NOTE: Transforms are a part of the underlying language that is not directly accessible to users. This content is maintained for reference purposes only.Splits a column of values into separate rows of data based on the specified delimiter. You can split rows only on String literal values. Pattern-based row splitting is not supported.
splitrows transform must be the first one in your recipe. When a dataset is loaded for the first time in the Transformer page, a
splitrows transform may added as the first step of the recipe. You cannot cannot add another
splitrows transform later in your recipe. For more information, see Initial Parsing Steps.
If you load CSV data into the Transformer page and then review the first recipe step in the Recipe panel, it might look like the following:
splitrows col: column1 on: '\r'
Output: The above splits all of the CSV data, which is stored as a comma-separated values in
column1 initially. The delimiter for the end of the row is a carriage return, which is indicated by the
\r escaped value.
splitrows col:column_ref on:'string_literal' [quote:'quoted_string']
|splitrows||Y||transform||Name of the transform|
|col||Y||string||Source column name|
|on||Y||string||Specifies the end of row delimiter for each value in the source column|
|quote||N||string||Specifies a quoted object that is omitted from pattern matching|
|quoteEscapeChar||N||string||Specifies the escape character that is used to precede quote marks.|
For more information on syntax standards, see Language Documentation Syntax Notes.
Identifies the column to which to apply the transform. You can specify only one column.
|Yes||String (column name)|
Identifies the pattern to match. Pattern can be a string literal, Cloud Dataprep pattern, or regular expression pattern.
NOTE: Value must be a string. For this transform, the parameter defines the string on which to split the current row and add the data after the string to the new row.
Can be used to specify a string as a single quoted object.
NOTE: This parameter value must be a single character.
splitrows col: MyCol on: '\r\n' quote: '"'
Output: Splits the
MyCol column into separate rows on the return-newline character string (
\r\n). Values contained within double quotes (
") are treated as strings, even if they contain
By default, the platform assumes the following characters are used to escape quote marks in text-based formats that use quotes to identify fields:
- JSON: Platform assumes that
- All other file formats: Platform assumes that
Optionally, you can specify the character that is used to escape quote marks in each recipe. Typically, this value is specified for processing JSON data or for customizing the transform for your specific data.
splitrows col: MyCol on: '\r\n' quote: '"' quoteEscapeChar:'"'
|No||String literal (single character)|
Example - splitrows with CSV data
Before you import, your data in CSV format looks like the following:
Date,UserId,Message 3/14/16,jjones,"Hi, everyone! Happy, St. Patrick's Day!" 3/14/16,lsmith,"@jjones, it's on 3/17." 3/14/16,thughes,lol 3/14/16,jjones,"@lsmith, no harm in celebrating twice!"
- The Message value for the first row of data contains carriage returns, which must be captured in the data value and not used to split the row.
- The Message value for
thughesis a single unquoted value.
When the data is first loaded into the Transformer page, the following step is added as the first step to the recipe:
splitrows col: column1 on: '\r' quote: '\"'
This transform splits the unstructured CSV data on the carriage return. However, values that are stored between double quotes are treated as single strings, and no row breaks are applied to this data.
For CSV data, this step, a
split step, and a
header step are typically added automatically as the first steps of the recipe. In the Transformer page, this dataset should look like the following:
|3/14/16||jjones||Hi, everyone! C R C RHappy, St. Patrick's Day!|
|3/14/16||lsmith||@jjones, it's on 3/17.|
|3/14/16||jjones||@lsmith, no harm in celebrating twice!|
The C R marker is used to indicate a carriage return in the data.