Version: Latest-3.2

Unified catalog

A unified catalog is a type of external catalog that is provided by StarRocks from v3.2 onwards to handle tables from Apache Hive™, Apache Iceberg, Apache Hudi, and Delta Lake data sources as a unified data source without ingestion. With unified catalogs, you can:

Directly query data stored in Hive, Iceberg, Hudi, and Delta Lake without the need to manually create tables.
Use INSERT INTO or asynchronous materialized views (which are supported from v2.5 onwards) to process data stored in Hive, Iceberg, Hudi, and Delta Lake and load the data into StarRocks.
Perform operations on StarRocks to create or drop Hive and Iceberg databases and tables.

To ensure successful SQL workloads on your unified data source, your StarRocks cluster must be able to access the storage system and metastore of your unified data source. StarRocks supports the following storage systems and metastores:

Distributed file system (HDFS) or object storage like AWS S3, Microsoft Azure Storage, Google GCS, or other S3-compatible storage system (for example, MinIO)
Metastore like Hive metastore or AWS Glue

NOTE

If you choose AWS S3 as storage, you can use HMS or AWS Glue as metastore. If you choose any other storage system, you can only use HMS as metastore.

Limits

One unified catalog supports integrations with only a single storage system and a single metastore service. Therefore, make sure all the data sources you want to integrate as a unified data source with StarRocks use the same storage system and metastore service.

Usage notes

See the "Usage notes" section in Hive catalog, Iceberg catalog, Hudi catalog, and Delta Lake catalog to understand the file formats and data types supported.
Format-specific operations are supported only for specific table formats. For example, CREATE TABLE and DROP TABLE are supported only for Hive and Iceberg, and REFRESH EXTERNAL TABLE is supported only for Hive and Hudi.

When you create a table within a unified catalog by using the CREATE TABLE statement, use the ENGINE parameter to specify the table format (Hive or Iceberg).

Integration preparations

Before you create a unified catalog, make sure your StarRocks cluster can integrate with the storage system and metastore of your unified data source.

AWS IAM

If you use AWS S3 as storage or AWS Glue as metastore, choose your suitable authentication method and make the required preparations to ensure that your StarRocks cluster can access the related AWS cloud resources. For more information, see Authenticate to AWS resources - Preparations.

HDFS

If you choose HDFS as storage, configure your StarRocks cluster as follows:

(Optional) Set the username that is used to access your HDFS cluster and Hive metastore. By default, StarRocks uses the username of the FE and BE or CN processes to access your HDFS cluster and Hive metastore. You can also set the username by adding export HADOOP_USER_NAME="<user_name>" at the beginning of the fe/conf/hadoop_env.sh file of each FE and at the beginning of the be/conf/hadoop_env.sh file of each BE or the cn/conf/hadoop_env.sh file of each CN. After you set the username in these files, restart each FE and each BE or CN to make the parameter settings take effect. You can set only one username for each StarRocks cluster.
When you query data, the FEs and BEs or CNs of your StarRocks cluster use the HDFS client to access your HDFS cluster. In most cases, you do not need to configure your StarRocks cluster to achieve that purpose, and StarRocks starts the HDFS client using the default configurations. You need to configure your StarRocks cluster only in the following situations:
- High availability (HA) is enabled for your HDFS cluster: Add the hdfs-site.xml file of your HDFS cluster to the $FE_HOME/conf path of each FE and to the $BE_HOME/conf path of each BE or the $CN_HOME/conf path of each CN.
- View File System (ViewFs) is enabled for your HDFS cluster: Add the core-site.xml file of your HDFS cluster to the $FE_HOME/conf path of each FE and to the $BE_HOME/conf path of each BE or the $CN_HOME/conf path of each CN.

NOTE

If an error indicating an unknown host is returned when you send a query, you must add the mapping between the host names and IP addresses of your HDFS cluster nodes to the /etc/hosts path.

Kerberos authentication

If Kerberos authentication is enabled for your HDFS cluster or Hive metastore, configure your StarRocks cluster as follows:

Run the kinit -kt keytab_path principal command on each FE and each BE or CN to obtain Ticket Granting Ticket (TGT) from Key Distribution Center (KDC). To run this command, you must have the permissions to access your HDFS cluster and Hive metastore. Note that accessing KDC with this command is time-sensitive. Therefore, you need to use cron to run this command periodically.
Add JAVA_OPTS="-Djava.security.krb5.conf=/etc/krb5.conf" to the $FE_HOME/conf/fe.conf file of each FE and to the $BE_HOME/conf/be.conf file of each BE or the $CN_HOME/conf/cn.conf file of each CN. In this example, /etc/krb5.conf is the save path of the krb5.conf file. You can modify the path based on your needs.

