With the Extension Import node, you can run scripts that are written in R, Python, or
Python for Spark to import data.
After adding the node to your canvas, double-click the node to open its properties.
Syntax tab
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Select your type of syntax – R, Python, or
Python for Spark. Then enter or paste your custom script for importing data.
When your syntax is ready, you can run the node.
Console Output tab
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The Console Output tab contains any output that's received when the R
script or Python script runs (for example, if using an R script, it shows output received from the R
console when the R script in the R Syntax field on the
Syntax tab is executed). This output might include R or Python error messages
or warnings that are produced when the R or Python script is executed. The output can be used,
primarily, to debug the script. The Console Output tab also contains the
script from the R Syntax or Python Syntax field.
Every time the Extension Import script runs, the content of the Console
Output tab is overwritten with the output received from the R or Python console. You
can't edit the output.
Filtering or renaming fields
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You can rename or exclude fields at any point in a flow. For example, as a medical researcher,
you may not be concerned about the potassium level (field-level data) of patients (record-level
data); therefore, you can filter out the K (potassium) field.
Using a Filter node, you can rename or filter fields at any point in the flow
You can use a Filter node to map fields from one import node to another
Viewing and setting information about types
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From the Type node, you can specify field metadata and properties that
are invaluable to modeling and other work.
These properties include:
Specifying a usage type, such as range, set, ordered set, or flag, for each field in your
data
Setting options for handling missing values and system nulls
Setting the role of a field for modeling purposes
Specifying values for a field and options used to automatically read values from your data
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