Version: 4.0 Stable

Hudi catalog

A Hudi catalog is a kind of external catalog that enables you to query data from Apache Hudi without ingestion.

Also, you can directly transform and load data from Hudi by using INSERT INTO based on Hudi catalogs.

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

Object storage like AWS S3, Microsoft Azure Storage, or Google GCS
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.

Usage notes

The file format of Hudi that StarRocks supports is Parquet. Parquet files support the following compression formats: SNAPPY, LZ4, ZSTD, GZIP, and NO_COMPRESSION.
StarRocks provides complete support for Copy On Write (COW) tables and Merge On Read (MOR) tables from Hudi.

Integration preparations

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

Hive metastore

If your Hudi cluster uses Hive metastore as metastore, check that PhoenixAI can access the host of your Hive metastore.

note

In normal cases, you can take one of the following actions to enable integration between your PhoenixAI cluster and your Hive metastore:

Deploy your PhoenixAI cluster and your Hive metastore on the same VPC.
Configure a VPC peering connection between the VPC of your PhoenixAI cluster and the VPC of your Hive metastore.

Then, check the configurations of the security group of your Hive metastore to ensure that its inbound rules allow inbound traffic from your PhoenixAI cluster's security group and that its port range covers the default port 9083.

AWS IAM

If your Hudi cluster uses 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.

The following authentication methods are recommended:

Instance profile
Assumed role
IAM user

Of the above-mentioned three authentication methods, instance profile is the most widely used.

For more information, see Preparation for authentication in AWS IAM.

Microsoft Azure Storage

If your Hudi cluster uses Azure as storage, choose your suitable authentication method and make the required preparations such as adding role assignments. For more information, see Authenticate to Azure cloud storage.

Create a Hudi catalog

Syntax

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

Parameters

catalog_name

The name of the Hudi 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 Hudi catalog. This parameter is optional.

type

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

MetastoreParams

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

Hive metastore

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

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

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

Parameter	Required	Description
hive.metastore.type	Yes	The type of metastore that you use for your Hudi cluster. 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:

"hive.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:

"hive.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:

"hive.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
hive.metastore.type	Yes	The type of metastore that you use for your Hudi cluster. 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 method. 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.

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

AWS S3

If you choose AWS S3 as storage for your Hudi cluster, 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.

Microsoft Azure Storage

This section describes the parameters that you need to configure in StorageCredentialParams for integrating with various Azure cloud storage services by using various authentication methods. For more information about how to obtain the values of these parameters, see Authenticate to Azure cloud storage.

Azure Blob Storage

If you choose Blob Storage as storage for your Hudi cluster, 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 name 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 name 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 for your Hudi cluster, 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.

note

The managed identity must be the one used to deploy your PhoenixAI cluster, and its client ID is the one referenced in the data credential of the destination PhoenixAI cluster. The managed identity must be assigned the required read and write permissions (for example, Storage Blob Data Owner) on the storage account. The storage account you use for authentication must be the one used to store the data of your Hudi cluster.

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 name 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.

note

The service principal must be the one used to deploy your PhoenixAI cluster and must be assigned the required read and write permissions (for example, Storage Blob Data Owner) on the storage account. The storage account you use for authentication must be the one used to store the data of your Hudi cluster.

Azure Data Lake Storage Gen1

If you choose Data Lake Storage Gen1 as storage for your Hudi cluster, 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.

note

Google GCS

If you choose Google GCS as storage for your Hudi cluster, 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 Hudi. This parameter set is optional.

StarRocks implements the automatic asynchronous update policy by default.

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 Hudi is high, you can tune these parameters to further optimize the performance of automatic asynchronous updates.

NOTE

In most cases, if your Hudi data is updated at a granularity of 1 hour or less, the data update frequency is considered high.

Parameter	Required	Description
enable_metastore_cache	No	Specifies whether StarRocks caches the metadata of Hudi 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 Hudi 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 Hudi 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 Hudi 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 Hudi 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 Hudi tables or partitions cached in itself. Unit: seconds. Default value: `129600`, which is 36 hours.

Examples

The following examples create a Hudi catalog named hudi_catalog_hms or hudi_catalog_glue, depending on the type of metastore you use, to query data from your Hudi cluster.

AWS S3

If you choose instance profile-based credential

If you use Hive metastore in your Hudi cluster, run a command like below:

CREATE EXTERNAL CATALOG hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 in your Amazon EMR Hudi cluster, run a command like below:

CREATE EXTERNAL CATALOG hudi_catalog_glue
PROPERTIES
(
    "type" = "hudi",
    "hive.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"
);

If you choose assumed role-based credential

If you use Hive metastore in your Hudi cluster, run a command like below:

CREATE EXTERNAL CATALOG hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 in your Amazon EMR Hudi cluster, run a command like below:

CREATE EXTERNAL CATALOG hudi_catalog_glue
PROPERTIES
(
    "type" = "hudi",
    "hive.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"
);

If you choose IAM user-based credential

If you use Hive metastore in your Hudi cluster, run a command like below:

CREATE EXTERNAL CATALOG hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 in your Amazon EMR Hudi cluster, run a command like below:

CREATE EXTERNAL CATALOG hudi_catalog_glue
PROPERTIES
(
    "type" = "hudi",
    "hive.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"
);

Microsoft Azure Storage

Azure Blob Storage

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

CREATE EXTERNAL CATALOG hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 hudi_catalog_hms
PROPERTIES
(
    "type" = "hudi",
    "hive.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 Hudi 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 Hudi catalog named hudi_catalog_glue:

SHOW CREATE CATALOG hudi_catalog_glue;

Switch to a Hudi Catalog and a database in it

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

Use SET CATALOG to specify a Hudi 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 Hudi catalog and a database in it:
```
USE <catalog_name>.<db_name>
```

Drop a Hudi catalog

You can use DROP CATALOG to drop an external catalog.

