Spark to JSON

Writes a Spark data to JSON.

Notice: This feature requires at least Apache Spark 1.5.

This node can access a variety of different file systems. More information about file handling in KNIME can be found in the official File Handling Guide.

Options

Settings

Write to
Shows the connected file system.
Folder
Enter the output path. The required syntax of a path depends on the connected file system. The node description of the respective connector node describes the required path format. You can also choose a previously selected file from the drop-down list, or select a location from the "Browse..." dialog. Note that browsing is disabled in some cases:
  • Browsing is disabled if the connector node hasn't been executed since the workflow has been opened. (Re)execute the connector node to enable browsing.
The location can be exposed as or automatically set via a path flow variable.
Create missing folders
Select if the folders of the selected output location should be created if they do not already exist. If this option is unchecked, the node will fail if a folder does not exist.
If exists
Specify the behavior of the node in case the output file already exists.
  • Overwrite: Will replace any existing file.
  • Append: Append to existing files or create new one if output path does not exists.
  • Ignore: Does nothing and keeps the output path unchanged.
  • Fail: Will issue an error during the node's execution (to prevent unintentional overwrite).

Partitions

Columns
Select the columns to partition on.
Overwrite partitions count
This can be useful to reduce output file count to e.g. one file.
Warning: This might result in serious performance issues on huge data sets. Use with caution!
See Spark documentation for more informations.

Input Ports

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Spark compatible connection (HDFS, WebHDFS, HttpFS, S3, Blob Storage, ...)
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Spark DataFrame/RDD

Output Ports

This node has no output ports

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Links

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