# Connecting to S/4 HANA
Before you can connect to your S/4 HANA data source, you must complete the following prerequisites. After that, AWS Supply Chain automatically creates the Amazon S3 paths and ingests data from the SAP source tables.
## Prerequisites to connect to S/4 HANA
To connect to S/4 HANA data source, the following prerequisites must be completed before ingesting data.
1. Configure your SAP S/4 HANA system to turn on ODP-based data extraction through the SAP OData connector for Amazon AppFlow. For more information, see [SAP OData connector for Amazon AppFlow](https://docs.aws.amazon.com/appflow/latest/userguide/sapodata.html).
1. Configure your SAP data sources or extractors, and generate ODP based OData services for AWS Supply Chain to connect and extract information. For more information, see [SAP data sources](#s4-datasources).
1. Configure your SAP system with one of the following types of authentication:
+ Basic
+ OAuth
1. Configure security roles in the SAP system to turn on data extraction.
1. Set up network connectivity to SAP S/4 HANA. If your SAP instance is in a secure VPN and you can't open a port for AWS Supply Chain to connect, we recommend that you use AWS PrivateLink. To manually setup AWS PrivateLink, see [AWS for SAP](https://aws.amazon.com/blogs/awsforsap/share-sap-odata-services-securely-through-aws-privatelink-and-the-amazon-appflow-sap-connector/) and to automatically setup using CloudFormation, see [CloudFormation](https://github.com/aws-cloudformation/aws-cloudformation-templates/tree/main/AWSSupplyChain/SapPrivateLink).
## Configuring S/4 HANA connection
To ingest data from an SAP S/4HANA data source, follow the procedure below.
1. On the AWS Supply Chain dashboard, on the left navigation pane, choose **Data Lake**.
1. On the **Data lake** page, choose **Add New Source**.
The **Select your supply chain data source** page appears.
1. Choose **SAP S/4HANA**.
1. Choose **Next**.
1. Under ** SAP S/4HANA Connection Details**, enter the following:
+ **Connection name** – Enter a name for this connection.
+ (Optional) **Connection description** – Enter a name for this connection.
+ **Use Existing AppFlow Connector** – Choose **Yes** to use an existing AppFlow connector.
+ **Application Host URL** – Enter the SAP account's URL.
+ **Application Service Path** – Enter the SAP application service path.
+ **Port Number** – Enter the SAP port number.
+ **Client Number** – Enter the SAP client number.
+ **Logon Language** – Enter the SAP language code. For example, EN for English.
+ **PrivateLink** – Choose **Enabled** to enable a private connection between the SAP server and your AWS account hosting AWS Supply Chain.
+ **Username** – Enter the username of the SAP account.
+ **Password** – Enter the password of the SAP account.
**Note**
Amazon AppFlow uses the SAP **Username** and **Password** provided by you to connect to SAP.
1. Choose **Connect to SAP**.
If the SAP username and password are entered correctly, a **Connection Successful** message appears.
1. (Optional) Under **Optional AppFlow Configuration**, **Step 1 - Download the JSON template file**, choose **Download the existing JSON template file** to modify the appflow ingestion settings.
**Note**
You can use your own editor to edit the .json file. You cannot edit the .json file in AWS Supply Chain.
After you update the .json file, under **Step 2 - Upload the modified JSON template file**, choose **browse files** to upload.
**Note**
If this upload is unsuccessful, the **Upload summary** will display the errors or conflicts in the .json file. You can update the .json file to fix the issues and re-upload the file.
Here is a sample .json file with the required schedule, data flows, and source tables.
