SAP SuccessFactors is a cloud-based human experience management (HXM/HCM) provider. The SAP SuccessFactors Batch Source plugin in Cloud Data Fusion lets you extract data from any entity within the SAP SuccessFactors Employee Central module.
You can configure and execute bulk data transfers from SAP SuccessFactors without any coding.
For more information, see Connect to SAP SuccessFactors Batch Source.
Configuration
Property | Macro enabled | Description |
---|---|---|
Reference Name | No | Uniquely identifies the source for lineage and annotates the metadata. |
SAP SuccessFactors Base URL | Yes | Required. The base URL of SuccessFactors API. |
Entity Name | Yes | Required. The name of the Entity to be extracted. Doesn't support
entities that have properties with the Binary data type or large volumes
of data. For example, UserBadges and
BadgeTemplates are not supported. |
SAP SuccessFactors Username | Yes | Required. The user ID for authentication, similar to
USER_ID@COMPANY_ID . For example,
sfadmin@SFCPART000807 . |
SAP SuccessFactors Password | Yes | Required. The SAP SuccessFactors Password for user authentication. |
Filter Options | Yes | Optional. The Filter condition that restricts the output data volume,
for example, Price gt 200 . See the
supported filter options. |
Select Fields | Yes | Optional. Fields to be preserved in the extracted data. For
example, Category , Price , Name ,
Address . If the field is left blank, then all the
non-navigation fields will be preserved in the extracted data.All fields must be comma (,) separated. |
Expand Fields | Yes | Optional. List of navigation fields to be expanded in the extracted
output data. For example, customManager . If an entity has
hierarchical records, the source outputs a record for each row in the
entity it reads, with each record containing an extra field that
holds the value from the navigational property specified in the Expand
Fields. |
Associated Entity Name | Yes | Optional. Name of the Associated Entity that is being extracted.
For example, EmpCompensationCalculated . |
Pagination Type | Yes | Required. The type of pagination to be used. Server-side pagination
uses snapshot-based pagination. If snapshot-based pagination is
attempted on an entity that doesn't support the feature, the server
automatically forces client-offset pagination on the query. Examples of entities that only support server-side pagination are BadgeTemplates , UserBadges , and
EPCustomBackgroundPortlet . No records are transferred if
client-side pagination is chosen on these entities, as it relies on
the Count API, which returns -1 as the response.Default is Server-side Pagination. |
Use connection (on/off toggle) | No | Whether to use an existing connection. |
Connections (browse connections) | Yes | Choose the existing connection to use. |
Supported filter options
The following operators are supported:
Operator | Description | Example |
---|---|---|
Logical Operators | ||
Eq |
Equal | /EmpGlobalAssignment?$filter=assignmentClass eq ‘GA' |
Ne |
Not equal | /RecurringDeductionItem?$filter=amount ne 18 |
Gt |
Greater than | /RecurringDeductionItem?$filter=amount gt 4 |
Ge |
Greater than or equal | /RecurringDeductionItem?$filter=amount ge 18 |
Lt |
Less than | /RecurringDeductionItem?$filter=amount lt 18 |
Le |
Less than or equal | /RecurringDeductionItem?$filter=amount le 20 |
And |
Logical and | /RecurringDeductionItem?$filter=amount le 20 and amount gt
4 |
Or |
Logical or | /RecurringDeductionItem?$filter=amount le 20 or amount gt 4 |
Not |
Logical negation | /RecurringDeductionItem?$filter=not endswith(payComponentType,
‘SUPSPEE_US') |
Arithmetic Operators | ||
Add |
Addition | /RecurringDeductionItem?$filter=amount add 5 gt 18 |
Sub |
Subtraction | /RecurringDeductionItem?$filter=amount sub 5 gt 18 |
Mul |
Multiplication | /RecurringDeductionItem?$filter=amount mul 2 gt 18 |
Div |
Division | /RecurringDeductionItem?$filter=amount div 2 gt 18 |
Mod |
Modulo | /RecurringDeductionItem?$filter=amount mod 2 eq 0 |
Grouping Operators | ||
( ) |
Precedence grouping | /RecurringDeductionItem?$filter=(amount sub 5) gt 8 |
Data type mapping
SuccessFactors Data Type | Cloud Data Fusion Schema Data Type | BigQuery Data Type |
---|---|---|
Binary |
Bytes |
BYTES |
Boolean |
Boolean |
BOOLEAN |
Byte |
Bytes |
BYTES |
DateTime |
DateTime |
DATETIME |
DateTimeOffset |
Timestamp_Micros |
TIMESTAMP |
Decimal |
Decimal |
NUMERIC |
Double |
Double |
FLOAT |
Float |
Float |
FLOAT |
Int16 |
Integer |
INTEGER |
Int32 |
Integer |
INTEGER |
Int64 |
Long |
INTEGER |
SByte |
Integer |
INTEGER |
String |
String |
STRING |
Time |
Time_Micros |
TIME |
Validation
Click Validate on the top right to Validate the plugin.
