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Yandex Data Processing
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        • Shared use of tables through Metastore
        • Transferring metadata between Yandex Data Processing clusters using Metastore
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In this article:

  • Required paid resources
  • Getting started
  • Create a test table
  • Export data
  • Connect Yandex Data Processing to Metastore
  • Import data
  • Check the result
  • Delete the resources you created
  1. Tutorials
  2. Integrating Yandex Data Processing with other services
  3. Hive Metastore
  4. Transferring metadata between Yandex Data Processing clusters using Metastore

Transferring metadata between Yandex Data Processing clusters using Metastore

Written by
Yandex Cloud
Updated at May 5, 2025
  • Required paid resources
  • Getting started
  • Create a test table
  • Export data
  • Connect Yandex Data Processing to Metastore
  • Import data
  • Check the result
  • Delete the resources you created

You can migrate metadata between Yandex Data Processing clusters with a Hive DBMS. First, you need to export metadata from a cluster, then import it into a different one using Hive Metastore.

To transfer metadata between Yandex Data Processing clusters:

  1. Create a test table.
  2. Export data.
  3. Connect Yandex Data Processing to Metastore.
  4. Import data.
  5. Check the result.

If you no longer need the resources you created, delete them.

Warning

If you want to configure an access policy for a bucket and connect to it from a Hive Metastore cluster, you will need some additional infrastructure setup. For more information, see this guide.

Note

Metastore is at the Preview stage.

Required paid resourcesRequired paid resources

The infrastructure support cost includes:

  • Fee for the Yandex Data Processing cluster computing resources and storage (see Yandex Data Processing pricing).
  • Fee for data storage and operations in a bucket (see Yandex Object Storage pricing).
  • Fee for NAT gateway usage and outbound traffic (see Yandex Virtual Private Cloud pricing).

Getting startedGetting started

Set up your infrastructure:

Manually
Terraform
  1. Create a service account named dataproc-s3-sa and assign it the dataproc.agent, dataproc.provisioner, managed-metastore.integrationProvider, and storage.uploader roles.

  2. In Yandex Object Storage, create a bucket named dataproc-bucket. Grant the READ and WRITE permission for this bucket to the service account.

  3. Create a cloud network named dataproc-network.

  4. In this network, create a subnet named dataproc-subnet.

  5. Set up a NAT gateway for the subnet you created.

  6. Create a dataproc-security-group with the following rules:

    Security group rules

    What service requires the rule

    Why the rule is required

    Rule settings

    Yandex Data Processing

    For incoming service traffic

    • Port range: 0-65535
    • Protocol: Any
    • Source: Security group
    • Security group: Self

    Yandex Data Processing

    For incoming traffic to allow access to NTP servers for time syncing

    • Port range: 123
    • Protocol: UDP
    • Source: CIDR
    • CIDR blocks: 0.0.0.0/0

    Yandex Data Processing

    For incoming traffic, to connect from the internet via SSH to subcluster hosts with public access

    • Port range: 22
    • Protocol: TCP
    • Source: CIDR
    • CIDR blocks: 0.0.0.0/0

    Metastore

    For incoming client traffic

    • Port range: 30000-32767
    • Protocol: Any
    • Source: CIDR
    • CIDR blocks: 0.0.0.0/0

    Metastore

    For incoming load balancer traffic

    • Port range: 10256
    • Protocol: Any
    • Source: Load balancer health checks

    Yandex Data Processing

    For outgoing service traffic

    • Port range: 0-65535
    • Protocol: Any
    • Source: Security group
    • Security group: Self

    Yandex Data Processing

    For outgoing HTTPS traffic

    • Port range: 443
    • Protocol: TCP
    • Destination type: CIDR
    • CIDR blocks: 0.0.0.0/0

    Yandex Data Processing

    For outgoing traffic to allow access to NTP servers for time syncing

    • Port range: 123
    • Protocol: UDP
    • Source: CIDR
    • CIDR blocks: 0.0.0.0/0

    Yandex Data Processing

    For outgoing traffic to allow Yandex Data Processing cluster connections to Metastore

    • Port range: 9083
    • Protocol: Any
    • Source: CIDR
    • CIDR blocks: 0.0.0.0/0
  7. Create two Yandex Data Processing clusters named dataproc-source and dataproc-target with the following settings:

    • Environment: PRODUCTION

    • Services:

      • HDFS
      • HIVE
      • SPARK
      • YARN
      • ZEPPELIN
    • Service account: dataproc-s3-sa.

    • Availability zone: Zone where dataproc-subnet resides.

    • Properties: spark:spark.sql.hive.metastore.sharedPrefixes with the com.amazonaws,ru.yandex.cloud value. Required for PySpark jobs and integration with Metastore.

    • Bucket name: dataproc-bucket.

    • Network: dataproc-network.

    • Security groups: dataproc-security-group.

    • UI Proxy: Enabled.

    • Subnet for the Yandex Data Processing subclusters: dataproc-subnet.

    • Public access for the master host: Enabled.

  1. If you do not have Terraform yet, install it.

  2. Get the authentication credentials. You can add them to environment variables or specify them later in the provider configuration file.

  3. Configure and initialize a provider. There is no need to create a provider configuration file manually, you can download it.

  4. Place the configuration file in a separate working directory and specify the parameter values. If you did not add the authentication credentials to environment variables, specify them in the configuration file.

