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Iceberg catalog

An Iceberg catalog is an external catalog that enables you to query data from Apache Iceberg without ingestion. To ensure successful SQL workloads on your Iceberg cluster, your CelerData cluster must be able to access the storage system and metastore of your Iceberg cluster. CelerData supports the following storage systems and metastores:

  • Object storage like AWS S3

  • Metastore like Hive metastore (HMS) 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 CelerData 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.

  • In addition to v1 tables, Iceberg catalogs support ORC-formatted v2 tables and Parquet-formatted v2 tables.

Preparations​

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

Hive metastore​

If your Iceberg cluster uses Hive metastore as metastore, check that CelerData 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 CelerData cluster and your Hive metastore:

  • Deploy your CelerData cluster and your Hive metastore on the same VPC.
  • Configure a VPC peering connection between the VPC of your CelerData 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 CelerData cluster's security group and that its port range covers the default port 9083.

AWS​

If your Iceberg cluster uses AWS S3 as storage or AWS Glue as metastore, choose your suitable authentication method and make the required preparations such as creating IAM roles or users and adding IAM policies to the specified IAM roles or users to ensure that your CelerData cluster can access these AWS resources. For more information, see Authenticate to AWS resources > Preparations.

Microsoft Azure Storage​

If your Iceberg 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 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 CelerData 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>"

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

ParameterRequiredDescription
iceberg.catalog.typeYesThe type of metastore that you use for your Iceberg cluster. Set the value to hive.
hive.metastore.urisYesThe 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.

ParameterRequiredDescription
iceberg.catalog.typeYesThe type of metastore that you use for your Iceberg cluster. Set the value to glue.
aws.glue.use_instance_profileYesSpecifies 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_arnNoThe 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.regionYesThe region in which your AWS Glue Data Catalog resides. Example: us-west-1.
aws.glue.access_keyNoThe 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_keyNoThe 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 your CelerData cluster integrates with your object storage.

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.

ParameterRequiredDescription
aws.s3.use_instance_profileYesSpecifies 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_arnNoThe 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.regionYesThe region in which your AWS S3 bucket resides. Example: us-west-1.
aws.s3.access_keyNoThe 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_keyNoThe 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 Iceberg cluster, take one of the following actions:

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

    "azure.blob.storage_account" = "<blob_storage_account_name>",
    "azure.blob.shared_key" = "<blob_storage_account_shared_key>"

    The following table describes the parameters.

    ParameterDescription
    azure.blob.storage_accountThe name of your Blob storage account.
    azure.blob.shared_keyThe shared key (access key) of your Blob storage account.

    NOTICE

    Note that the storage account you use for authentication must be the one used to store the data of your Iceberg cluster.

  • To use 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.

    ParameterDescription
    azure.blob.storage_accountThe name of your Blob storage account.
    azure.blob.containerThe name of the Blob container that stores your data within your Blob storage account.
    azure.blob.sas_tokenThe SAS token that is used to access your Blob storage account.

    NOTICE

    Note that the storage account you use for authentication must be the one used to store the data of your Iceberg cluster.

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 use 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.

    ParameterDescription
    azure.adls2.oauth2_use_managed_identitySpecifies whether to enable the Managed Identity authentication method. Set the value to true.
    azure.adls2.oauth2_tenant_idThe ID of the tenant of your ADLS Gen2 storage account.
    azure.adls2.oauth2_client_idThe client ID of the managed identity that is referenced in the data credential of the destination CelerData cluster.

    NOTICE

    Note that the storage account you use for authentication must be the one used to store the data of your Iceberg cluster, and the managed identity must be the one used to deploy your CelerData cluster and be assigned the required read and write permissions (for example, Storage Blob Data Owner) to the storage account.

  • To use 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.

    ParameterDescription
    azure.adls2.storage_accountThe name of your ADLS Gen2 storage account.
    azure.adls2.shared_keyThe shared key (access key) of your ADLS Gen2 storage account.

    NOTICE

    Note that the storage account you use for authentication must be the one used to store the data of your Iceberg cluster.

  • To use 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.

    ParameterDescription
    azure.adls2.oauth2_client_idThe application (client) ID of the service principal.
    azure.adls2.oauth2_client_secretThe value of the client secret of the service principal.
    azure.adls2.oauth2_client_endpointThe OAuth 2.0 token endpoint (v1) of the service principal.

    NOTICE

    Note that the storage account you use for authentication must be the one used to store the data of your Iceberg cluster, and the service principal must be the one used to deploy your CelerData cluster and be assigned the required read and write permissions (for example, Storage Blob Data Owner) to the 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 use the Managed Service Identity authentication method, configure StorageCredentialParams as follows:

    "azure.adls1.use_managed_service_identity" = "true"

    The following table describes the parameters.

