Version: Stable-3.1

Hive catalog

A Hive catalog is a kind of external catalog that enables you to query data from Apache Hive™ without ingestion. Also, you can directly transform and load data from Hive by using INSERT INTO based on Hive catalogs.

StarRocks supports Hive catalogs from v2.4 onwards, and from v3.1 onwards StarRocks supports accessing views that are created on tables within Hive catalogs.

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

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

NOTE

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

Usage notes

The file formats of Hive that StarRocks supports are Parquet, ORC, and Textfile:
- Parquet files support the following compression formats: SNAPPY, LZ4, ZSTD, GZIP, and NO_COMPRESSION. From v3.1.5 onwards, Parquet files also support the LZO compression format.
- ORC files support the following compression formats: ZLIB, SNAPPY, LZO, LZ4, ZSTD, and NO_COMPRESSION.
- Textfile files support the LZO compression format from v3.1.5 onwards.
The data types of Hive that StarRocks does not support are INTERVAL, BINARY, and UNION. Additionally, StarRocks does not support the MAP and STRUCT data types for Textfile-formatted Hive tables.
You can only use Hive catalogs to query data. You cannot use Hive catalogs to drop, delete, or insert data into your Hive cluster.

Integration preparations

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

AWS IAM

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

NOTE

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

Kerberos authentication

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

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

Create a Hive catalog

Syntax

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

Parameters

catalog_name

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

type

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

GeneralParams

A set of general parameters.

The following table describes the parameters you can configure in GeneralParams.

Parameter	Required	Description
enable_recursive_listing	No	Specifies whether StarRocks reads data from a table and its partitions and from the subdirectories within the physical locations of the table and its partitions. Valid values: `true` and `false`. Default value: `true`. The value `true` specifies to recursively list subdirectories, and the value `false` specifies to ignore subdirectories.

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>"

NOTE

Before querying Hive 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
hive.metastore.type	Yes	The type of metastore that you use for your Hive 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 Hive 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. 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 Hive 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

Hive 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 Hive cluster, configure StorageCredentialParams as follows to ensure a successful integration:

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

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

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

Microsoft Azure Storage

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

Azure Blob Storage

If you choose Blob Storage as storage for your Hive 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 Gen2

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

Azure Data Lake Storage Gen1

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

Google GCS

Hive catalogs support Google GCS from v3.0 onwards.

If you choose Google GCS as storage for your Hive 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 Hive. 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 Hive is high, you can tune these parameters to further optimize the performance of automatic asynchronous updates.

NOTE

In most cases, if your Hive 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 Hive tables. Valid values: `true` and `false`. Default value: `true`. The value `true` enables the cache, and the value `false` disables the cache.
enable_remote_file_cache	No	Specifies whether StarRocks caches the metadata of the underlying data files of Hive tables or partitions. Valid values: `true` and `false`. Default value: `true`. The value `true` enables the cache, and the value `false` disables the cache.
metastore_cache_refresh_interval_sec	No	The time interval at which StarRocks asynchronously updates the metadata of Hive tables or partitions cached in itself. Unit: seconds. Default value: `7200`, which is 2 hours.
remote_file_cache_refresh_interval_sec	No	The time interval at which StarRocks asynchronously updates the metadata of the underlying data files of Hive tables or partitions cached in itself. Unit: seconds. Default value: `60`.
metastore_cache_ttl_sec	No	The time interval at which StarRocks automatically discards the metadata of Hive tables or partitions cached in itself. Unit: seconds. Default value: `86400`, which is 24 hours.
remote_file_cache_ttl_sec	No	The time interval at which StarRocks automatically discards the metadata of the underlying data files of Hive tables or partitions cached in itself. Unit: seconds. Default value: `129600`, which is 36 hours.
enable_cache_list_names	No	Specifies whether StarRocks caches Hive partition names. Valid values: `true` and `false`. Default value: `true`. The value `true` enables the cache, and the value `false` disables the cache.

