The Apache Spark adapter plugin for dbt
Project description
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
The dbt-ocean-spark
package contains all of the code enabling dbt to work with Apache Spark on Ocean. For
more information, consult the docs.
Getting started
- Install dbt
- Read the introduction and viewpoint
Running locally
A docker-compose
environment starts a Spark Thrift server and a Postgres database as a Hive Metastore backend.
Note: dbt-spark now supports Spark 3.1.1 (formerly on Spark 2.x).
The following command would start 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: ocean_spark
method: http
host: api.spotinst.io
port: 443
cluster: osc-[clusterId]
account: acc-[accountId]
app: spark-hive-[appId]
schema: analytics
connect_retries: 5
connect_timeout: 60
retry_all: true
Connecting to the local spark instance:
- The Spark UI should be available at http://console.spotinst.com/ocean/spark/cluster/{clusterId}/app/{appId}/sparkUI/jobs
- The endpoint for SQL-based testing is at
http://localhost:10000
and can be referenced with the Hive or Spark JDBC drivers using connection stringjdbc:hive2://localhost:10000
and default credentialsdbt
:dbt
Note 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/
Reporting bugs and contributing code
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.
Join the dbt Community
- Be part of the conversation in the dbt Community Slack
- Read more on the dbt Community Discourse
Reporting bugs and contributing code
- Want to report a bug or request a feature? Let us know on Slack, or open an issue
- Want to help us build dbt? Check out the Contributing Guide
Code of Conduct
Everyone interacting in the dbt project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow the dbt Code of Conduct.
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