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When creating a Dataproc cluster, you can put the cluster into
Hadoop High Availability (HA) mode by
specifying the number of master instances in the
cluster. The number of masters can only be specified at cluster creation time.
Currently, Dataproc supports two master configurations:
1 master (default, non HA)
3 masters (Hadoop HA)
Comparison of default and Hadoop High Availability mode
Compute Engine failure: In the rare case of an
unexpected Compute Engine failure, Dataproc
instances will experience a machine reboot. The default single-master
configuration for Dataproc is designed to recover and continue processing
new work in such cases, but in-flight jobs will necessarily fail and need to be
retried, and HDFS will be inaccessible until the single NameNode fully recovers
on reboot. In HA mode, HDFS High Availability and
YARN High Availability
are configured to allow uninterrupted YARN and HDFS operations despite any
single-node failures/reboots.
Job driver termination: The driver/main program of any jobs you run still represents a
potential single point of failure if the correctness of your job depends on the
driver program running successfully. Jobs submitted through the Dataproc
Jobs API are not considered "high availability," and will still be terminated on
failure of the master node that runs the corresponding job driver programs. For
individual jobs to be resilient against single-node failures using a HA Cloud
Dataproc cluster, the job must either 1) run without a synchronous driver
program or 2) it must run the driver program itself inside a YARN container and
be written to handle driver-program restarts. See
Launching Spark on YARN for an example
of how restartable driver programs can run inside YARN containers for fault
tolerance.
Zonal failure: As is the case with all Dataproc clusters, all nodes in a High
Availability cluster reside in the same zone. If there is a failure that
impacts all nodes in a zone, the failure will not be mitigated.
Instance Names
The default master is named cluster-name-m; HA masters are named
cluster-name-m-0, cluster-name-m-1, cluster-name-m-2.
Apache ZooKeeper
In an HA Dataproc cluster, the
Zookeeper component
is automatically installed on cluster master nodes. All masters
participate in a ZooKeeper cluster, which enables automatic failover for
other Hadoop services.
HDFS
In a standard Dataproc cluster:
cluster-name-m runs:
NameNode
Secondary NameNode
In a High Availability Dataproc cluster:
cluster-name-m-0 and cluster-name-m-1 run:
NameNode
ZKFailoverController
All masters run JournalNode
There is no Secondary NameNode
Please see the HDFS High Availability
documentation for additional details on components.
YARN
In a standard Dataproc cluster, cluster-name-m runs ResourceManager.
In a High Availability Dataproc cluster, all masters run ResourceManager.
Please see the YARN High Availability
documentation for additional details on components.
To create an HA cluster, select High Availability (3 masters, N workers) in
the Cluster type section of the Set up cluster panel on the
Dataproc
Create a cluster
page.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\u003cp\u003eDataproc clusters can be configured in Hadoop High Availability (HA) mode by setting the number of master instances to 3 during cluster creation, as opposed to the default of 1.\u003c/p\u003e\n"],["\u003cp\u003eHA mode provides uninterrupted YARN and HDFS operations despite single-node failures or reboots, unlike the default mode where in-flight jobs may fail during a Compute Engine failure, necessitating job retries.\u003c/p\u003e\n"],["\u003cp\u003eJobs submitted through the Dataproc Jobs API are not considered "high availability" and will be terminated if the master node running the job driver fails; if a job requires high availability, it must be launched without a driver program, or the driver program must be launched within a YARN container.\u003c/p\u003e\n"],["\u003cp\u003eIn an HA cluster, all master nodes participate in a ZooKeeper cluster to enable automatic failover, and each node runs ResourceManager, while in a default cluster, the single master runs the NameNode, Secondary NameNode, and ResourceManager.\u003c/p\u003e\n"],["\u003cp\u003eCreating an HA cluster involves using either the gcloud command with \u003ccode\u003e--num-masters=3\u003c/code\u003e, the REST API by setting \u003ccode\u003emasterConfig.numInstances\u003c/code\u003e to \u003ccode\u003e3\u003c/code\u003e, or by selecting "High Availability (3 masters, N workers)" in the Dataproc console.\u003c/p\u003e\n"]]],[],null,["# High Availability Mode\n\nWhen creating a Dataproc cluster, you can put the cluster into\nHadoop High Availability (HA) mode by\nspecifying the number of master instances in the\ncluster. The number of masters can only be specified at cluster creation time.\n\nCurrently, Dataproc supports two master configurations:\n\n- 1 master (default, non HA)\n- 3 masters (Hadoop HA)\n\nComparison of default and Hadoop High Availability mode\n-------------------------------------------------------\n\n| Due to the complexity and higher cost of HA mode, use the default mode unless your use case requires HA mode.