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Extractkv Transform

Nota

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.

Extracts key-value pairs from a source column and writes them to a new column.

Source column must be of String type, although the data can be formatted as other data types. The generated column is of Object type.

Your source column (MyKeyValues) is formatted in the following manner:

key1=value1,key2=value2

Basic Usage

The following transform extracts the key-value pairs. The key parameter contains a single pattern that matches all keys that you want to extract:

extractkv col: MyKeyValues key:`{alpha}+{digit}` valueafter: '=' delimiter: ','

Output: The generated column contains data that looks like the following:

{"key1":"value1","key2":"value2"}

If the source data contained additional keys which were not specified in the transform, those key-value pairs would not appear in the generated column.

Syntax and Parameters

extractkv col:column_ref delimiter:string_literal_pattern key:string_literal_pattern valueafter:string_literal_pattern [as:'new_column_name']

Parameter

Required?

Data Type

Description

extractkv

Y

transform

Name of the transform

col

Y

string

Source column name

delimiter

Y

string

String literal or pattern that identifies the separator between key-value pairs

key

Y

string

Pattern that identifies the key to match

valueafter

Y

string

String literal or pattern after which is located a key's value

as

N

string

Name of the newly generated column

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)

delimiter

Specifies the character or pattern that defines the end of a key-value pair. This value can be specified as a String literal, regular expression, or Wrangle.

In the following:

{ key1=value1,key2=value2 }

The delimiter is the comma ( ','). The final key-value pair does not need a delimiter.

Sugerencia

You can insert the Unicode equivalent character for this parameter value using a regular expression of the form /\uHHHH/. For example, /\u0013/ represents Unicode character 0013 (carriage return). For more information, see Supported Special Regular Expression Characters.

Usage Notes:

Required?

Data Type

Yes

String (literal, regular expression, orWrangle)

key

Specifies the pattern used to extract the keys from a source column by the extractkv transform. For the following data:

{ key1=value1,key2=value2 }

The keys are represented in the transform by the following parameter and value:

key:`{alpha}+{digit}`

This pattern matches all keys that begin with a letter and end with a digit. If the source data contains other keys, they do not appear in the extracted data.

Usage Notes:

Required?

Data Type

Yes

Single pattern representing the individual keys to extract.

valueafter

Specifies the character or pattern after which the value is specified in a key-value pair. This value can be specified as a String literal, regular expression, or Wrangle .

For the following:

{ key1=value1,key2=value2 }

The valueafter string is the equals sign ( '=').

Usage Notes:

Required?

Data Type

Yes

String (literal, regular expression, orWrangle)

as

Name of the new column that is being generated. If the as parameter is not specified, a default name is used.

Usage Notes:

Required?

Data Type

No

String (column name)

Examples

Sugerencia

For additional examples, see Common Tasks.

Example - extracting key values from car data and the unnesting into separate columns

This example shows how you can unpack data nested in an Object into separate columns.

Source:

You have the following information on used cars. The VIN column contains vehicle identifiers, and the Properties column contains key-value pairs describing characteristics of each vehicle. You want to unpack this data into separate columns.

VIN

Properties

XX3 JT4522

year=2004,make=Subaru,model=Impreza,color=green,mileage=125422,cost=3199

HT4 UJ9122

year=2006,make=VW,model=Passat,color=silver,mileage=102941,cost=4599

KC2 WZ9231

year=2009,make=GMC,model=Yukon,color=black,mileage=68213,cost=12899

LL8 UH4921

year=2011,make=BMW,model=328i,color=brown,mileage=57212,cost=16999

Transformation:

Add the following transformation, which identifies all of the key values in the column as beginning with alphabetical characters.

  • The valueafter string identifies where the corresponding value begins after the key.

  • The delimiter string indicates the end of each key-value pair.

Transformation Name

Convert keys/values into Objects

Parameter: Column

Properties

Parameter: Key

`{alpha}+`

Parameter: Separator between key and value

`=`

Parameter: Delimiter between pair

','

Now that the Object of values has been created, you can use the unnest transform to unpack this mapped data. In the following, each key is specified, which results in separate columns headed by the named key:

Nota

Each key must be entered on a separate line in the Path to elements area.

Transformation Name

Unnest Objects into columns

Parameter: Column

extractkv_Properties

Parameter: Paths to elements

year

Parameter: Paths to elements

make

Parameter: Paths to elements

model

Parameter: Paths to elements

color

Parameter: Paths to elements

mileage

Parameter: Paths to elements

cost

Results:

When you delete the unnecessary Properties columns, the dataset now looks like the following:

VIN

year

make

model

color

mileage

cost

XX3 JT4522

2004

Subaru

Impreza

green

125422

3199

HT4 UJ9122

2006

VW

Passat

silver

102941

4599

KC2 WZ9231

2009

GMC

Yukon

black

68213

12899

LL8 UH4921

2011

BMW

328i

brown

57212

16999