Create a unified catalog

Syntax

CREATE EXTERNAL CATALOG <catalog_name>
[COMMENT <comment>]
PROPERTIES
(
    "type" = "unified",
    MetastoreParams,
    StorageCredentialParams,
    MetadataUpdateParams
)

Parameters

catalog_name

The name of the unified catalog. The naming conventions are as follows:

The name can contain letters, digits (0-9), and underscores (_). It must start with a letter.
The name is case-sensitive and cannot exceed 1023 characters in length.

comment

The description of the unified catalog. This parameter is optional.

type

The type of your data source. Set the value to unified.

MetastoreParams

A set of parameters about how StarRocks integrates with your metastore.

Hive metastore

If you choose Hive metastore as the metastore of your unified data source, configure MetastoreParams as follows:

"unified.metastore.type" = "hive",
"hive.metastore.uris" = "<hive_metastore_uri>"

NOTE

Before querying data, you must add the mapping between the host names and IP addresses of your Hive metastore nodes to the /etc/hosts path. Otherwise, StarRocks may fail to access your Hive metastore when you start a query.

The following table describes the parameters you need to configure in MetastoreParams.

Parameter	Required	Description
unified.metastore.type	Yes	The type of metastore that you use for your unified data source. Set the value to `hive`.
hive.metastore.uris	Yes	The URI of your Hive metastore. Format: `thrift://<metastore_IP_address>:<metastore_port>`. If high availability (HA) is enabled for your Hive metastore, you can specify multiple metastore URIs and separate them with commas (`,`), for example, `"thrift://<metastore_IP_address_1>:<metastore_port_1>,thrift://<metastore_IP_address_2>:<metastore_port_2>,thrift://<metastore_IP_address_3>:<metastore_port_3>"`.

AWS Glue

If you choose AWS Glue as the metastore of your data source, which is supported only when you choose AWS S3 as storage, take one of the following actions:

To choose the instance profile-based authentication method, configure MetastoreParams as follows:

"unified.metastore.type" = "glue",
"aws.glue.use_instance_profile" = "true",
"aws.glue.region" = "<aws_glue_region>"

To choose the assumed role-based authentication method, configure MetastoreParams as follows:

"unified.metastore.type" = "glue",
"aws.glue.use_instance_profile" = "true",
"aws.glue.iam_role_arn" = "<iam_role_arn>",
"aws.glue.region" = "<aws_glue_region>"

To choose the IAM user-based authentication method, configure MetastoreParams as follows:

"unified.metastore.type" = "glue",
"aws.glue.use_instance_profile" = "false",
"aws.glue.access_key" = "<iam_user_access_key>",
"aws.glue.secret_key" = "<iam_user_secret_key>",
"aws.glue.region" = "<aws_s3_region>"

The following table describes the parameters you need to configure in MetastoreParams.

Parameter	Required	Description
unified.metastore.type	Yes	The type of metastore that you use for your unified data source. Set the value to `glue`.
aws.glue.use_instance_profile	Yes	Specifies whether to enable the instance profile-based authentication method and the assumed role-based authentication. Valid values: `true` and `false`. Default value: `false`.
aws.glue.iam_role_arn	No	The ARN of the IAM role that has privileges on your AWS Glue Data Catalog. If you use the assumed role-based authentication method to access AWS Glue, you must specify this parameter.
aws.glue.region	Yes	The region in which your AWS Glue Data Catalog resides. Example: `us-west-1`.
aws.glue.access_key	No	The access key of your AWS IAM user. If you use the IAM user-based authentication method to access AWS Glue, you must specify this parameter.
aws.glue.secret_key	No	The secret key of your AWS IAM user. If you use the IAM user-based authentication method to access AWS Glue, you must specify this parameter.

For information about how to choose an authentication method for accessing AWS Glue and how to configure an access control policy in the AWS IAM Console, see Authentication parameters for accessing AWS Glue.

StorageCredentialParams

A set of parameters about how StarRocks integrates with your storage system. This parameter set is optional.

If you use HDFS as storage, you do not need to configure StorageCredentialParams.

If you use AWS S3, other S3-compatible storage system, Microsoft Azure Storage, or Google GCS as storage, you must configure StorageCredentialParams.