\n\n- **Compute Engine failure:** In the rare case of an\n unexpected Compute Engine failure, Dataproc\n instances will experience a machine reboot. The default single-master\n configuration for Dataproc is designed to recover and continue processing\n new work in such cases, but in-flight jobs will necessarily fail and need to be\n retried, and HDFS will be inaccessible until the single NameNode fully recovers\n on reboot. In **HA mode** , [HDFS High Availability](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithQJM.html) and\n [YARN High Availability](https://hadoop.apache.org/docs/stable/hadoop-yarn/hadoop-yarn-site/ResourceManagerHA.html)\n are configured to allow uninterrupted YARN and HDFS operations despite any\n single-node failures/reboots.\n\n- **Job driver termination:** The driver/main program of any jobs you run still represents a\n potential single point of failure if the correctness of your job depends on the\n driver program running successfully. Jobs submitted through the Dataproc\n Jobs API are not considered \"high availability,\" and will still be terminated on\n failure of the master node that runs the corresponding job driver programs. For\n individual jobs to be resilient against single-node failures using a HA Cloud\n Dataproc cluster, the job must either 1) run without a synchronous driver\n program or 2) it must run the driver program itself inside a YARN container and\n be written to handle driver-program restarts. See\n [Launching Spark on YARN](http://spark.apache.org/docs/latest/running-on-yarn.html#launching-spark-on-yarn) for an example\n of how restartable driver programs can run inside YARN containers for fault\n tolerance.\n\n- **Zonal failure:** As is the case with all Dataproc clusters, all nodes in a High\n Availability cluster reside in the same zone. If there is a failure that\n impacts all nodes in a zone, the failure will not be mitigated.\n\n### Instance Names\n\nThe default master is named `cluster-name-m`; HA masters are named\n`cluster-name-m-0`, `cluster-name-m-1`, `cluster-name-m-2`.\n\n### Apache ZooKeeper\n\nIn an HA Dataproc cluster, the\n[Zookeeper component](/dataproc/docs/concepts/components/zookeeper)\nis automatically installed on cluster master nodes. All masters\nparticipate in a ZooKeeper cluster, which enables automatic failover for\nother Hadoop services.\n\n### HDFS\n\nIn a standard Dataproc cluster:\n\n- `cluster-name-m` runs:\n - NameNode\n - Secondary NameNode\n\nIn a High Availability Dataproc cluster:\n\n- `cluster-name-m-0` and `cluster-name-m-1` run:\n - NameNode\n - ZKFailoverController\n- All masters run JournalNode\n- There is no Secondary NameNode\n\nPlease see the [HDFS High Availability](https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HDFSHighAvailabilityWithQJM.html)\ndocumentation for additional details on components.\n\n### YARN\n\nIn a standard Dataproc cluster, `cluster-name-m` runs ResourceManager.\n\nIn a High Availability Dataproc cluster, all masters run ResourceManager.\n\nPlease see the [YARN High Availability](https://hadoop.apache.org/docs/stable/hadoop-yarn/hadoop-yarn-site/ResourceManagerHA.html)\ndocumentation for additional details on components.\n\nCreate a High Availability cluster\n----------------------------------\n\n### gcloud command\n\n\n| **gcloud CLI setup:** You must [setup and configure](/sdk/docs/quickstarts) the gcloud CLI to use the Google Cloud CLI.\nTo create an HA cluster with [gcloud dataproc clusters create](/sdk/gcloud/reference/dataproc/clusters/create), run the following command: \n\n```\ngcloud dataproc clusters create cluster-name \\\n --region=region \\\n --num-masters=3 \\\n ... other args\n```\n\n\u003cbr /\u003e\n\n### REST API\n\n\nTo create an HA cluster, use the\n[clusters.create](/dataproc/docs/reference/rest/v1/projects.regions.clusters/create)\nAPI, setting [masterConfig.numInstances](/dataproc/docs/reference/rest/v1/ClusterConfig#InstanceGroupConfig)\nto `3`.\n| An easy way to construct the JSON body of an HA cluster create request is to create the request from the Dataproc [Create a cluster](https://console.cloud.google.com/dataproc/clustersAdd) page of the Google Cloud console. Select High Availability (3 masters, N workers) in the Cluster type section of the Set up cluster panel, then click the Equivalent REST button at the bottom of the left panel. Here's a snippet of a sample JSON output produced by the console for an HA cluster create request: \n|\n| ```\n| ...\n| masterConfig\": {\n| \"numInstances\": 3,\n| \"machineTypeUri\": \"n1-standard-4\",\n| \"diskConfig\": {\n| \"bootDiskSizeGb\": 500,\n| \"numLocalSsds\": 0\n| }\n| }\n| ...\n| ```\n\n\u003cbr /\u003e\n\n### Console\n\n\nTo create an HA cluster, select High Availability (3 masters, N workers) in\nthe Cluster type section of the Set up cluster panel on the\nDataproc\n[Create a cluster](https://console.cloud.google.com/dataproc/clustersAdd)\npage."]]
