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dbt-spark
Advanced tools
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
dbt is the T in ELT. Organize, cleanse, denormalize, filter, rename, and pre-aggregate the raw data in your warehouse so that it's ready for analysis.
dbt-spark enables dbt to work with Apache Spark.
For more information on using dbt with Spark, consult the docs.
Review the repository README.md as most of that information pertains to dbt-spark.
A docker-compose environment starts a Spark Thrift server and a Postgres database as a Hive Metastore backend.
Note: dbt-spark now supports Spark 3.3.2.
The following command starts two docker containers:
docker-compose up -d
It will take a bit of time for the instance to start, you can check the logs of the two containers. If the instance doesn't start correctly, try the complete reset command listed below and then try start again.
Create a profile like this one:
spark_testing:
target: local
outputs:
local:
type: spark
method: thrift
host: 127.0.0.1
port: 10000
user: dbt
schema: analytics
connect_retries: 5
connect_timeout: 60
retry_all: true
Connecting to the local spark instance:
http://localhost:10000 and can be referenced with the Hive or Spark JDBC drivers using connection string jdbc:hive2://localhost:10000 and default credentials dbt:dbtNote that the Hive metastore data is persisted under ./.hive-metastore/, and the Spark-produced data under ./.spark-warehouse/. To completely reset you environment run the following:
docker-compose down
rm -rf ./.hive-metastore/
rm -rf ./.spark-warehouse/
If installing on MacOS, use homebrew to install required dependencies.
brew install unixodbc
dbt-spark? Check out the Contributing Guide.FAQs
The Apache Spark adapter plugin for dbt
We found that dbt-spark demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

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