    ParameterDescription
    azure.adls1.use_managed_service_identitySpecifies whether to enable the Managed Service Identity authentication method. Set the value to true.

  • To use 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.

    ParameterDescription
    azure.adls1.oauth2_client_idThe application (client) ID of the service principal.
    azure.adls1.oauth2_credentialThe value of the client secret of the service principal.
    azure.adls1.oauth2_endpointThe OAuth 2.0 token endpoint (v1) of the service principal or application.

    NOTICE

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

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.

AWS S3​

Instance profile-based authentication​

  • 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"
    );
Assumed role-based authentication​

  • 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"
    );
IAM user-based authentication​

  • 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"
    );

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 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>"
    );
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>"
    );

View Iceberg catalogs​

You can use SHOW CATALOGS to query all catalogs in the current CelerData 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 <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

Create an Iceberg database​

Similar to the internal catalog of CelerData, if you have the CREATE DATABASE privilege on an Iceberg catalog, you can use the CREATE DATABASE statement to create databases in that Iceberg catalog.

NOTE

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

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

You can use the location parameter to specify the file path in which you want to create the database. If you do not specify the location parameter, CelerData creates the database in the default file path of the Iceberg catalog.

The prefix varies based on the storage system you use:

Storage systemPrefix value
HDFShdfs
Google GCSgs
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 Gen1adl
Azure Data Lake Storage Gen2
  • If your storage account allows access over HTTP, theprefix 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 an Iceberg database​

Similar to the internal databases of CelerData, if you have the DROP privilege on an Iceberg database, you can use the DROP DATABASE statement to drop that Iceberg database. You can only drop empty databases.

NOTE

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

When you drop an Iceberg database, the database's file path on your cloud storage will not be dropped along with the database.

Switch to an Iceberg catalog, and then use the following statement to drop an Iceberg database in that catalog:

DROP DATABASE <database_name>

Create an Iceberg table​

Similar to the internal databases of CelerData, if you have the CREATE TABLE privilege on an Iceberg database, you can use the CREATE TABLE or CREATE TABLE AS SELECT (CTAS) statement to create a table in that Iceberg database.

NOTE

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

Switch to an Iceberg catalog and a database in it, and then use the following syntax to create an Iceberg table in that database.

Syntax​

CREATE TABLE [IF NOT EXISTS] [database.]table_name
(column_definition1[, column_definition2, ...
partition_column_definition1,partition_column_definition2...])
[partition_desc]
[PROPERTIES ("key" = "value", ...)]
[AS SELECT query]

Parameters​

column_definition​

The syntax of column_definition is as follows:

col_name col_type [COMMENT 'comment']

The following table describes the parameters.

ParameterDescription
col_nameThe name of the column.
col_typeThe data type of the column. The following data types are supported: TINYINT, SMALLINT, INT, BIGINT, FLOAT, DOUBLE, DECIMAL, DATE, DATETIME, CHAR, VARCHAR[(length)], ARRAY, MAP, and STRUCT. The LARGEINT, HLL, and BITMAP data types are not supported.

NOTICE

All non-partition columns must use NULL as the default value. This means that you must specify DEFAULT "NULL" for each of the non-partition columns in the table creation statement. Additionally, partition columns must be defined following non-partition columns and cannot use NULL as the default value.

partition_desc​

The syntax of partition_desc is as follows:

PARTITION BY (par_col1[, par_col2...])

Currently CelerData only supports identity transforms, which means that CelerData creates a partition for each unique partition value.

NOTICE

Partition columns must be defined following non-partition columns. Partition columns support all data types excluding FLOAT, DOUBLE, DECIMAL, and DATETIME and cannot use NULL as the default value.

properties​

You can specify the table attributes in the "key" = "value" format in properties. See Iceberg table attributes.

The following table describes a few key properties.

PropertyDescription
locationThe file path in which you want to create the Iceberg table. When you use HMS as metastore, you do not need to specify the location parameter, because StarRocks will create the table in the default file path of the current Iceberg catalog. When you use AWS Glue as metastore:
  • If you have specified the location parameter for the database in which you want to create the table, you do not need to specify the location parameter for the table. As such, the table defaults to the file path of the database to which it belongs.
  • If you have not specified the location for the database in which you want to create the table, you must specify the location parameter for the table.
file_formatThe file format of the Iceberg table. Only the Parquet format is supported. Default value: parquet.
compression_codecThe compression algorithm used for the Iceberg table. The supported compression algorithms are SNAPPY, GZIP, ZSTD, and LZ4. Default value: gzip.