AWS S3

If you choose AWS S3 as storage, take one of the following actions:

To choose the instance profile-based authentication method, configure StorageCredentialParams as follows:
```
"aws.s3.use_instance_profile" = "true",
"aws.s3.region" = "<aws_s3_region>"
```

To choose the assumed role-based authentication method, configure StorageCredentialParams as follows:

"aws.s3.use_instance_profile" = "true",
"aws.s3.iam_role_arn" = "<iam_role_arn>",
"aws.s3.region" = "<aws_s3_region>"

To choose the IAM user-based authentication method, configure StorageCredentialParams as follows:

"aws.s3.use_instance_profile" = "false",
"aws.s3.access_key" = "<iam_user_access_key>",
"aws.s3.secret_key" = "<iam_user_secret_key>",
"aws.s3.region" = "<aws_s3_region>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
aws.s3.use_instance_profile	Yes	Specifies whether to enable the instance profile-based authentication method and the assumed role-based authentication method. Valid values: `true` and `false`. Default value: `false`.
aws.s3.iam_role_arn	No	The ARN of the IAM role that has privileges on your AWS S3 bucket. If you use the assumed role-based authentication method to access AWS S3, you must specify this parameter.
aws.s3.region	Yes	The region in which your AWS S3 bucket resides. Example: `us-west-1`.
aws.s3.access_key	No	The access key of your IAM user. If you use the IAM user-based authentication method to access AWS S3, you must specify this parameter.
aws.s3.secret_key	No	The secret key of your IAM user. If you use the IAM user-based authentication method to access AWS S3, you must specify this parameter.

For information about how to choose an authentication method for accessing AWS S3 and how to configure an access control policy in AWS IAM Console, see Authentication parameters for accessing AWS S3.

S3-compatible storage system

If you choose an S3-compatible storage system, such as MinIO, as storage, configure StorageCredentialParams as follows to ensure a successful integration:

"aws.s3.enable_ssl" = "false",
"aws.s3.enable_path_style_access" = "true",
"aws.s3.endpoint" = "<s3_endpoint>",
"aws.s3.access_key" = "<iam_user_access_key>",
"aws.s3.secret_key" = "<iam_user_secret_key>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
aws.s3.enable_ssl	Yes	Specifies whether to enable SSL connection. Valid values: `true` and `false`. Default value: `true`.
aws.s3.enable_path_style_access	Yes	Specifies whether to enable path-style access. Valid values: `true` and `false`. Default value: `false`. For MinIO, you must set the value to `true`. Path-style URLs use the following format: `https://s3.<region_code>.amazonaws.com/<bucket_name>/<key_name>`. For example, if you create a bucket named `DOC-EXAMPLE-BUCKET1` in the US West (Oregon) Region, and you want to access the `alice.jpg` object in that bucket, you can use the following path-style URL: `https://s3.us-west-2.amazonaws.com/DOC-EXAMPLE-BUCKET1/alice.jpg`.
aws.s3.endpoint	Yes	The endpoint that is used to connect to your S3-compatible storage system instead of AWS S3.
aws.s3.access_key	Yes	The access key of your IAM user.
aws.s3.secret_key	Yes	The secret key of your IAM user.

Microsoft Azure Storage

Azure Blob Storage

If you choose Blob Storage as storage, take one of the following actions:

To choose the Shared Key authentication method, configure StorageCredentialParams as follows:
```
"azure.blob.storage_account" = "<storage_account_name>",
"azure.blob.shared_key" = "<storage_account_shared_key>"
```
The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter Required Description
azure.blob.storage_account Yes The username of your Blob Storage account.
azure.blob.shared_key Yes The shared key of your Blob Storage account.

To choose the SAS Token authentication method, configure StorageCredentialParams as follows:

"azure.blob.storage_account" = "<storage_account_name>",
"azure.blob.container" = "<container_name>",
"azure.blob.sas_token" = "<storage_account_SAS_token>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
azure.blob.storage_account	Yes	The username of your Blob Storage account.
azure.blob.container	Yes	The name of the blob container that stores your data.
azure.blob.sas_token	Yes	The SAS token that is used to access your Blob Storage account.

Azure Data Lake Storage Gen2

If you choose Data Lake Storage Gen2 as storage, take one of the following actions:

To choose the Managed Identity authentication method, configure StorageCredentialParams as follows:

"azure.adls2.oauth2_use_managed_identity" = "true",
"azure.adls2.oauth2_tenant_id" = "<service_principal_tenant_id>",
"azure.adls2.oauth2_client_id" = "<service_client_id>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
azure.adls2.oauth2_use_managed_identity	Yes	Specifies whether to enable the Managed Identity authentication method. Set the value to `true`.
azure.adls2.oauth2_tenant_id	Yes	The ID of the tenant whose data you want to access.
azure.adls2.oauth2_client_id	Yes	The client (application) ID of the managed identity.