Examples

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

HDFS

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

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

AWS S3

Instance profile-based authentication

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

CREATE EXTERNAL CATALOG hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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 Hive cluster, run a command like below:

CREATE EXTERNAL CATALOG hive_catalog_glue
PROPERTIES
(
    "type" = "hive",
    "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"
);

Assumed role-based authentication

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

CREATE EXTERNAL CATALOG hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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 Hive cluster, run a command like below:

CREATE EXTERNAL CATALOG hive_catalog_glue
PROPERTIES
(
    "type" = "hive",
    "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"
);

IAM user-based authentication

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

CREATE EXTERNAL CATALOG hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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 Hive cluster, run a command like below:

CREATE EXTERNAL CATALOG hive_catalog_glue
PROPERTIES
(
    "type" = "hive",
    "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"
);

S3-compatible storage system

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

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

Microsoft Azure Storage

Azure Blob Storage

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

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

Google GCS

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

CREATE EXTERNAL CATALOG hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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 hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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" = "<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 hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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 hive_catalog_hms
PROPERTIES
(
    "type" = "hive",
    "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 Hive 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 Hive catalog named hive_catalog_glue:

SHOW CREATE CATALOG hive_catalog_glue;

Switch to a Hive Catalog and a database in it

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

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

Drop a Hive catalog

You can use DROP CATALOG to drop an external catalog.

The following example drops a Hive catalog named hive_catalog_glue:

DROP Catalog hive_catalog_glue;

View the schema of a Hive table

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

Use SHOW DATABASES to view the databases in your Hive cluster:
```
SHOW DATABASES FROM <catalog_name>
```
Switch to a Hive Catalog and a database in it.
Use SELECT to query the destination table in the specified database:
```
SELECT count(*) FROM <table_name> LIMIT 10
```

Load data from Hive

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 hive_table

Grant privileges on Hive tables and views

You can use the GRANT statement to grant the privileges on all tables and views within a Hive catalog to a specific role. The command syntax is as follows:

GRANT SELECT ON ALL TABLES IN ALL DATABASES TO ROLE <role_name>

For example, use the following commands to create a role named hive_role_table, switch to the Hive catalog hive_catalog, and then grant the role hive_role_table the privilege to query all tables and views within the Hive catalog hive_catalog:

-- Create a role named hive_role_table.
CREATE ROLE hive_role_table;

-- Switch to the Hive catalog hive_catalog.
SET CATALOG hive_catalog;

-- Grant the role hive_role_table the privilege to query all tables and views within the Hive catalog hive_catalog.
GRANT SELECT ON ALL TABLES IN ALL DATABASES TO ROLE hive_role_table;

Manually or automatically update metadata cache

Manual update

By default, StarRocks caches the metadata of Hive and automatically updates the metadata in asynchronous mode to deliver better performance. Additionally, after some schema changes or table updates are made on a Hive 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', ...)]

You need to manually update metadata in the following situations:

A data file in an existing partition is changed, for example, by running the INSERT OVERWRITE ... PARTITION ... command.
Schema changes are made on a Hive table.
An existing Hive table is deleted by using the DROP statement, and a new Hive table with the same name as the deleted Hive table is created.
You have specified "enable_cache_list_names" = "true" in PROPERTIES at the creation of your Hive catalog, and you want to query new partitions that you just created on your Hive cluster.

NOTE

From v2.5.5 onwards, StarRocks provides the periodic Hive metadata cache refresh feature. For more information, see the below "Periodically refresh metadata cache" section of this topic. After you enable this feature, StarRocks refreshes your Hive metadata cache every 10 minutes by default. Therefore, manual updates are not needed in most cases. You need to perform a manual update only when you want to query new partitions immediately after the new partitions are created on your Hive cluster.

Note that the REFRESH EXTERNAL TABLE refreshes only the tables and partitions cached in your FEs.