```
{
"schedule" : {
"scheduleExpression" : "rate(1days)", // scheduleExpression key should be available and the value cannot be null/empty. Format starts with rate and having time values in minutes, hours, or days. For example, rate(1days)
"scheduleStartTime" : null // Supported format - "yyyy-MM-dd'T'hh:mm:ss[+|-]hh:mm". For example, 2022-04-26T13:00:00-07:00. ScheduleStartTime should atleast be 5 minutes after current time. A null value will automatically set the start time as 5 minutes after the connection creation time
},
"dataFlows" : [ // DataFlows cannot be null or empty. Make sure to choose from the list below
"Company-Company",
"Geography-Geography",
"Inventory-Inventory Level",
"Inventory-Inventory Policy",
"Outbound-Outbound Order Line",
"Outbound-Outbound Shipment",
"Product-Product",
"Product-Product Hierarchy",
"Production Order-Inbound Order",
"Production Order-Inbound Order Line",
"Purchase Order-Inbound Order",
"Purchase Order-Inbound Order Line",
"Purchase Order-Inbound Order Line Schedule",
"Reference-Reference Fields",
"Shipment-Shipment",
"Site-Site",
"Site-Transportation Lane",
"Trading Partner-Trading Partner",
"Transfer Order-Inbound Order Line",
"Vendor Management-Vendor Lead Time",
"Vendor Management-Vendor Product",
"Product-Product UOM"
],
"sourceTables" : [ // sourceTables cannot be empty
{
"tableName" : "SomeString", // Should be an existing table name from the SAP instance
"extractType" : "DELTA", // Should either be DELTA or FULL
"tableCols" : [ // TableCols cannot be empty. Enter valid column names for the table
"col1",
"col2",
"col3"
],
"filters" : [// Optional field
"colName" : "col1", // colName value should be part of tableCols
"dataType" : "String", // Should contain values `STRING` or `DATETIME`
"value" : "String",
"operator" : "String" // Choose a string value from the pre-defined value of "PROJECTION", "LESS_THAN", "CONTAINS","GREATER_THAN","LESS_THAN_OR_EQUAL_TO","GREATER_THAN_OR_EQUAL_TO","EQUAL_TO","NOT_EQUAL_TO","ADDITION","MULTIPLICATION","DIVISION","SUBTRACTION","MASK_ALL","MASK_FIRST_N","MASK_LAST_N","VALIDATE_NON_NULL","VALIDATE_NON_ZERO","VALIDATE_NON_NEGATIVE",or "VALIDATE_NUMERIC","NO_OP";
]
},
{
// sourceTables with same keys - tableName, extractType, tableCols, filters(not mandatory)
}
]
}
```
1. Under **Amazon S3 Bucket Billing**, review the Amazon S3 billing information, and then select **Acknowledge**.
1. Choose **Next**.
1. Under **Data Mapping**, choose **Get started**.
1.
**Note**
The required fields are already mapped. Perform this step only if you want to make specific changes to the default transformation recipe.
On the **Mapping Recipe** page, you can view the default transformation recipe under **Field mappings**.
Choose **Add mapping**, to map any additional destination field. The **Required Destination Fields** are mandatory. Choose **Destination field** to add an additional custom destination field.
1. To view the source field values and data mappings from the transformation recipe, you can upload sample data. On the **Mapping Recipe** page, under **Upload sample data**, choose **browse files**, or drag and drop files. The sample data file must contain the required parameters and include the source field names.
1. Choose **Accept all and continue**.
1. Under **Review and confirm**, you can view the data connection summary. To edit your data field mapping, choose **Go back to Data Mapping**.
1. (Optional) Under **Recipe Actions**, you can do the following:
+ **Download recipe file** - Select **Download** to edit your recipe files in SQL as a text file.
**Note**
For information about built-in SQL functions, see [Spark SQL](https://spark.apache.org/docs/latest/api/sql/index.html).
+ **Upload recipe file** - Choose **browse files** or drag and drop your edited recipe text files. Select **Confirm upload** to upload the edited recipe file and modify your data field mappings.
1. To review the Amazon S3 location paths where you must upload your SAP source data for ingestion, choose **Confirm and configure data ingestion**. Alternatively, you can choose **Confirm and configure data ingestion later**. You can view the data ingestion information anytime. From the AWS Supply Chain dashboard, select **Connections**. Select the connection dataflow that you want to ingest data, choose the vertical ellipsis, and select **Ingestion setup**.
## SAP data sources
Configure the following SAP table sources for AWS Supply Chain to connect and extract information.
