An idiomatic C++ client library for the Cloud Dataproc API, a managed Apache Spark and Apache Hadoop service that lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. This library allows you to manage Cloud Dataproc resources, but it does not provide APIs to run C++ applications in Cloud Dataproc.
While this library is GA, please note Google Cloud C++ client libraries do not follow Semantic Versioning.
Quickstart
The following shows the code that you'll run in the google/cloud/dataproc/quickstart/ directory, which should give you a taste of the Cloud Dataproc API C++ client library API.
This library offers multiple *Client classes, which are listed below. Each one of these classes exposes all the RPCs for a service as member functions of the class. This library groups multiple services because they are part of the same product or are often used together. A typical example may be the administrative and data plane operations for a single product.
The library also has other classes that provide helpers, configuration parameters, and infrastructure to mock the *Client classes when testing your application.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[[["\u003cp\u003eThis webpage details the Cloud Dataproc API C++ client library, which facilitates managing Cloud Dataproc resources, a service for Apache Spark and Apache Hadoop, but does not run C++ applications within it.\u003c/p\u003e\n"],["\u003cp\u003eThe library provides several \u003ccode\u003e*Client\u003c/code\u003e classes, such as \u003ccode\u003eAutoscalingPolicyServiceClient\u003c/code\u003e, \u003ccode\u003eBatchControllerClient\u003c/code\u003e, \u003ccode\u003eClusterControllerClient\u003c/code\u003e, \u003ccode\u003eJobControllerClient\u003c/code\u003e, \u003ccode\u003eNodeGroupControllerClient\u003c/code\u003e, and \u003ccode\u003eWorkflowTemplateServiceClient\u003c/code\u003e, each exposing RPCs for a specific service.\u003c/p\u003e\n"],["\u003cp\u003eThe latest release candidate version is 2.37.0-rc, and other versions are available such as 2.36.0, 2.35.0, 2.34.0, 2.33.0, and down to the 2.11.0, with the current version being 2.20.0, but it is important to know that the library does not adhere to Semantic Versioning.\u003c/p\u003e\n"],["\u003cp\u003eThe library's functionality includes error handling, endpoint overriding, authentication credential management, retry policy adjustments, and environment variable configurations.\u003c/p\u003e\n"],["\u003cp\u003eA quickstart example demonstrates how to use the \u003ccode\u003eClusterControllerClient\u003c/code\u003e to list clusters for a given project ID and region.\u003c/p\u003e\n"]]],[],null,["Version 2.20.0keyboard_arrow_down\n\n- [2.42.0-rc (latest)](/cpp/docs/reference/dataproc/latest)\n- [2.41.0](/cpp/docs/reference/dataproc/2.41.0)\n- [2.40.0](/cpp/docs/reference/dataproc/2.40.0)\n- [2.39.0](/cpp/docs/reference/dataproc/2.39.0)\n- [2.38.0](/cpp/docs/reference/dataproc/2.38.0)\n- [2.37.0](/cpp/docs/reference/dataproc/2.37.0)\n- [2.36.0](/cpp/docs/reference/dataproc/2.36.0)\n- [2.35.0](/cpp/docs/reference/dataproc/2.35.0)\n- [2.34.0](/cpp/docs/reference/dataproc/2.34.0)\n- [2.33.0](/cpp/docs/reference/dataproc/2.33.0)\n- [2.32.0](/cpp/docs/reference/dataproc/2.32.0)\n- [2.31.0](/cpp/docs/reference/dataproc/2.31.0)\n- [2.30.0](/cpp/docs/reference/dataproc/2.30.0)\n- [2.29.0](/cpp/docs/reference/dataproc/2.29.0)\n- [2.28.0](/cpp/docs/reference/dataproc/2.28.0)\n- [2.27.0](/cpp/docs/reference/dataproc/2.27.0)\n- [2.26.0](/cpp/docs/reference/dataproc/2.26.0)\n- [2.25.1](/cpp/docs/reference/dataproc/2.25.1)\n- [2.24.0](/cpp/docs/reference/dataproc/2.24.0)\n- [2.23.0](/cpp/docs/reference/dataproc/2.23.0)\n- [2.22.1](/cpp/docs/reference/dataproc/2.22.1)\n- [2.21.0](/cpp/docs/reference/dataproc/2.21.0)\n- [2.20.0](/cpp/docs/reference/dataproc/2.20.0)\n- [2.19.0](/cpp/docs/reference/dataproc/2.19.0)\n- [2.18.0](/cpp/docs/reference/dataproc/2.18.0)\n- [2.17.0](/cpp/docs/reference/dataproc/2.17.0)\n- [2.16.0](/cpp/docs/reference/dataproc/2.16.0)\n- [2.15.1](/cpp/docs/reference/dataproc/2.15.1)\n- [2.14.0](/cpp/docs/reference/dataproc/2.14.0)\n- [2.13.0](/cpp/docs/reference/dataproc/2.13.0)\n- [2.12.0](/cpp/docs/reference/dataproc/2.12.0)\n- [2.11.0](/cpp/docs/reference/dataproc/2.11.0) \n\nCloud Dataproc API C++ Client Library\n=====================================\n\nAn idiomatic C++ client library for the [Cloud Dataproc API](https://cloud.google.com/dataproc), a managed Apache Spark and Apache Hadoop service that lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. This library allows you to *manage* Cloud Dataproc resources, but it does not provide APIs to run C++ applications in Cloud Dataproc.