Periodically refresh metadata cache

From v2.5.5 onwards, StarRocks can periodically refresh the cached metadata of the frequently accessed Hive catalogs to perceive data changes. You can configure the Hive metadata cache refresh through the following FE parameters:

Configuration item	Default	Description
enable_background_refresh_connector_metadata	`true` in v3.0 `false` in v2.5	Whether to enable the periodic Hive metadata cache refresh. After it is enabled, StarRocks polls the metastore (Hive Metastore or AWS Glue) of your Hive cluster, and refreshes the cached metadata of the frequently accessed Hive catalogs to perceive data changes. `true` indicates to enable the Hive metadata cache refresh, and `false` indicates to disable it. This item is an FE dynamic parameter. You can modify it using the ADMIN SET FRONTEND CONFIG command.
background_refresh_metadata_interval_millis	`600000` (10 minutes)	The interval between two consecutive Hive metadata cache refreshes. Unit: millisecond. This item is an FE dynamic parameter. You can modify it using the ADMIN SET FRONTEND CONFIG command.
background_refresh_metadata_time_secs_since_last_access_secs	`86400` (24 hours)	The expiration time of a Hive metadata cache refresh task. For the Hive catalog that has been accessed, if it has not been accessed for more than the specified time, StarRocks stops refreshing its cached metadata. For the Hive catalog that has not been accessed, StarRocks will not refresh its cached metadata. Unit: second. This item is an FE dynamic parameter. You can modify it using the ADMIN SET FRONTEND CONFIG command.

Using the periodic Hive metadata cache refresh feature and the metadata automatic asynchronous update policy together significantly accelerates data access, reduces the read load from external data sources, and improves query performance.

Appendix: Understand metadata automatic asynchronous update

Automatic asynchronous update is the default policy that StarRocks uses to update the metadata in Hive 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 Hive 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 Hive 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 username of your Blob Storage account.
azure.blob.shared_key	Yes	The shared key of your Blob Storage account.

Hive catalog

Usage notes​

Integration preparations​

AWS IAM​

HDFS​

Kerberos authentication​

Create a Hive catalog​

Syntax​

Parameters​

catalog_name​

comment​

type​

GeneralParams​

MetastoreParams​

Hive metastore​

AWS Glue​

StorageCredentialParams​

AWS S3​

S3-compatible storage system​

Microsoft Azure Storage​

Azure Blob Storage​

Azure Data Lake Storage Gen2​

Azure Data Lake Storage Gen1​

Google GCS​

MetadataUpdateParams​

Examples​

HDFS​

AWS S3​

Instance profile-based authentication​

Assumed role-based authentication​

IAM user-based authentication​

S3-compatible storage system​

Microsoft Azure Storage​

Azure Blob Storage​

Azure Data Lake Storage Gen1​

Azure Data Lake Storage Gen2​

Google GCS​

View Hive catalogs​

Switch to a Hive Catalog and a database in it​

Drop a Hive catalog​

View the schema of a Hive table​

Query a Hive table​

Load data from Hive​

Grant privileges on Hive tables and views​

Manually or automatically update metadata cache​

Manual update​

Periodically refresh metadata cache​

Appendix: Understand metadata automatic asynchronous update​

What did you think of this doc?

Usage notes

Integration preparations

AWS IAM

HDFS

Kerberos authentication

Create a Hive catalog

Syntax

Parameters

catalog_name

comment

type

GeneralParams

MetastoreParams

Hive metastore

AWS Glue

StorageCredentialParams

AWS S3

S3-compatible storage system

Microsoft Azure Storage

Azure Blob Storage

Azure Data Lake Storage Gen2

Azure Data Lake Storage Gen1

Google GCS

MetadataUpdateParams

Examples

HDFS

AWS S3

Instance profile-based authentication

Assumed role-based authentication

IAM user-based authentication

S3-compatible storage system

Microsoft Azure Storage

Azure Blob Storage

Azure Data Lake Storage Gen1

Azure Data Lake Storage Gen2

Google GCS

View Hive catalogs

Switch to a Hive Catalog and a database in it

Drop a Hive catalog

View the schema of a Hive table

Query a Hive table

Load data from Hive

Grant privileges on Hive tables and views

Manually or automatically update metadata cache

Manual update

Periodically refresh metadata cache

Appendix: Understand metadata automatic asynchronous update