To choose the Shared Key authentication method, configure StorageCredentialParams as follows:

"azure.adls2.storage_account" = "<storage_account_name>",
"azure.adls2.shared_key" = "<storage_account_shared_key>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
azure.adls2.storage_account	Yes	The username of your Data Lake Storage Gen2 storage account.
azure.adls2.shared_key	Yes	The shared key of your Data Lake Storage Gen2 storage account.

To choose the Service Principal authentication method, configure StorageCredentialParams as follows:

"azure.adls2.oauth2_client_id" = "<service_client_id>",
"azure.adls2.oauth2_client_secret" = "<service_principal_client_secret>",
"azure.adls2.oauth2_client_endpoint" = "<service_principal_client_endpoint>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
azure.adls2.oauth2_client_id	Yes	The client (application) ID of the service principal.
azure.adls2.oauth2_client_secret	Yes	The value of the new client (application) secret created.
azure.adls2.oauth2_client_endpoint	Yes	The OAuth 2.0 token endpoint (v1) of the service principal or application.

Azure Data Lake Storage Gen1

If you choose Data Lake Storage Gen1 as storage, take one of the following actions:

To choose the Managed Service Identity authentication method, configure StorageCredentialParams as follows:
```
"azure.adls1.use_managed_service_identity" = "true"
```
The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter Required Description
azure.adls1.use_managed_service_identity Yes Specifies whether to enable the Managed Service Identity authentication method. Set the value to true.

Parameter	Required	Description
azure.adls1.use_managed_service_identity	Yes	Specifies whether to enable the Managed Service Identity authentication method. Set the value to `true`.

To choose the Service Principal authentication method, configure StorageCredentialParams as follows:

"azure.adls1.oauth2_client_id" = "<application_client_id>",
"azure.adls1.oauth2_credential" = "<application_client_credential>",
"azure.adls1.oauth2_endpoint" = "<OAuth_2.0_authorization_endpoint_v2>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Required	Description
azure.adls1.oauth2_client_id	Yes	The client (application) ID of the service principal.
azure.adls1.oauth2_credential	Yes	The value of the new client (application) secret created.
azure.adls1.oauth2_endpoint	Yes	The OAuth 2.0 token endpoint (v1) of the service principal or application.

Google GCS

If you choose Google GCS as storage, take one of the following actions:

To choose the VM-based authentication method, configure StorageCredentialParams as follows:
```
"gcp.gcs.use_compute_engine_service_account" = "true"
```
The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter Default value Value example Description
gcp.gcs.use_compute_engine_service_account false true Specifies whether to directly use the service account that is bound to your Compute Engine.

To choose the service account-based authentication method, configure StorageCredentialParams as follows:

"gcp.gcs.service_account_email" = "<google_service_account_email>",
"gcp.gcs.service_account_private_key_id" = "<google_service_private_key_id>",
"gcp.gcs.service_account_private_key" = "<google_service_private_key>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Default value	Value example	Description
gcp.gcs.service_account_email	""	"user@hello.iam.gserviceaccount.com"	The email address in the JSON file generated at the creation of the service account.
gcp.gcs.service_account_private_key_id	""	"61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"	The private key ID in the JSON file generated at the creation of the service account.
gcp.gcs.service_account_private_key	""	"-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"	The private key in the JSON file generated at the creation of the service account.

To choose the impersonation-based authentication method, configure StorageCredentialParams as follows:

Make a VM instance impersonate a service account:

"gcp.gcs.use_compute_engine_service_account" = "true",
"gcp.gcs.impersonation_service_account" = "<assumed_google_service_account_email>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Default value	Value example	Description
gcp.gcs.use_compute_engine_service_account	false	true	Specifies whether to directly use the service account that is bound to your Compute Engine.
gcp.gcs.impersonation_service_account	""	"hello"	The service account that you want to impersonate.

Make a service account (temporarily named as meta service account) impersonate another service account (temporarily named as data service account):

"gcp.gcs.service_account_email" = "<google_service_account_email>",
"gcp.gcs.service_account_private_key_id" = "<meta_google_service_account_email>",
"gcp.gcs.service_account_private_key" = "<meta_google_service_account_email>",
"gcp.gcs.impersonation_service_account" = "<data_google_service_account_email>"

The following table describes the parameters you need to configure in StorageCredentialParams.

