dbt-clickzetta
The dbt adapter for ClickZetta Lakehouse.
Installation
# SQL models only (default)
pip install dbt-clickzetta
# Python models (requires ZettaPark)
pip install "dbt-clickzetta[python]"
Requires Python 3.10+ (3.12 recommended) and dbt-core 1.8+.
Note on versions: The legacy
dbt-clickzetta 0.2.xseries requires dbt-core ~1.5 and is no longer maintained. Usedbt-clickzetta >= 1.6.
Quickstart
1. Configure profiles.yml
my_project:
target: dev
outputs:
dev:
type: clickzetta
service: cn-shanghai-alicloud.api.clickzetta.com
instance: your_instance
workspace: your_workspace
username: your_username
password: your_password
schema: your_schema
vcluster: default
query_tag: "dbt_{{ target.name }}" # optional
2. Test connection
dbt debug
3. Run your project
dbt run
dbt test
dbt docs generate
See the examples/ directory for complete, runnable examples.
→ 完整功能文档
Supported Features
| Feature | Description | Docs |
|---|---|---|
table / view / ephemeral |
Standard dbt materializations | materializations.md |
incremental |
Incremental load: merge / append / insert_overwrite / delete+insert | incremental.md |
dynamic_table |
Auto-refresh on schedule, no manual scheduling needed | dynamic-table.md |
materialized_view |
Pre-computed aggregation view | materializations.md |
snapshot |
SCD Type 2 history tracking | snapshots.md |
clone |
Zero-copy clone + Time Travel clone | clone.md |
| Python models | Run Python/ML models via ZettaPark | python-models.md |
| Table Stream | CDC source: capture INSERT/UPDATE/DELETE | table-stream.md |
| Indexes | Bloomfilter / Inverted / Vector indexes | materializations.md |
| Partitioned & clustered tables | Partition by column, cluster by bucket | materializations.md |
persist_docs |
Sync model/column descriptions to Lakehouse | — |
on_schema_change |
Handle schema drift in incremental models | incremental.md |
grants |
Column/table-level access control | — |
| VCluster per-model | Assign compute cluster per model | incremental.md |
query_tag |
Tag all queries for job history filtering | observability.md |
query_comment |
Auto-inject dbt metadata into every SQL (on by default) | observability.md |
| Utility macros | optimize, undrop, clone, refresh, etc. | utility-macros.md |
Connection Parameters
| Parameter | Required | Description |
|---|---|---|
type |
✅ | Must be clickzetta |
service |
✅ | API endpoint, e.g. cn-shanghai-alicloud.api.clickzetta.com |
instance |
✅ | Instance name |
workspace |
✅ | Workspace name |
username |
✅ | Username |
password |
✅ | Password |
schema |
✅ | Default schema |
vcluster |
✅ | VCluster name, e.g. default |
connect_retries |
❌ | Connection retry count (default: 3) |
query_tag |
❌ | Tag applied to every query; visible in job history |
Development
git clone https://github.com/clickzetta/dbt-clickzetta.git
cd dbt-clickzetta
pip install -e .
# Unit tests (no connection required)
pytest tests/unit/
# Functional tests (requires a real Lakehouse connection)
cp test.env.example test.env
# Fill in test.env with your connection details
pytest tests/functional/
License
Apache 2.0
Release files for dbt-clickzetta 1.7.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dbt_clickzetta-1.7.13.tar.gz | 38.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dbt_clickzetta-1.7.13-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 85.7 kB
Release files / dbt_clickzetta-1.7.13.tar.gz
| Download URL | dbt_clickzetta-1.7.13.tar.gz |
|---|---|
| Size | 38.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / dbt_clickzetta-1.7.13-py3-none-any.whl
| Download URL | dbt_clickzetta-1.7.13-py3-none-any.whl |
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| Size | 47.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 16, 2026.
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