This node allows you to execute Python code on Spark (See PySpark documentation). The code has to put the desired output in the data frame with the name resultDataFrame1
Enter your Python code here.
The SparkSession can be accessed via the global variable spark. The input Dataset<Row> can be accessed via the method input parameter dataFrame1 and dataFrame2. The output Dataset<Row> must be called resultDataFrame1.
The editor optionally provides autocompletion (CTRL + Space) using the local Python installation,
if the KNIME Python Extension and the Python module jedi is installed.
The path to the Python executable has to be configured in Preferences → KNIME → Python.
Note:
The completion suggestions are made based on the local Python environment, which may differ
from the Python setup in the cluster!
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
To use this node in KNIME, install the extension KNIME Extension for Apache Spark (legacy) from the below update site following our NodePit Product and Node Installation Guide:
A zipped version of the software site can be downloaded here.
Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.
Try NodePit Runner!Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.