Parameter	Default value	Value example	Description
gcp.gcs.service_account_email	""	"user@hello.iam.gserviceaccount.com"	The email address in the JSON file generated at the creation of the meta service account.
gcp.gcs.service_account_private_key_id	""	"61d257bd8479547cb3e04f0b9b6b9ca07af3b7ea"	The private key ID in the JSON file generated at the creation of the meta service account.
gcp.gcs.service_account_private_key	""	"-----BEGIN PRIVATE KEY----xxxx-----END PRIVATE KEY-----\n"	The private key in the JSON file generated at the creation of the meta service account.
gcp.gcs.impersonation_service_account	""	"hello"	The data service account that you want to impersonate.

MetadataUpdateParams

A set of parameters about how StarRocks updates the cached metadata of Hive, Hudi, and Delta Lake. This parameter set is optional. For more information about the policies for updating cached metadata from Hive, Hudi, and Delta Lake, see Hive catalog, Hudi catalog, and Delta Lake catalog.

In most cases, you can ignore MetadataUpdateParams and do not need to tune the policy parameters in it, because the default values of these parameters already provide you with an out-of-the-box performance.

However, if the frequency of data updates in Hive, Hudi, or Delta Lake is high, you can tune these parameters to further optimize the performance of automatic asynchronous updates.

Parameter	Required	Description
enable_metastore_cache	No	Specifies whether StarRocks caches the metadata of Hive, Hudi, or Delta Lake tables. Valid values: `true` and `false`. Default value: `true`. The value `true` enables the cache, and the value `false` disables the cache.
enable_remote_file_cache	No	Specifies whether StarRocks caches the metadata of the underlying data files of Hive, Hudi, or Delta Lake tables or partitions. Valid values: `true` and `false`. Default value: `true`. The value true enables the cache, and the value `false` disables the cache.
metastore_cache_refresh_interval_sec	No	The time interval at which StarRocks asynchronously updates the metadata of Hive, Hudi, or Delta Lake tables or partitions cached in itself. Unit: seconds. Default value: `7200`, which is 2 hours.
remote_file_cache_refresh_interval_sec	No	The time interval at which StarRocks asynchronously updates the metadata of the underlying data files of Hive, Hudi, or Delta Lake tables or partitions cached in itself. Unit: seconds. Default value: `60`.
metastore_cache_ttl_sec	No	The time interval at which StarRocks automatically discards the metadata of Hive, Hudi, or Delta Lake tables or partitions cached in itself. Unit: seconds. Default value: `86400`, which is 24 hours.
remote_file_cache_ttl_sec	No	The time interval at which StarRocks automatically discards the metadata of the underlying data files of Hive, Hudi, or Delta Lake tables or partitions cached in itself. Unit: seconds. Default value: `129600`, which is 36 hours.

Examples

The following examples create a unified catalog named unified_catalog_hms or unified_catalog_glue, depending on the type of metastore you use, to query data from your unified data source.

HDFS

If you use HDFS as storage, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083"
);

AWS S3

Instance profile-based authentication

If you use Hive metastore, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "aws.s3.use_instance_profile" = "true",
    "aws.s3.region" = "us-west-2"
);

If you use AWS Glue with Amazon EMR, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_glue
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "glue",
    "aws.glue.use_instance_profile" = "true",
    "aws.glue.region" = "us-west-2",
    "aws.s3.use_instance_profile" = "true",
    "aws.s3.region" = "us-west-2"
);

Assumed role-based authentication

If you use Hive metastore, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "aws.s3.use_instance_profile" = "true",
    "aws.s3.iam_role_arn" = "arn:aws:iam::081976408565:role/test_s3_role",
    "aws.s3.region" = "us-west-2"
);

If you use AWS Glue with Amazon EMR, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_glue
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "glue",
    "aws.glue.use_instance_profile" = "true",
    "aws.glue.iam_role_arn" = "arn:aws:iam::081976408565:role/test_glue_role",
    "aws.glue.region" = "us-west-2",
    "aws.s3.use_instance_profile" = "true",
    "aws.s3.iam_role_arn" = "arn:aws:iam::081976408565:role/test_s3_role",
    "aws.s3.region" = "us-west-2"
);

IAM user-based authentication

If you use Hive metastore, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "aws.s3.use_instance_profile" = "false",
    "aws.s3.access_key" = "<iam_user_access_key>",
    "aws.s3.secret_key" = "<iam_user_access_key>",
    "aws.s3.region" = "us-west-2"
);