\n\nWhile this library is **GA** , please note Google Cloud C++ client libraries do **not** follow [Semantic Versioning](https://semver.org/).\n\n### Quickstart\n\nThe following shows the code that you'll run in the `google/cloud/dataproc/quickstart/` directory, which should give you a taste of the Cloud Dataproc API C++ client library API. \n\n #include \"google/cloud/dataproc/v1/cluster_controller_client.h\"\n #include \"google/cloud/common_options.h\"\n #include \u003ciostream\u003e\n\n int main(int argc, char* argv[]) try {\n if (argc != 3) {\n std::cerr \u003c\u003c \"Usage: \" \u003c\u003c argv[0] \u003c\u003c \" project-id region\\n\";\n return 1;\n }\n std::string const project_id = argv[1];\n std::string const region = argv[2];\n\n namespace dataproc = ::google::cloud::dataproc_v1;\n\n auto client = dataproc::ClusterControllerClient(\n dataproc::MakeClusterControllerConnection(region == \"global\" ? \"\"\n : region));\n\n for (auto c : client.ListClusters(project_id, region)) {\n if (!c) throw std::move(c).status();\n std::cout \u003c\u003c c-\u003ecluster_name() \u003c\u003c \"\\n\";\n }\n\n return 0;\n } catch (google::cloud::Status const& status) {\n std::cerr \u003c\u003c \"google::cloud::Status thrown: \" \u003c\u003c status \u003c\u003c \"\\n\";\n return 1;\n }\n\n### Main classes\n\nThis library offers multiple `*Client` classes, which are listed below. Each one of these classes exposes all the RPCs for a service as member functions of the class. This library groups multiple services because they are part of the same product or are often used together. A typical example may be the administrative and data plane operations for a single product.\n\nThe library also has other classes that provide helpers, configuration parameters, and infrastructure to mock the `*Client` classes when testing your application.\n\n- [`dataproc_v1::AutoscalingPolicyServiceClient`](/cpp/docs/reference/dataproc/2.20.0/classgoogle_1_1cloud_1_1dataproc__v1_1_1AutoscalingPolicyServiceClient)\n- [`dataproc_v1::BatchControllerClient`](/cpp/docs/reference/dataproc/2.20.0/classgoogle_1_1cloud_1_1dataproc__v1_1_1BatchControllerClient)\n- [`dataproc_v1::ClusterControllerClient`](/cpp/docs/reference/dataproc/2.20.0/classgoogle_1_1cloud_1_1dataproc__v1_1_1ClusterControllerClient)\n- [`dataproc_v1::JobControllerClient`](/cpp/docs/reference/dataproc/2.20.0/classgoogle_1_1cloud_1_1dataproc__v1_1_1JobControllerClient)\n- [`dataproc_v1::NodeGroupControllerClient`](/cpp/docs/reference/dataproc/2.20.0/classgoogle_1_1cloud_1_1dataproc__v1_1_1NodeGroupControllerClient)\n- [`dataproc_v1::WorkflowTemplateServiceClient`](/cpp/docs/reference/dataproc/2.20.0/classgoogle_1_1cloud_1_1dataproc__v1_1_1WorkflowTemplateServiceClient)\n\n### More Information\n\n- [Error Handling](https://cloud.google.com/cpp/docs/reference/common/latest/common-error-handling.html) - describes how the library reports errors.\n- [How to Override the Default Endpoint](/cpp/docs/reference/dataproc/2.20.0/dataproc-override-endpoint) - describes how to override the default endpoint.\n- [How to Override the Authentication Credentials](/cpp/docs/reference/dataproc/2.20.0/dataproc-override-authentication) - describes how to change the authentication credentials used by the library.\n- [Override Retry, Backoff, and Idempotency Policies](/cpp/docs/reference/dataproc/2.20.0/dataproc-override-retry) - describes how to change the default retry policies.\n- [Environment Variables](/cpp/docs/reference/dataproc/2.20.0/dataproc-env) - describes environment variables that can configure the behavior of the library."]]