**Note**
When you search for an SAP data source, prefix the data source name with *EntityOf*. For example, for the data source *0BP\$1DEF\$1ADDRESS\$1ATTR*, the entity name should be *EntityOf0BP\$1DEF\$1ADDRESS\$1ATTR*.
When Amazon AppFlow extracts each SAP data source, the entity name format is used to extract information. For example, to extract data from *0BP\$1DEF\$1ADDRESS\$1ATTR*, the data is extracted from the entity path */sap/opu/odata/sap/Z0BP\$1DEF\$1ADDRESS\$1ATTR\$1SRV/EntityOf0BP\$1DEF\$1ADDRESS\$1ATT*.
| SAP data source | SAP data source description | SAP source table | OData service name | BW data source | SAP data | Delta/Full |
| --- | --- | --- | --- | --- | --- | --- |
| 0BP\$1DEF\$1ADDRESS\$1ATTR | BP standard address extraction | NA | Z0BP\$1DEF\$1ADDRESS\$1ATTR\$1SRV | Data source | Master data | Delta |
| 0BPARTNER\$1ATTR | BP: BW Extraction Central Data | NA | Z0BPARTNER\$1ATTR\$1SRV | Data source | Master data | Delta |
| 0BPARTNER\$1TEXT | BP: DataSource for Business Partner Texts | NA | Z0BPARTNER\$1TEXT\$1SRV | Data source | Master data | Delta |
| 0CO\$1PC\$1ACT\$105 | Material Valuation: Prices | NA | Z0CO\$1PC\$1ACT\$105\$1SRV | Data source | Master data | Full |
| 0COMP\$1CODE\$1TEXT | Company Code Text | NA | Z0COMP\$1CODE\$1TEXT\$1SRV | Data source | Master data | Full |
| 0CUSTOMER\$1ATTR | Customer | NA | Z0CUSTOMER\$1ATTR\$1SRV | Data source | Master data | Delta |
| 0MAT\$1VEND\$1ATTR | Material or Vendor | NA | Z0MAT\$1VEND\$1ATTR\$1SRV | Data source | Master data | Delta |
| 0MATERIAL\$1ATTR | Material | NA | Z0MATERIAL\$1ATTR\$1SRV | Data source | Master data | Delta |
| 0MATERIAL\$1TEXT | Material text | NA | Z0MATERIAL\$1TEXT\$1SRV | Data source | Master data | Delta |
| 0PURCH\$1ORG\$1TEXT | Purchasing org text | NA | Z0PURCH\$1ORG\$1TEXT\$1SRV | Data source | Master data | Full |
| 0VENDOR\$1ATTR | Vendor | NA | Z0VENDOR\$1ATTR\$1SRV | Data source | Master data | Delta |
| 2LIS\$102\$1HDR | Purchasing Data (Header Level) | NA | Z2LIS\$102\$1HDR\$1SRV | Data source | Transactional | Delta |
| 2LIS\$102\$1ITM | Purchasing Data (Item Level) | NA | Z2LIS\$102\$1ITM\$1SRV | Data source | Transactional | Delta |
| 2LIS\$102\$1SCL | Purchasing Data (Schedule Line Level) | NA | Z2LIS\$102\$1SCL\$1SRV | Data source | Transactional | Delta |
| 2LIS\$102\$1SCN | Confirmation of Schedule Lines | NA | Z2LIS\$102\$1SCN\$1SRV | Data source | Transactional | Delta |
| 2LIS\$103\$1BF | Goods Movements from Inventory Management | NA | Z2LIS\$103\$1BF\$1SRV | Data source | Transactional | Delta |
| 2LIS\$104\$1P\$1MATNR | Material View from PP/PP-PI | NA | Z2LIS\$104\$1P\$1MATNR\$1SRV | Data source | Transactional | Delta |
| 2LIS\$108TRFKP | Shipment Costs at Item Level | NA | Z2LIS\$108TRFKP\$1SRV | Data source | Transactional | Delta |
| 2LIS\$108TRTLP | Shipment: Delivery Item Data by Section | NA | Z2LIS\$108TRTLP\$1SRV | Data source | Transactional | Delta |