If you use AWS Glue with Amazon EMR, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_glue
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "glue",
    "aws.glue.use_instance_profile" = "false",
    "aws.glue.access_key" = "<iam_user_access_key>",
    "aws.glue.secret_key" = "<iam_user_secret_key>",
    "aws.glue.region" = "us-west-2",
    "aws.s3.use_instance_profile" = "false",
    "aws.s3.access_key" = "<iam_user_access_key>",
    "aws.s3.secret_key" = "<iam_user_secret_key>",
    "aws.s3.region" = "us-west-2"
);

S3-compatible storage system

Use MinIO as an example. Run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "aws.s3.enable_ssl" = "true",
    "aws.s3.enable_path_style_access" = "true",
    "aws.s3.endpoint" = "<s3_endpoint>",
    "aws.s3.access_key" = "<iam_user_access_key>",
    "aws.s3.secret_key" = "<iam_user_secret_key>"
);

Microsoft Azure Storage

Azure Blob Storage

If you choose the Shared Key authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.blob.storage_account" = "<blob_storage_account_name>",
    "azure.blob.shared_key" = "<blob_storage_account_shared_key>"
);

If you choose the SAS Token authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.blob.storage_account" = "<blob_storage_account_name>",
    "azure.blob.container" = "<blob_container_name>",
    "azure.blob.sas_token" = "<blob_storage_account_SAS_token>"
);

Azure Data Lake Storage Gen1

If you choose the Managed Service Identity authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.adls1.use_managed_service_identity" = "true"    
);

If you choose the Service Principal authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.adls1.oauth2_client_id" = "<application_client_id>",
    "azure.adls1.oauth2_credential" = "<application_client_credential>",
    "azure.adls1.oauth2_endpoint" = "<OAuth_2.0_authorization_endpoint_v2>"
);

Azure Data Lake Storage Gen2

If you choose the Managed Identity authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.adls2.oauth2_use_managed_identity" = "true",
    "azure.adls2.oauth2_tenant_id" = "<service_principal_tenant_id>",
    "azure.adls2.oauth2_client_id" = "<service_client_id>"
);

If you choose the Shared Key authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.adls2.storage_account" = "<storage_account_name>",
    "azure.adls2.shared_key" = "<shared_key>"     
);

If you choose the Service Principal authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "azure.adls2.oauth2_client_id" = "<service_client_id>",
    "azure.adls2.oauth2_client_secret" = "<service_principal_client_secret>",
    "azure.adls2.oauth2_client_endpoint" = "<service_principal_client_endpoint>"
);

Google GCS

If you choose the VM-based authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "gcp.gcs.use_compute_engine_service_account" = "true"    
);

If you choose the service account-based authentication method, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "gcp.gcs.service_account_email" = "<google_service_account_email>",
    "gcp.gcs.service_account_private_key_id" = "<google_service_private_key_id>",
    "gcp.gcs.service_account_private_key" = "<google_service_private_key>"    
);

If you choose the impersonation-based authentication method:

If you make a VM instance impersonate a service account, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "gcp.gcs.use_compute_engine_service_account" = "true",
    "gcp.gcs.impersonation_service_account" = "<assumed_google_service_account_email>"    
);

If you make a service account impersonate another service account, run a command like below:

CREATE EXTERNAL CATALOG unified_catalog_hms
PROPERTIES
(
    "type" = "unified",
    "unified.metastore.type" = "hive",
    "hive.metastore.uris" = "thrift://xx.xx.xx.xx:9083",
    "gcp.gcs.service_account_email" = "<google_service_account_email>",
    "gcp.gcs.service_account_private_key_id" = "<meta_google_service_account_email>",
    "gcp.gcs.service_account_private_key" = "<meta_google_service_account_email>",
    "gcp.gcs.impersonation_service_account" = "<data_google_service_account_email>"    
);

View unified catalogs

You can use SHOW CATALOGS to query all catalogs in the current StarRocks cluster:

SHOW CATALOGS;

You can also use SHOW CREATE CATALOG to query the creation statement of an external catalog. The following example queries the creation statement of a unified catalog named unified_catalog_glue:

SHOW CREATE CATALOG unified_catalog_glue;

Switch to a Unified Catalog and a database in it

You can use one of the following methods to switch to a unified catalog and a database in it:

Use SET CATALOG to specify a unified catalog in the current session, and then use USE to specify an active database:

-- Switch to a specified catalog in the current session:
SET CATALOG <catalog_name>
-- Specify the active database in the current session:
USE <db_name>

Directly use USE to switch to a unified catalog and a database in it:
```
USE <catalog_name>.<db_name>
```

Drop a unified catalog

You can use DROP CATALOG to drop an external catalog.

