dbt
dbt-starrocks
enables the use of dbt
to transform data in StarRocks using dbt's modeling patterns and best practices.
dbt-starrocks
GitHub repo.
Supported featuresβ
Supported featuresβ
StarRocks >= 3.1 | StarRocks >= 3.4 | Feature |
---|---|---|
β | β | Table materialization |
β | β | View materialization |
β | β | Materialized View materialization |
β | β | Incremental materialization |
β | β | Primary Key Model |
β | β | Sources |
β | β | Custom data tests |
β | β | Docs generate |
β | β | Expression Partition |
β | β | Kafka |
β | β | Dynamic Overwrite |
* | β | Submit task |
β | β | Microbatch (Insert Overwrite) |
β | β | Microbatch (Dynamic Overwrite) |
*
Verify the specific submit task
support for your version, see SUBMIT TASK
Installationβ
Install the StarRocks DBT adapter using pip:
pip install dbt-starrocks
Verify Installationβ
Verify the installation by checking the version:
dbt --version
This should list starrocks
under plugins.
Configurationβ
Profilesβ
Create or update profiles.yml
with StarRocks-specific settings.
starrocks_project:
target: dev
outputs:
dev:
type: starrocks
host: your-starrocks-host.com
port: 9030
schema: your_database
username: your_username
password: your_password
catalog: test_catalog
Parametersβ
type
β
Description: The specific adapter to use, this must be set to starrocks
Required?: Required
Example: starrocks
host
β
Description: The hostname to connect to
Required?: Required
Example: 192.168.100.28
port
β
Description: The port to use
Required?: Required
Example: 9030
catalog
β
Description: Specify the catalog to build models into
Required?: Optional
Example: default_catalog
schema
β
Description: Specify the schema (database in StarRocks) to build models into
Required?: Required
Example: analytics
username
β
Description: The username to use to connect to the server
Required?: Required
Example: dbt_admin
password
β
Description: The password to use for authenticating to the server
Required?: Required
Example: correct-horse-battery-staple
version
β
Description: Let Plugin try to go to a compatible starrocks version
Required?: Optional
Example: 3.1.0
use_pure
β
Description: set to "true" to use C extensions
Required?: Optional
Example: true
is_async
β
Description: "true" to submit suitable tasks as etl tasks.
Required?: Optional
Example: true
async_query_timeout
β
Description: Sets the query_timeout
value when submitting a task to StarRocks
Required?: Optional
Example: 300
Sourcesβ
Create or update sources.yml
sources:
- name: your_source
database: your_sr_catalog
schema: your_sr_database
tables:
- name: your_table
If the catalog is not specified in the schema, it will default to the catalog defined in the profile. Using the profile from earlier, if catalog is not defined, the model will assume the source is located at test_catalog.your_sr_database
.
Materializationsβ
Tableβ
Basic Table Configuration
{{ config(
materialized='table',
engine='OLAP',
keys=['id', 'name', 'created_date'],
table_type='PRIMARY',
distributed_by=['id'],
buckets=3,
partition_by=['created_date'],
properties=[
{"replication_num": "1"}
]
) }}
SELECT
id,
name,
email,
created_date,
last_modified_date
FROM {{ source('your_source', 'users') }}
Configuration Optionsβ
- engine: Storage engine (default:
OLAP
) - keys: Columns that define the sort key
- table_type: Table model type
PRIMARY
: Primary key model (supports upserts and deletes)DUPLICATE
: Duplicate key model (allows duplicate rows)UNIQUE
: Unique key model (enforces uniqueness)
distributed_by
: Columns for hash distributionbuckets
: Number of buckets for data distribution (leave empty for auto bucketing)partition_by
: Columns for table partitioningpartition_by_init
: Initial partition definitionsproperties
: Additional StarRocks table properties
Tables in External Catalogsβ
Read from External into StarRocksβ
This example creates a materialized table in StarRocks containing aggregated data from an external Hive catalog.
Configure the external catalog if it does not already exist:
CREATE EXTERNAL CATALOG `hive_external`
PROPERTIES (
"hive.metastore.uris" = "thrift://127.0.0.1:8087",
"type"="hive"
);
{{ config(
materialized='table',
keys=['product_id', 'order_date'],
distributed_by=['product_id'],
partition_by=['order_date']
) }}
-- Aggregate data from Hive external catalog into StarRocks table
SELECT
h.product_id,
h.order_date,
COUNT(*) as order_count,
SUM(h.amount) as total_amount,
MAX(h.last_updated) as last_updated
FROM {{ source('hive_external', 'orders') }} h
GROUP BY
h.product_id,
h.order_date
Write to Externalβ
{{
config(
materialized='table',
on_table_exists = 'replace',
partition_by=['order_date'],
properties={},
catalog='external_catalog',
database='test_db'
)
}}
SELECT * FROM {{ source('iceberg_external', 'orders') }}
The configuration for materialization to external catalogs supports fewer options. on_table_exist
s, partition_by
, and properties
are supported. If catalog
and database
are not set, the defaults from the profile will be used.
Incrementalβ
Incremental materializations are supported in StarRocks as well:
{{ config(
materialized='incremental',
unique_key='id',
table_type='PRIMARY',
keys=['id'],
distributed_by=['id'],
incremental_strategy='default'
) }}
SELECT
id,
user_id,
event_name,
event_timestamp,
properties
FROM {{ source('raw', 'events') }}
{% if is_incremental() %}
WHERE event_timestamp > (SELECT MAX(event_timestamp) FROM {{ this }})
{% endif %}
Incremental Strategiesβ
dbt-starrocks
supports multiple incremental strategies:
append
(default): Simply appends new records without deduplicationinsert_overwrite
: Overwrites table partitions with insertiondynamic_overwrite
: Overwrites, creates, and writes table partitions
For more information about which overwrite strategy to use, see the INSERT documentation.
Currently, incremental merge is not supported.
Troubleshootingβ
- Before using external catalogs in dbt, you must create them in StarRocks. There is documentation on that here.
- External sources should be accessed using the
{{ source('external_source_name', 'table_name' }}
macro. dbt seed
was not tested for external catalogs and is not currently supported.- In order for
dbt
to create models in external databases that do not currently exist, the location of the models must be set through properties. - External models need to define the location they are stored at. This location will be defined if the destination database exists and sets the location property. Otherwise, the location needs to be set.
- We will currently only support creating external models in databases that already exist.