The following example drops a Hudi catalog named hudi_catalog_glue:

DROP Catalog hudi_catalog_glue;

View the schema of a Hudi table

You can use one of the following syntaxes to view the schema of a Hudi table:

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 a Hudi table

Use SHOW DATABASES to view the databases in your Hudi cluster:
```
SHOW DATABASES FROM <catalog_name>
```
Switch to a Hudi 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 Hudi

Suppose you have an OLAP table named olap_tbl, you can transform and load data like below:

INSERT INTO default_catalog.olap_db.olap_tbl SELECT * FROM hudi_table

Manually or automatically update metadata cache

Manual update

By default, StarRocks caches the metadata of Hudi and automatically updates the metadata in asynchronous mode to deliver better performance. Additionally, after some schema changes or table updates are made on a Hudi table, you can also use REFRESH EXTERNAL TABLE to manually update its metadata, thereby ensuring that StarRocks can obtain up-to-date metadata at its earliest opportunity and generate appropriate execution plans:

REFRESH EXTERNAL TABLE <table_name> [PARTITION ('partition_name', ...)]

Appendix: Understand metadata automatic asynchronous update

Automatic asynchronous update is the default policy that StarRocks uses to update the metadata in Hudi catalogs.

By default (namely, when the enable_metastore_cache and enable_remote_file_cache parameters are both set to true), if a query hits a partition of a Hudi table, StarRocks automatically caches the metadata of the partition and the metadata of the underlying data files of the partition. The cached metadata is updated by using the lazy update policy.

For example, there is a Hudi table named table2, which has four partitions: p1, p2, p3, and p4. A query hits p1, and StarRocks caches the metadata of p1 and the metadata of the underlying data files of p1. Assume that the default time intervals to update and discard the cached metadata are as follows:

The time interval (specified by the metastore_cache_refresh_interval_sec parameter) to asynchronously update the cached metadata of p1 is 2 hours.
The time interval (specified by the remote_file_cache_refresh_interval_sec parameter) to asynchronously update the cached metadata of the underlying data files of p1 is 60 seconds.
The time interval (specified by the metastore_cache_ttl_sec parameter) to automatically discard the cached metadata of p1 is 24 hours.
The time interval (specified by the remote_file_cache_ttl_sec parameter) to automatically discard the cached metadata of the underlying data files of p1 is 36 hours.

The following figure shows the time intervals on a timeline for easier understanding.

Timeline for updating and discarding cached metadata

Then StarRocks updates or discards the metadata in compliance with the following rules:

If another query hits p1 again and the current time from the last update is less than 60 seconds, StarRocks does not update the cached metadata of p1 or the cached metadata of the underlying data files of p1.
If another query hits p1 again and the current time from the last update is more than 60 seconds, StarRocks updates the cached metadata of the underlying data files of p1.
If another query hits p1 again and the current time from the last update is more than 2 hours, StarRocks updates the cached metadata of p1.
If p1 has not been accessed within 24 hours from the last update, StarRocks discards the cached metadata of p1. The metadata will be cached at the next query.
If p1 has not been accessed within 36 hours from the last update, StarRocks discards the cached metadata of the underlying data files of p1. The metadata will be cached at the next query.

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

Usage notes​

Integration preparations​

Hive metastore​

AWS IAM​

Microsoft Azure Storage​

Create a Hudi catalog​

Syntax​

Parameters​

catalog_name​

comment​

type​

MetastoreParams​

Hive metastore​

AWS Glue​

StorageCredentialParams​

AWS S3​

Microsoft Azure Storage​

Azure Blob Storage​

Azure Data Lake Storage Gen2​

Azure Data Lake Storage Gen1​

Google GCS​

MetadataUpdateParams​

Examples​

AWS S3​

If you choose instance profile-based credential​

If you choose assumed role-based credential​

If you choose IAM user-based credential​

Microsoft Azure Storage​

Azure Blob Storage​

Azure Data Lake Storage Gen1​

Azure Data Lake Storage Gen2​

Google GCS​

View Hudi catalogs​

Switch to a Hudi Catalog and a database in it​

Drop a Hudi catalog​

View the schema of a Hudi table​

Query a Hudi table​

Load data from Hudi​

Manually or automatically update metadata cache​

Manual update​

Appendix: Understand metadata automatic asynchronous update​

Usage notes

Integration preparations

Hive metastore

AWS IAM

Microsoft Azure Storage

Create a Hudi catalog

Syntax

Parameters

catalog_name

comment

type

MetastoreParams

Hive metastore

AWS Glue

StorageCredentialParams

AWS S3

Microsoft Azure Storage

Azure Blob Storage

Azure Data Lake Storage Gen2

Azure Data Lake Storage Gen1

Google GCS

MetadataUpdateParams

Examples

AWS S3

If you choose instance profile-based credential

If you choose assumed role-based credential

If you choose IAM user-based credential

Microsoft Azure Storage

Azure Blob Storage

Azure Data Lake Storage Gen1

Azure Data Lake Storage Gen2

Google GCS

View Hudi catalogs

Switch to a Hudi Catalog and a database in it

Drop a Hudi catalog

View the schema of a Hudi table

Query a Hudi table

Load data from Hudi

Manually or automatically update metadata cache

Manual update

Appendix: Understand metadata automatic asynchronous update