The following example drops a unified catalog named unified_catalog_glue:

DROP CATALOG unified_catalog_glue;

View the schema of a table from a unified catalog

You can use one of the following syntaxes to view the schema of a table from a unified catalog:

View schema

DESC[RIBE] <catalog_name>.<database_name>.<table_name>

View schema and location from the CREATE statement

SHOW CREATE TABLE <catalog_name>.<database_name>.<table_name>

Query data from a unified catalog

To query data from a unified catalog, follow these steps:

Use SHOW DATABASES to view the databases in your unified data source with which the unified catalog is associated:
```
SHOW DATABASES FROM <catalog_name>
```
Switch to a Hive Catalog and a database in it.
Use SELECT to query the destination table in the specified database:
```
SELECT count(*) FROM <table_name> LIMIT 10
```

Load data from Hive, Iceberg, Hudi, or Delta Lake

You can use INSERT INTO to load the data of a Hive, Iceberg, Hudi, or Delta Lake table into a StarRocks table created within a unified catalog.

The following example loads the data of the Hive table hive_table into the StarRocks table test_tbl created in the database test_database that belongs to the unified catalog unified_catalog:

INSERT INTO unified_catalog.test_database.test_table SELECT * FROM hive_table

Create a database in a unified catalog

Similar to the internal catalog of StarRocks, if you have the CREATE DATABASE privilege on a unified catalog, you can use the CREATE DATABASE statement to create a database in that catalog.

NOTE

You can grant and revoke privileges by using GRANT and REVOKE.

StarRocks supports creating only Hive and Iceberg databases in unified catalogs.

Switch to a unified catalog, and then use the following statement to create a database in that catalog:

CREATE DATABASE <database_name>
[properties ("location" = "<prefix>://<path_to_database>/<database_name.db>")]

The location parameter specifies the file path in which you want to create the database, which can be in either HDFS or cloud storage.

When you use Hive metastore as the metastore of your data source, the location parameter defaults to <warehouse_location>/<database_name.db>, which is supported by Hive metastore if you do not specify that parameter at database creation.
When you use AWS Glue as the metastore of your data source, the location parameter does not have a default value, and therefore you must specify that parameter at database creation.

The prefix varies based on the storage system you use:

Storage system	`Prefix` value
HDFS	`hdfs`
Google GCS	`gs`
Azure Blob Storage	If your storage account allows access over HTTP, the `prefix` is `wasb`. If your storage account allows access over HTTPS, the `prefix` is `wasbs`.
Azure Data Lake Storage Gen1	`adl`
Azure Data Lake Storage Gen2	If your storage account allows access over HTTP, the`prefix` is `abfs`. If your storage account allows access over HTTPS, the `prefix` is `abfss`.
AWS S3 or other S3-compatible storage (for example, MinIO)	`s3`

Drop a database from a unified catalog

Similar to the internal databases of StarRocks, if you have the DROP privilege on a database created within a unified catalog, you can use the DROP DATABASE statement to drop that database. You can only drop empty databases.

NOTE

You can grant and revoke privileges by using GRANT and REVOKE.

StarRocks supports dropping only Hive and Iceberg databases from unified catalogs.

When you drop a database from a unified catalog, the database's file path on your HDFS cluster or cloud storage will not be dropped along with the database.

Switch to a unified catalog, and then use the following statement to drop a database in that catalog:

DROP DATABASE <database_name>

Create a table in a unified catalog

Similar to the internal databases of StarRocks, if you have the CREATE TABLE privilege on a database created within a unified catalog, you can use the CREATE TABLE or CREATE TABLE AS SELECT (CTAS) statement to create a table in that database.

NOTE

You can grant and revoke privileges by using GRANT and REVOKE.

StarRocks supports creating only Hive and Iceberg tables in unified catalogs.

Switch to a Hive Catalog and a database in it. Then, use CREATE TABLE to create a Hive or Iceberg table in that database:

CREATE TABLE <table_name>
(column_definition1[, column_definition2, ...]
ENGINE = {|hive|iceberg}
[partition_desc]

For more information, see Create a Hive table and Create an Iceberg table.

The following example creates a Hive table named hive_table. The table consists of three columns action, id, and dt, of which id and dtare partition columns.

CREATE TABLE hive_table
(
    action varchar(65533),
    id int,
    dt date
)
ENGINE = hive
PARTITION BY (id,dt);

Sink data to a table in a unified catalog

Similar to the internal tables of StarRocks, if you have the INSERT privilege on a table created within a unified catalog, you can use the INSERT statement to sink the data of a StarRocks table to that Unified Catalog table (currently only Parquet-formatted Unified Catalog tables are supported).