The plugin generates a schema based on the metadata from SAP SuccessFactors. It automatically maps SAP SuccessFactors data types to corresponding Cloud Data Fusion data types.
Example data
The following example is the data for a single employee in EmployeePayrollRunResults
:
Example property | Example value |
---|---|
externalCode | SAP_EC_PAYROLL_1000_0101201501312015_456_416 |
Person ID | 456 |
User | Foo Bar |
Employment ID | 416 |
Payroll Provider ID | SAP_EC_PAYROLL |
Start of Effective Payment Period | 01/01/2015 |
End of Effective Payment Period | 01/31/2015 |
Company ID | BestRun Germany (1000) |
Payout | 01/28/2015 |
Currency | EUR (EUR) |
Payroll Run Type | Regular (REGULAR) |
System ID | X0B |
The example shows the results for an employee in EmployeePayrollRunResults
:
EmployeePayrollRunResults_externalCod e |
EmployeePayrollRunResults_mdfSystemEffectiveStartDate |
amount |
createdBy |
createdDate |
---|---|---|---|---|
SAP_EC_PAYROLL_2800_0101201901312019_305_265 |
1/31/2019 0:00:00 |
70923.9 |
sfadmin |
12/10/2019 15:32:20 |
SAP_EC_PAYROLL_2800_0101201901312019_310_270 |
1/31/2019 0:00:00 |
64500 |
sfadmin |
12/10/2019 15:32:20 |
SAP_EC_PAYROLL_2800_0201201902282019_305_265 |
2/28/2019 0:00:00 |
70923.9 |
sfadmin |
12/10/2019 15:32:20 |
SAP_EC_PAYROLL_2800_0201201902282019_310_270 |
2/28/2019 0:00:00 |
64500 |
sfadmin |
12/10/2019 15:32:20 |
SAP_EC_PAYROLL_2800_0301201903312019_305_265 |
3/31/2019 0:00:00 |
70923.9 |
sfadmin |
12/10/2019 15:32:20 |
Example pipeline
See the configurations in the following JSON file:
{ "artifact": { "name": "cdap-data-pipeline", "version": "VERSION_NUMBER", "scope": "SYSTEM" }, "description": "", "name": "Demo_SuccessFactors_BatchSource", "config": { "resources": { "memoryMB": 2048, "virtualCores": 1 }, "driverResources": { "memoryMB": 2048, "virtualCores": 1 }, "connections": [ { "from": "SAP SuccessFactors", "to": "BigQuery" } ], "comments": [], "postActions": [], "properties": {}, "processTimingEnabled": true, "stageLoggingEnabled": false, "stages": [ { "name": "SAP SuccessFactors", "plugin": { "name": "SuccessFactors", "type": "batchsource", "label": "SAP SuccessFactors", "artifact": { "name": "successfactors-plugins", "version": "0.2.9-SNAPSHOT", "scope": "USER" }, "properties": { "referenceName": "test", "baseURL": "${baseUrl}", "entityName": "EmpCompensation", "username": "${username}", "password": "${password}", "expandOption": "empCompensationCalculatedNav", "associatedEntityName": "EmpCompensationCalculated", "paginationType": "serverSide" } }, "outputSchema": [ { "name": "etlSchemaBody", "schema": "" } ], "id": "SAP-SuccessFactors" }, { "name": "BigQuery", "plugin": { "name": "BigQueryTable", "type": "batchsink", "label": "BigQuery", "artifact": { "name": "google-cloud", "version": "0.18.1", "scope": "SYSTEM" }, "properties": { "referenceName": "test", "project": "${projectId}", "datasetProject": "${datasetProjectId}", "dataset": "${dataset}", "table": "${table}", "serviceAccountType": "filePath", "serviceFilePath": "auto-detect", "operation": "insert", "truncateTable": "false", "allowSchemaRelaxation": "false", "location": "US", "createPartitionedTable": "false", "partitioningType": "TIME", "partitionFilterRequired": "false" } }, "outputSchema": [ { "name": "etlSchemaBody", "schema": "" } ], "inputSchema": [ { "name": "SAP SuccessFactors", "schema": "" } ], "id": "BigQuery" } ], "schedule": "0 1 */1 * *", "numOfRecordsPreview": 100, "maxConcurrentRuns": 1 } }
What's next
- Learn more about connecting to an SAP SuccessFactors Source in Cloud Data Fusion.