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Note
This article covers Databricks Connect for Databricks Runtime 14.0 and above.
Databricks Connect for Python ships with a pyspark binary which is a PySpark REPL (a Spark shell) configured to use Databricks Connect.
Start the shell
To start the Spark shell and to connect it to your running cluster, run the following command from your activated Python virtual environment.
Note
When started with no additional parameters, the shell picks up default credentials from the environment (for example, the DATABRICKS_ environment variables or the DEFAULT configuration profile) to connect to the Azure Databricks cluster. For information about configuring a connection, see Compute configuration for Databricks Connect.
pyspark
The Spark shell appears, for example:
Python 3.10 ...
[Clang ...] on darwin
Type "help", "copyright", "credits" or "license" for more information.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 13.x.dev0
/_/
Using Python version 3.10 ...
Client connected to the Spark Connect server at sc://...:.../;token=...;x-databricks-cluster-id=...
SparkSession available as 'spark'.
>>>
Once the shell starts up, the spark object is available to run Apache Spark commands on the Databricks cluster. Run a simple PySpark command, such as spark.range(1,10).show(). If there are no errors, you have successfully connected.
Use the shell
Refer to Interactive Analysis with the Spark Shell for information about how to use the Spark shell with Python to run commands on your compute.
Use the built-in spark variable to represent the SparkSession on your running cluster, for example:
>>> df = spark.read.table("samples.nyctaxi.trips")
>>> df.show(5)
+--------------------+---------------------+-------------+-----------+----------+-----------+
|tpep_pickup_datetime|tpep_dropoff_datetime|trip_distance|fare_amount|pickup_zip|dropoff_zip|
+--------------------+---------------------+-------------+-----------+----------+-----------+
| 2016-02-14 16:52:13| 2016-02-14 17:16:04| 4.94| 19.0| 10282| 10171|
| 2016-02-04 18:44:19| 2016-02-04 18:46:00| 0.28| 3.5| 10110| 10110|
| 2016-02-17 17:13:57| 2016-02-17 17:17:55| 0.7| 5.0| 10103| 10023|
| 2016-02-18 10:36:07| 2016-02-18 10:41:45| 0.8| 6.0| 10022| 10017|
| 2016-02-22 14:14:41| 2016-02-22 14:31:52| 4.51| 17.0| 10110| 10282|
+--------------------+---------------------+-------------+-----------+----------+-----------+
only showing top 5 rows
All Python code runs locally, while all PySpark code involving DataFrame operations runs on the cluster in the remote Azure Databricks workspace and run responses are sent back to the local caller.
Stop the shell
To stop the Spark shell, press Ctrl + d or Ctrl + z, or run the command quit() or exit().