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FieldName | Type | Value |
Id | String | 1234 |
Name | String | John |
Salary | INT | 9000 |
Designation | String | SSE |
Properties:
mapperFieldsource: name of the field that contains the input column name to be mapped. This field should be removed from the output schema.
- mappingFieldtarget: name of the field that contains the output column name that will be mapped. This field should be included in output schema.
- lookup table: The configuration of the lookup tables to be used in your transform as mapping dataset. For example, if lookup table "designation" is configured, then you will be able to perform operations with that lookup table in your transform. Currently supports KeyValueTable.
- User would provide these properties in input text field as triplet (as shown below)
- User would provide default values for mapping fields. Json representation is provided in below example
Example:
{
"name": "ValueMapper",
"type": "transform",
"properties": {
"mapperFieldmapping": "designationID",
"mappingField" : "designationName",
"lookup": "{
\"tables\":{
\"designation\":{
\"type\":\"DATASET\"source1:LookupTableName:target1,source2:LookupTable2:target2",
\"datasetProperties\":{
\"dataset_argument1\":\"foo\",
\"dataset_argument2\":\"bar\"
"defaults":"field1:value1,field2:value2" }
}
}
}"
}
}
The transform takes record that have "id,name,salary,designationID" fields, maps the value of designationID field to generate designationName field based on the mapping dataset and then returns a record containing "id,name,salary,designationName" fields.
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