  5. Download the metastore-import.tf configuration file to the same working directory.

    This file describes:

    • Network.
    • NAT gateway and route table required for Yandex Data Processing.
    • Subnet.
    • Security group for Yandex Data Processing and Metastore.
    • Service account required for the Yandex Data Processing cluster.
    • Service account required to create an Object Storage bucket.
    • Static access key required to create a Yandex Object Storage bucket.
    • Bucket.
    • Two Yandex Data Processing clusters.
  6. Specify the following in the metastore-import.tf file:

    • folder_id: Cloud folder ID, same as in the provider settings.
    • dp_ssh_key: Absolute path to the public key for the Yandex Data Processing clusters. To learn more, see Connecting to a Yandex Data Processing host via SSH.
  7. Make sure the Terraform configuration files are correct using this command:

    terraform validate
    

    If there are any errors in the configuration files, Terraform will point them out.

  8. Create the required infrastructure:

    1. Run this command to view the planned changes:

      terraform plan
      

      If you described the configuration correctly, the terminal will display a list of the resources to update and their parameters. This is a verification step that does not apply changes to your resources.

    2. If everything looks correct, apply the changes:

      1. Run this command:

        terraform apply
        
      2. Confirm updating the resources.

      3. Wait for the operation to complete.

    All the required resources will be created in the specified folder. You can check resource availability and their settings in the management console.

Create a test tableCreate a test table

In the dataproc-source cluster, create a test table named countries:

  1. Go to the folder page and select Yandex Data Processing.

  2. Open the dataproc-source cluster page.

  3. Click the Zeppelin Web UI link under UI Proxy.

  4. Select Notebook, then select Create new note.

  5. In the window that opens, specify the name for the note and click Create.

  6. To run a PySpark job, paste a Python script into the input line:

    %pyspark
    
    from pyspark.sql.types import *
    
    schema = StructType([StructField('Name', StringType(), True),
    StructField('Capital', StringType(), True),
    StructField('Area', IntegerType(), True),
    StructField('Population', IntegerType(), True)])
    
    df = spark.createDataFrame([('Australia', 'Canberra', 7686850, 19731984), ('Austria', 'Vienna', 83855, 7700000)], schema)
    df.write.mode("overwrite").option("path","s3a://dataproc-bucket/countries").saveAsTable("countries")
    
  7. Click Run all paragraphs and wait until the job is complete.

  8. Replace the Python code in the input line with this SQL query:

    %sql
    
    SELECT * FROM countries;
    
  9. Click Run all paragraphs.

    Result:

    |   Name    |  Capital |  Area   | Population |
    | --------- | -------- | ------- | ---------- |
    | Australia | Canberra | 7686850 | 19731984   |
    | Austria   | Vienna   | 83855   | 7700000    |
    

Export dataExport data

To transfer data from one Yandex Data Processing cluster to another, back up the data in the dataproc-source cluster using pg_dump:

  1. Use SSH to connect to the dataproc-source cluster's master host:

    ssh ubuntu@<master_host_FQDN>
    

    You can learn how to get the FQDN here.

  2. Create a backup and save it in the metastore_dump.sql file:

    pg_dump --data-only --schema public postgres://hive:hive-p2ssw0rd@localhost/metastore > metastore_dump.sql
    
  3. Disconnect from the master host.

  4. Download the metastore_dump.sql file to your local current directory:

    scp ubuntu@<master_host_FQDN>:metastore_dump.sql .
    
  5. Upload the metastore_dump.sql file to the dataproc-bucket bucket.

Connect Yandex Data Processing to MetastoreConnect Yandex Data Processing to Metastore

  1. Create a Metastore cluster with the following parameters:

    • Service account: dataproc-s3-sa
    • Network: dataproc-network
    • Subnet: dataproc-subnet
    • Security groups: dataproc-security-group
  2. Add to the dataproc-target cluster settings the spark:spark.hive.metastore.uris property with the following value: thrift://<Metastore_cluster_IP_address>:9083.

    To find out the Metastore cluster IP address, select Yandex MetaData Hub in the management console and then select the Metastore page in the left-hand panel. Copy the IP address column value for the cluster in question.

Import dataImport data

  1. Open the Metastore cluster page.
  2. Click Import.
  3. In the window that opens, specify the dataproc-bucket and the metastore_dump.sql file.
  4. Click Import.
  5. Wait for the import to complete. You can check the import status on the Metastore cluster page under  Operations.

Check the resultCheck the result

  1. Open the dataproc-target cluster page.

  2. Click the Zeppelin Web UI link under UI Proxy.

  3. Select Notebook, then select Create new note.

  4. In the window that opens, specify the name for the note and click Create.

  5. Run the following SQL query:

    %sql
    
    SELECT * FROM countries;
    
  6. Click Run all paragraphs.

    Result:

    |   Name    |  Capital |  Area   | Population |
    | --------- | -------- | ------- | ---------- |
    | Australia | Canberra | 7686850 | 19731984   |
    | Austria   | Vienna   | 83855   | 7700000    |
    

The metadata from the dataproc-source cluster was successfully imported into the dataproc-target cluster.

Delete the resources you createdDelete the resources you created

Some resources are not free of charge. Delete the resources you no longer need to avoid paying for them:

  1. Delete the Metastore cluster.

  2. Delete the objects from the bucket.

  3. Delete other resources depending on how they were created:

    Manually
    Terraform
    1. Yandex Data Processing clusters.
    2. Object Storage bucket.
    3. Route table.
    4. NAT gateway.
    5. Security group.
    6. Subnet.
    7. Network.
    8. Service account.
    1. In the terminal window, go to the directory containing the infrastructure plan.

      Warning

      Make sure the directory has no Terraform manifests with the resources you want to keep. Terraform deletes all resources that were created using the manifests in the current directory.

    2. Delete resources:

      1. Run this command:

        terraform destroy
        
      2. Confirm deleting the resources and wait for the operation to complete.

      All the resources described in the Terraform manifests will be deleted.

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© 2025 Direct Cursus Technology L.L.C.