Apache Spark Code Tool
The Apache Spark Code tool is a code editor that creates an Apache Spark context and executes Apache Spark commands directly from Designer. This tool uses the R programming language.
For additional information, see Apache Spark Direct, Apache Spark on Databricks, and Apache Spark on Microsoft Azure HDInsight.
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Connect to your Apache Spark cluster directly.
- Drag a Connect In-DB Tool or Data Stream In Tool onto the canvas.
- Click the Connection Name drop-down arrow and select Manage connection.
Alternatively, connect directly with the Apache Spark Code tool.
- Drag the Apache Spark Code tool onto the canvas.
- Under Data Connection, click the Connection Name drop-down arrow and select Manage connection.
Both methods bring up the Manage In-DB Connections window.
In Manage In-DB Connections , select a Data Source. See Supported Data Sources and File Formats.
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With an Apache Spark Direct connection established, the Code Editor activates.
Use Insert Code to generate template functions in the code editor.
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Import Library creates an import statement.
import package
Read Data creates a readAlteryxData function to return the incoming data as an Apache SparkSQL DataFrame.
val dataFrame = readAlteryxData(1)
Write Data creates a writeAlteryxData function to output an Apache SparkSQL DataFrame.
writeAlteryxData(dataFrame, 1)
Log Message creates a logAlteryxMessage function to write a string to the log as a message.
logAlteryxMessage("Example message")
Log Warning creates a logAlteryxWarning function to write a string to the log as a warning.
logAlteryxWarning("Example warning")
Log Error creates a logAlteryxError functions to write a string to the log as an error.
logAlteryxError("Example error")
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Import Library creates an import statement.
from module import library
Read Data creates a readAlteryxData function to return the incoming data as an Apache SparkSQL DataFrame.
dataFrame = readAlteryxData(1)
Write Data creates a writeAlteryxData function to output an Apache SparkSQL DataFrame.
writeAlteryxData(dataFrame, 1)
Log Message creates a logAlteryxMessage function to write a string to the log as a message.
logAlteryxMessage("Example message")
Log Warning creates a logAlteryxWarning function to write a string to the log as a warning.
logAlteryxWarning("Example warning")
Log Error creates a logAlteryxError functions to write a string to the log as an error.
logAlteryxError("Example error")
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Import Library creates an import statement.
library(jsonlite)
Read Data creates a readAlteryxData function to return the incoming data as an Apache SparkSQL DataFrame.
dataFrame <- readAlteryxData(1)
Write Data creates a writeAlteryxData function to output an Apache SparkSQL DataFrame.
writeAlteryxData(dataFrame, 1)
Log Message creates a logAlteryxMessage function to write a string to the log as a message.
logAlteryxMessage("Example message")
Log Warning creates a logAlteryxWarning function to write a string to the log as a warning.
logAlteryxWarning("Example warning")
Log Error creates a logAlteryxError functions to write a string to the log as an error.
logAlteryxError("Example error")
Use Import Code to pull in code created externally.
- From File opens a File Explorer to browse to your file.
- From Jupyter Notebook opens a File Explorer to browse to your file.
- From URL provides a field to type or paste a file location.
Click the gear icon to change cosmetic aspects of the code editor.
- Use the Text Size buttons to increase or decrease the size of the text in the editor.
- Use Color Theme to toggle between a dark and light color scheme.
- Select Wrap Long Lines causes long lines to remain visible within the code editor window instead of requiring a horizontal scroll.
- Select Show Line Numbers to see line numbers for the editor.
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Select the output channel metainfo you want to manage.
Manually change the Apache Spark Data Type of existing data.
Click the plus icon to add a data row.
- Type the Field Name.
- Select the Apache Spark Data Type.
- Type the Size in bits.