Iceberg catalog

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

Also, you can directly transform and load data from Iceberg by using INSERT INTO based on Iceberg catalogs. StarRocks supports Iceberg catalogs from v2.4 onwards.

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

• Object storage or distributed file system like AWS S3, other S3-compatible storage system, Microsoft Azure Storage, Google GCS, or HDFS

• 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 formats of Iceberg that StarRocks supports are Parquet and ORC:

  • Parquet files support the following compression formats: SNAPPY, LZ4, ZSTD, GZIP, and NO_COMPRESSION.
  • ORC files support the following compression formats: ZLIB, SNAPPY, LZO, LZ4, ZSTD, and NO_COMPRESSION.

• Iceberg catalogs support v1 tables, and support ORC-formatted v2 tables from StarRocks v3.0 onwards.

Integration preparations

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

AWS IAM

If your Iceberg 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.

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 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. After you set the username in these files, restart each FE and each BE to make the parameter settings take effect. You can set only one username for each StarRocks cluster.

• When you query Iceberg data, the FEs and BEs 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.
  • 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.

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 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. 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 an Iceberg catalog

Syntax

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

Parameters

catalog_name

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

type

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

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:

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

NOTE

Before querying Iceberg 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 parameter you need to configure in MetastoreParams.

Parameter	Required	Description
iceberg.catalog.type	Yes	The type of metastore that you use for your Iceberg 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:

  "iceberg.catalog.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:

  "iceberg.catalog.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:

  "iceberg.catalog.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
iceberg.catalog.type	Yes	The type of metastore that you use for your Iceberg 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. 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 for your Iceberg 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.

S3-compatible storage system

Iceberg catalogs support S3-compatible storage systems from v2.5 onwards.

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

"aws.s3.enable_ssl" = "{true | false}",
"aws.s3.enable_path_style_access" = "{true | false}",
"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

Iceberg catalogs support Microsoft Azure Storage from v3.0 onwards.

Azure Blob Storage

If you choose Blob Storage as storage for your Iceberg 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 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 Gen1

If you choose Data Lake Storage Gen1 as storage for your Iceberg 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.

• 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.

Azure Data Lake Storage Gen2

If you choose Data Lake Storage Gen2 as storage for your Iceberg 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.

• 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.

Google GCS

Iceberg catalogs support Google GCS from v3.0 onwards.

If you choose Google GCS as storage for your Iceberg 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.

Examples

The following examples create an Iceberg catalog named iceberg_catalog_hms or iceberg_catalog_glue, depending on the type of metastore you use, to query data from your Iceberg cluster.

HDFS

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

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

AWS S3

If you choose instance profile-based credential

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

  CREATE EXTERNAL CATALOG iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 Iceberg cluster, run a command like below:

  CREATE EXTERNAL CATALOG iceberg_catalog_glue
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 HIceberg cluster, run a command like below:

  CREATE EXTERNAL CATALOG iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 Iceberg cluster, run a command like below:

  CREATE EXTERNAL CATALOG iceberg_catalog_glue
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 Iceberg cluster, run a command like below:

  CREATE EXTERNAL CATALOG iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 Iceberg cluster, run a command like below:

  CREATE EXTERNAL CATALOG iceberg_catalog_glue
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
PROPERTIES
(
    "type" = "iceberg",
    "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
  PROPERTIES
  (
      "type" = "iceberg",
      "iceberg.catalog.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 iceberg_catalog_hms
    PROPERTIES
    (
        "type" = "iceberg",
        "iceberg.catalog.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 iceberg_catalog_hms
    PROPERTIES
    (
        "type" = "iceberg",
        "iceberg.catalog.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 Iceberg 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 an Iceberg catalog named iceberg_catalog_glue:

SHOW CREATE CATALOG iceberg_catalog_glue;

Switch to an Iceberg Catalog and a database in it

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

• Use SET CATALOG to specify an Iceberg 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 an Iceberg catalog and a database in it:

  USE <catalog_name>.<db_name>

Drop an Iceberg catalog

You can use DROP CATALOG to drop an external catalog.

The following example drops an Iceberg catalog named iceberg_catalog_glue:

DROP Catalog iceberg_catalog_glue;

View the schema of an Iceberg table

You can use one of the following syntaxes to view the schema of an Iceberg 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 an Iceberg table

1. Use SHOW DATABASES to view the databases in your Iceberg cluster:

   SHOW DATABASES FROM <catalog_name>

2. Switch to an Iceberg catalog and a database in it.

3. Use SELECT to query the destination table in the specified database:

   SELECT count(*) FROM <table_name> LIMIT 10

Load data from Iceberg

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 iceberg_table