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Splitrows Transform

注記

Transforms are a part of the underlying language, which is not directly accessible to users. This content is maintained for reference purposes only. For more information on the user-accessible equivalent to transforms, see Transformation Reference.

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.

注記

The 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.

Basic Usage

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.

Syntax and Parameters

splitrows col:column_ref on:'string_literal' [quote:'quoted_string']

Token

Required?

Data Type

Description

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.

col

Identifies the column to which to apply the transform. You can specify only one column.

Usage Notes:

Required?

Data Type

Yes

String (column name)

on

Identifies the pattern to match, which can be a string literal, Wrangle , or regular expression.

注記

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.

Usage Notes:

Required?

Data Type

Yes

String literal

quote

Can be used to specify a string as a single quoted object.

注記

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 \r\n values.

Usage Notes:

Required?

Data Type

No

String

quoteEscapeChar

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 \ is used.

  • All other file formats: Platform assumes that " is used.

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:'"'

Usage Notes:

Required?

Data Type

No

String literal (single character)

Examples

ヒント

For additional examples, see Common Tasks.

Example - splitrows with CSV data

Unstructured source:

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!"

Notes:

  • 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 thughes is a single unquoted value.

Transformation:

When the data is first loaded into the Transformer page, the following step is added as the first step to the recipe:

Transformation Name

Split into rows

Parameter: Column

column1

Parameter: Split on

'\r'

Parameter: Quote escape character

'\"'

This transformation 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.

Results:

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:

Date

UserId

Message

3/14/16

jjones

Hi, everyone! CRC RHappy, 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 C R marker is used to indicate a carriage return in the data.