dbt-trino 0.20.0

The trino adapter plugin for dbt (data build tool)

dbt-trino

Introduction

One frequently asked question in the context of using dbt tool is:

Can I connect my dbt project to two databases?

(see the answered question on the dbt website).

tldr; dbt stands for transformation as in T within ELT pipelines, it doesn't move data from source to a warehouse.

The creators of the dbt tool have added however support for handling such scenarios via dbt-presto plugin.

This repository represents a fork of the dbt-presto with slight adaptations to make it work with Trino SQL compute engine.

Compatibility

This dbt plugin has been tested against dbt version 0.20.0 and trino version 359.

Installation

This dbt adapter can be installed via pip:

$ pip install dbt-trino

Configuring your profile

A dbt profile can be configured to run against Trino using the following configuration:

Option	Description	Required?	Example
method	The Trino authentication method to use	Optional (default is none)	none or kerberos
user	Username for authentication	Required	commander
password	Password for authentication	Optional (required if method is ldap or kerberos)	none or abc123
database	Specify the database to build models into	Required	analytics
schema	Specify the schema to build models into. Note: it is not recommended to use upper or mixed case schema names	Required	public
host	The hostname to connect to	Required	127.0.0.1
port	The port to connect to the host on	Required	8080
threads	How many threads dbt should use	Optional (default is 1)	8

Example profiles.yml entry:

my-trino-db:
  target: dev
  outputs:
    dev:
      type: trino
      user: commander
      host: 127.0.0.1
      port: 8080
      database: analytics
      schema: public
      threads: 8

Usage Notes

Supported Functionality

Due to the nature of Trino, not all core dbt functionality is supported. The following features of dbt are not implemented on Trino:

• Archival
• Incremental models

Also, note that upper or mixed case schema names will cause catalog queries to fail. Please only use lower case schema names with this adapter.

Required configuration

dbt fundamentally works by dropping and creating tables and views in databases. As such, the following Trino configs must be set for dbt to work properly on Trino:

hive.metastore-cache-ttl=0s
hive.metastore-refresh-interval = 5s
hive.allow-drop-table=true
hive.allow-rename-table=true

Running tests

Build dbt container locally:

./docker/dbt/build.sh

Run a Trino server locally:

./docker/init.bash

If you see errors while about "inconsistent state" while bringing up Trino, you may need to drop and re-create the public schema in the hive metastore:

# Example error

Initialization script hive-schema-2.3.0.postgres.sql
Error: ERROR: relation "BUCKETING_COLS" already exists (state=42P07,code=0)
org.apache.hadoop.hive.metastore.HiveMetaException: Schema initialization FAILED! Metastore state would be inconsistent !!
Underlying cause: java.io.IOException : Schema script failed, errorcode 2
Use --verbose for detailed stacktrace.
*** schemaTool failed ***

Solution: Drop (or rename) the public schema to allow the init script to recreate the metastore from scratch. Only run this against a test Trino deployment. Do not run this in production!

-- run this against the hive metastore (port forwarded to 10005 by default)
-- DO NOT RUN THIS IN PRODUCTION!

drop schema public cascade;
create schema public;

You probably should be slightly less reckless than this.

Run tests against Trino:

./docker/run_tests.bash

Run the locally-built docker image (from docker/dbt/build.sh):

export DBT_PROJECT_DIR=$HOME/... # wherever the dbt project you want to run is
docker run -it --mount "type=bind,source=$HOME/.dbt/,target=/home/dbt_user/.dbt" --mount="type=bind,source=$DBT_PROJECT_DIR,target=/usr/app" --network dbt-net dbt-trino /bin/bash

Running integration tests

Install dbt-adapter-tests library to be able to run the dbt tests:

pip install pytest-dbt-adapter

Run from the base directory of the project the command:

pytest test/integration/trino.dbtspec

Code of Conduct

Everyone interacting in the dbt project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow the PyPA Code of Conduct.