This code is no longer maintained.
This container is designed for developing PySpark application in VS Code using Databricks-Connect. Technically it should work for Scala, Java & R - though I haven't tried.
It can be used as a Docker Container or as a cloud hosted container using CodeSpaces.
- VS Code with the Remote Containers Extension
- Docker or a CodeSpace Plan
- VS Code with the Remote Containers Extension
- Docker or a CodeSpace Plan
- If using Docker:
- WSL or WSL2 (WSL2 Preferred)
For a more advanced option you can use any OS and a Remote Docker Host.
This maybe useful if you cannot run local containers and do not want to use a cloud container.
- Open an empty folder in VS Code
- Create a directory called .devcontainer
- Create an empty file in the directory called devcontainer.json
- Paste this code into the file:
{
"context": "..",
"image": "datathirstltd/dbconnect:7.1.0",
"settings": {
"python.pythonPath": "/opt/conda/envs/dbconnect/bin/python",
"python.venvPath": "/opt/conda/envs/dbconnect/lib/python3.7/site-packages/pyspark/jars"
},
// Optional command - could add your own environment.yml file here (you must keep --name the same)
// "postCreateCommand": "conda env update --file environment.yml --name dbconnect",
// Rather than storing/committing your bearer token here we recommend using a local variable and passing thru "DATABRICKS_API_TOKEN": "${localEnv:DatabricksToken}",
// You can manually set these as environment variables if you prefer
"containerEnv": {
"DATABRICKS_ADDRESS": "https://westeurope.azuredatabricks.net/",
"DATABRICKS_API_TOKEN": "dapia12345678901234567890",
"DATABRICKS_CLUSTER_ID": "0000-11111-hello123",
"DATABRICKS_ORG_ID": "1234567890",
"DATABRICKS_PORT": "8787"
},
"extensions": [
"ms-python.python"
]
}
IMPORTANT: Correct the image tag to the version of Databricks Runtime your cluster is running. Currently we only support Databricks 6+
- Update the Databricks Variables for your environment
- Optionally add any additional extensions you want to the extensions block.
IMPORTANT: Changing any setting in the devcontain.json after the container has been build requires you to rebuild the container for it take effect
To open using Docker locally:
- Click on the Green icon in the bottom left of VSCode and select "Reopen in Container"
To open in a CodeSpace:
- Commit your folder to a repo first
- Open the Remote Explorer (left hand toolbar)
- Ensure CodeSpaces is selected in the top drop down
- Click + (Create new CodeSpace)
- Follow the prompts
The first pull can be a little slow as the image is quite big. But once it is cached rebuilding the container should take just a few seconds.
First from command prompt check that you databricks connect install can connect:
databricks-connect test
If create a test.py file and paste this code:
from pyspark.sql import SparkSession
spark = SparkSession\
.builder\
.getOrCreate()
print("Testing simple count")
# The Spark code will execute on the Azure Databricks cluster.
print(spark.range(100).count())
Press F5 and select the Python debugger.
Because setting up Databricks-Connect (particulary on Windows is a PIA). This allow:
- A common setup between team members
- Multiple side by side versions
- Ability to reset your environment
- Even run the whole thing from a browser!
https://github.com/DataThirstLtd/databricksConnectDocker
https://hub.docker.com/r/datathirstltd/dbconnect
About Data Thirst - https://datathirst.net About VSCode and Containers: https://code.visualstudio.com/docs/remote/containers