0 ×

CSV to Spark

KNIME Extension for Apache Spark core infrastructure version 4.3.1.v202101261633 by KNIME AG, Zurich, Switzerland

This node supports the path flow variable. For further information about file handling in general see the File Handling Guide.

Creates a Spark DataFrame/RDD from given CSV file. See CSV Data Source documentation for more information.

Notice: This feature requires at least Apache Spark 1.5.



Select if you like to read a file or folder.
Enter the input 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.
Upload data source driver or depend on cluster side provided driver.
First line of files will be used to name columns and will not be included in data.
Character used as delimiter between columns (supports escape sequences, e.g. \t or \u0123).
Quote character
Quote character (delimiters inside quotes are ignored).
Escape character
Escape character (escaped quote characters are ignored).
Determines the parsing mode. By default it is PERMISSIVE.
  • PERMISSIVE: tries to parse all lines: nulls are inserted for missing tokens and extra tokens are ignored.
  • DROPMALFORMED: drops lines which have fewer or more tokens than expected or tokens which do not match the schema.
  • FAILFAST: aborts with a RuntimeException if encounters any malformed line.
Valid charset name (see java.nio.charset.Charset).
Automatically infers column types. It requires one extra pass over the data. All types will be assumed string otherwise.
Skip lines beginning with this character.
Null value
Specifies a string that indicates a null value, any fields matching this string will be set as nulls in the DataFrame.
Date format
Specifies a string that indicates the date format to use when reading dates or timestamps. Custom date formats follow the formats at java.text.SimpleDateFormat. This applies to both DateType and TimestampType. By default, it is null which means trying to parse times and date by java.sql.Timestamp.valueOf() and java.sql.Date.valueOf().

Input Ports

Spark compatible connection (HDFS, WebHDFS, HttpFS, S3, Blob Storage, ...)
Spark context

Output Ports

Spark DataFrame/RDD



To use this node in KNIME, install KNIME Extension for Apache Spark from the following update site:


A zipped version of the software site can be downloaded here.

You don't know what to do with this link? Read our NodePit Product and Node Installation Guide that explains you in detail how to install nodes to your KNIME Analytics Platform.

Wait a sec! You want to explore and install nodes even faster? We highly recommend our NodePit for KNIME extension for your KNIME Analytics Platform. Browse NodePit from within KNIME, install nodes with just one click and share your workflows with NodePit Space.


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.