Examples​

  1. Create a non-partitioned table named unpartition_tbl. The table consists of two columns, id and score, as shown below:

    CREATE TABLE unpartition_tbl
    (
        id int,
        score double
    );

  2. Create a partitioned table named partition_tbl_1. The table consists of three columns, action, id, and dt, of which id and dt are defined as partition columns, as shown below:

    CREATE TABLE partition_tbl_1
    (
        action varchar(20),
        id int,
        dt date
    )
    PARTITION BY (id,dt);

  3. Query an existing table named partition_tbl_1, and create a partitioned table named partition_tbl_2 based on the query result of partition_tbl_1. For partition_tbl_2, id and dt are defined as partition columns, as shown below:

    CREATE TABLE partition_tbl_2
    PARTITION BY (k1, k2)
    AS SELECT * from partition_tbl_1;

Sink data to an Iceberg table​

Similar to the internal tables of CelerData, if you have the INSERT privilege on an Iceberg table, you can use the INSERT statement to sink the data of a CelerData table to that Iceberg table (currently only Parquet-formatted Iceberg tables are supported).

NOTE

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

Switch to an Iceberg catalog and a database in it, and then use the following syntax to sink the data of StarRocks table to a Parquet-formatted Iceberg table in that database.

Syntax​

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 }

NOTICE

Partition columns do not allow NULL values. Therefore, you must make sure that no empty values are loaded into the partition columns of the Iceberg table.

Parameters​

ParameterDescription
INTOTo append the data of the CelerData table to the Iceberg table.
OVERWRITETo overwrite the existing data of the Iceberg table with the data of the CelerData table.
column_nameThe name of the destination column to which you want to load data. You can specify one or more columns. If you specify multiple columns, separate them with commas (,). You can only specify columns that actually exist in the Iceberg table, and the destination columns that you specify must include the partition columns of the Iceberg table. The destination columns you specify are mapped one on one in sequence to the columns of the CelerData table, regardless of what the destination column names are. If no destination columns are specified, the data is loaded into all columns of the Iceberg table. If a non-partition column of the CelerData table cannot be mapped to any column of the Iceberg table, CelerData writes the default value NULL to the Iceberg table column. If the INSERT statement contains a query statement whose returned column types differ from the data types of the destination columns, CelerData performs an implicit conversion on the mismatched columns. If the conversion fails, a syntax parsing error will be returned.
expressionExpression that assigns values to the destination column.
DEFAULTAssigns a default value to the destination column.
queryQuery statement whose result will be loaded into the Iceberg table. It can be any SQL statement supported by CelerData.
PARTITIONThe partitions into which you want to load data. You must specify all partition columns of the Iceberg table in this property. The partition columns that you specify in this property can be in a different sequence than the partition columns that you have defined in the table creation statement. If you specify this property, you cannot specify the column_name property.

Examples​

  1. Insert three data rows into the partition_tbl_1 table:

    INSERT INTO partition_tbl_1
    VALUES
        ("buy", 1, "2023-09-01"),
        ("sell", 2, "2023-09-02"),
        ("buy", 3, "2023-09-03");

  2. Insert the result of a SELECT query, which contains simple computations, into the partition_tbl_1 table:

    INSERT INTO partition_tbl_1 (id, action, dt) SELECT 1+1, 'buy', '2023-09-03';

  3. Insert the result of a SELECT query, which reads data from the partition_tbl_1 table, into the same table:

    INSERT INTO partition_tbl_1 SELECT 'buy', 1, date_add(dt, INTERVAL 2 DAY)
    FROM partition_tbl_1
    WHERE id=1;

  4. Insert the result of a SELECT query into the partitions that meet two conditions, dt='2023-09-01' and id=1, of the partition_tbl_2 table:

    INSERT INTO partition_tbl_2 SELECT 'order', 1, '2023-09-01';

    Or

    INSERT INTO partition_tbl_2 partition(dt='2023-09-01',id=1) SELECT 'order';

  5. Overwrite all action column values in the partitions that meet two conditions, dt='2023-09-01' and id=1, of the partition_tbl_1 table with close:

    INSERT OVERWRITE partition_tbl_1 SELECT 'close', 1, '2023-09-01';

    Or

    INSERT OVERWRITE partition_tbl_1 partition(dt='2023-09-01',id=1) SELECT 'close';

Drop an Iceberg table​

Similar to the internal tables of CelerData, if you have the DROP privilege on an Iceberg table, you can use the DROP TABLE statement to drop that Iceberg table.

NOTE

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

When you drop an Iceberg table, the table's file path and data on your cloud storage will not be dropped along with the table.

When you forcibly drop an Iceberg table (namely, with the FORCE keyword specified in the DROP TABLE statement), the table's data on your cloud storage will be dropped along with the table, but the table's file path is retained.

Switch to an Iceberg catalog and a database in it, and then use the following statement to drop an Iceberg table in that database.

DROP TABLE <table_name> [FORCE];