NOTE

You can grant and revoke privileges by using GRANT and REVOKE.

StarRocks supports sinking data only to Hive and Iceberg tables in unified catalogs.

Switch to a Hive Catalog and a database in it. Then, use INSERT INTO to insert data into a Hive or Iceberg table in that database:

INSERT {INTO | OVERWRITE} <table_name>
[ (column_name [, ...]) ]
{ VALUES ( { expression | DEFAULT } [, ...] ) [, ...] | query }

-- If you want to sink data to specified partitions, use the following syntax:
INSERT {INTO | OVERWRITE} <table_name>
PARTITION (par_col1=<value> [, par_col2=<value>...])
{ VALUES ( { expression | DEFAULT } [, ...] ) [, ...] | query }

For more information, see Sink data to a Hive table and Sink data to an Iceberg table.

The following example inserts three data rows to a Hive table named hive_table:

INSERT INTO hive_table
VALUES
    ("buy", 1, "2023-09-01"),
    ("sell", 2, "2023-09-02"),
    ("buy", 3, "2023-09-03");

Drop a table from a unified catalog

Similar to the internal tables of StarRocks, if you have the DROP privilege on a table created within a unified catalog, you can use the DROP TABLE statement to drop that table.

NOTE

You can grant and revoke privileges by using GRANT and REVOKE.

StarRocks supports dropping only Hive and Iceberg tables from unified catalogs.

Switch to a Hive Catalog and a database in it. Then, use DROP TABLE to drop a Hive or Iceberg table in that database:

DROP TABLE <table_name>

For more information, see Drop a Hive table and Drop an Iceberg table.

The following example drops a Hive table named hive_table:

DROP TABLE hive_table FORCE

Parameter	Required	Description
azure.blob.storage_account	Yes	The username of your Blob Storage account.
azure.blob.shared_key	Yes	The shared key of your Blob Storage account.

Unified catalog

Limits​

Usage notes​

Integration preparations​

AWS IAM​

HDFS​

Kerberos authentication​

Create a unified catalog​

Syntax​

Parameters​

catalog_name​

comment​

type​

MetastoreParams​

Hive metastore​

AWS Glue​

StorageCredentialParams​

AWS S3​

S3-compatible storage system​

Microsoft Azure Storage​

Azure Blob Storage​

Azure Data Lake Storage Gen2​

Azure Data Lake Storage Gen1​

Google GCS​

MetadataUpdateParams​

Examples​

HDFS​

AWS S3​

Instance profile-based authentication​

Assumed role-based authentication​

IAM user-based authentication​

S3-compatible storage system​

Microsoft Azure Storage​

Azure Blob Storage​

Azure Data Lake Storage Gen1​

Azure Data Lake Storage Gen2​

Google GCS​

View unified catalogs​

Switch to a Unified Catalog and a database in it​

Drop a unified catalog​

View the schema of a table from a unified catalog​

Query data from a unified catalog​

Load data from Hive, Iceberg, Hudi, or Delta Lake​

Create a database in a unified catalog​

Drop a database from a unified catalog​

Create a table in a unified catalog​

Sink data to a table in a unified catalog​

Drop a table from a unified catalog​

What did you think of this doc?

Limits

Usage notes

Integration preparations

AWS IAM

HDFS

Kerberos authentication

Create a unified catalog

Syntax

Parameters

catalog_name

comment

type

MetastoreParams

Hive metastore

AWS Glue

StorageCredentialParams

AWS S3

S3-compatible storage system

Microsoft Azure Storage

Azure Blob Storage

Azure Data Lake Storage Gen2

Azure Data Lake Storage Gen1

Google GCS

MetadataUpdateParams

Examples

HDFS

AWS S3

Instance profile-based authentication

Assumed role-based authentication

IAM user-based authentication

S3-compatible storage system

Microsoft Azure Storage

Azure Blob Storage

Azure Data Lake Storage Gen1

Azure Data Lake Storage Gen2

Google GCS

View unified catalogs

Switch to a Unified Catalog and a database in it

Drop a unified catalog

View the schema of a table from a unified catalog

Query data from a unified catalog

Load data from Hive, Iceberg, Hudi, or Delta Lake

Create a database in a unified catalog

Drop a database from a unified catalog

Create a table in a unified catalog

Sink data to a table in a unified catalog

Drop a table from a unified catalog