted into the working directory of each executor.
-   * Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
+   * Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.Note: Spark applications must be
+   * deployed in cluster mode (https://spark.apache.org/docs/latest/cluster-overview.html) for
+   * correct environment propagation.
    * @return value or {@code null} for none
    */
   public java.util.List<java.lang.String> getArchiveUris() {
@@ -105,7 +109,9 @@ public java.util.List<java.lang.String> getArchiveUris() {
 
   /**
    * Optional. HCFS URIs of archives to be extracted into the working directory of each executor.
-   * Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.
+   * Supported file types: .jar, .tar, .tar.gz, .tgz, and .zip.Note: Spark applications must be
+   * deployed in cluster mode (https://spark.apache.org/docs/latest/cluster-overview.html) for
+   * correct environment propagation.
    * @param archiveUris archiveUris or {@code null} for none
    */
   public PySparkJob setArchiveUris(java.util.List<java.lang.String> archiveUris) {

clients/google-api-services-dataproc/v1/2.0.0/pom.xml

@@ -8,8 +8,8 @@
 
   <groupId>com.google.apis</groupId>
   <artifactId>google-api-services-dataproc</artifactId>
-  <version>v1-rev20251015-2.0.0</version>
-  <name>Cloud Dataproc API v1-rev20251015-2.0.0</name>
+  <version>v1-rev20251021-2.0.0</version>
+  <name>Cloud Dataproc API v1-rev20251021-2.0.0</name>
   <packaging>jar</packaging>
 
   <inceptionYear>2011</inceptionYear>

clients/google-api-services-dataproc/v1/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-dataproc</artifactId>
-      <version>v1-rev20251015-2.0.0</version>
+      <version>v1-rev20251021-2.0.0</version>
     </dependency>
   </dependencies>
 </project>
@@ -35,7 +35,7 @@ repositories {
   mavenCentral()
 }
 dependencies {
-  implementation 'com.google.apis:google-api-services-dataproc:v1-rev20251015-2.0.0'
+  implementation 'com.google.apis:google-api-services-dataproc:v1-rev20251021-2.0.0'
 }
 ```