| 2LIS\$108TRTK | Shipment: Header Data | NA | Z2LIS\$108TRTK\$1SRV | Data source | Transactional | Delta |
| 2LIS\$111\$1VAHDR | Sales Document Header | NA | Z2LIS\$111\$1VAHDR\$1SRV | Data source | Transactional | Delta |
| 2LIS\$111\$1VAITM | Sales Document Item | NA | Z2LIS\$111\$1VAITM\$1SRV | Data source | Transactional | Delta |
| 2LIS\$112\$1VCITM | Delivery Item Data | NA | Z2LIS\$112\$1VCITM\$1SRV | Data source | Transactional | Delta |
| ZADRC | Addresses | ADRC | ZADRC\$1SRV | Table | Master data | Full |
| ZBUT021\$1FS | Partner Address | BUT021\$1FS | ZBUT021\$1FS\$1SRV | Table | Master data | Full |
| ZCDHDR | Change document header | CDHDR | ZCDHDR\$1SRV | Table | Master data | Delta |
| ZEINA | Purchasing Info Record: General Data | EINA | ZEINA\$1SRV | Table | Master data | Full |
| ZEINE | Purchasing Info Record: Purchasing Organization Data | ZV\$1EINE | ZEINE\$1SRV | Table | Master data | Full |
| ZEKKO | Purchasing Document Header | ZV\$1EKKO | ZEKKO\$1SRV | Table | Transactional | Delta |
| ZEKPO | Purchasing Document Item | ZV\$1EKPO | ZEKPO\$1SRV | Table | Transactional | Delta |
| ZEQUI | Equipment master data | EQUI | ZEQUI\$1SRV | Table | Master data | Full |
| ZGEOLOC | Geo Location | GEOLOC | ZGEOLOC\$1SRV | Table | Master data | Full |
| ZLIKP | Delivery Header Data | LIKP | ZLIKP\$1SRV | Table | Transactional | Delta |
| ZLIPS | Delivery: Item Data | ZV\$1LIPS | ZLIPS\$1SRV | Table | Transactional | Delta |
| ZMDRP\$1NODTT | Node Type for DRP Network | MDRP\$1NODTT | ZMDRP\$1NODTT\$1SRV | Table | Master data | Full |
| ZMARC | Plant Data for Material | ZQ\$1MARC | ZMARC\$1SRV | Table | Master data | Full |
| ZMARD | Storage Location Data for Material | ZQ\$1MARD | ZMARD\$1SRV | Table | Master data | Full |
| ZMCHB | Batch Stocks | ZQ\$1MCHB | ZMCHB\$1SRV | Table | Master data | Full |
| ZT001W | Plant | T001W | ZT001W\$1SRV | Table | Master data | Full |
| ZT005T | Country Names | T005T | ZT005T\$1SRV | Table | Master data | Full |
| ZT141T | Descriptions of Material Status | T141T | ZT141T\$1SRV | Table | Master data | Full |
| ZT173T | Shipping Type of Transport Texts | T173T | ZT173T\$1SRV | Table | Master data | Full |
| ZT179 | Materials: Product Hierarchies | T179 | ZT179\$1SRV | Table | Master data | Full |
| ZT179T | Materials: Product Hierarchies Text | T179T | ZT179T\$1SRV | Table | Master data | Full |
| ZT370U | Equipment Category Text | T370U | ZT370U\$1SRV | Table | Master data | Full |
| ZT618T | Mode of Transport Descriptions | T618T | ZT618T\$1SRV | Table | Master data | Full |
| ZTVRAB | Route Stages | TVRAB | ZTVRAB\$1SRV | Table | Master data | Full |
| ZTVRO | Routes | TVRO | ZTVRO\$1SRV | Table | Master data | Full |
| ZVALW | Route Schedule | VALW | ZVALW\$1SRV | Table | Master data | Full |
| ZVBBE | Sales Requirements: Individual Records | VBBE | ZVBBE\$1SRVs | Table | Master data | Full |
| ZINB\$1SHIPMENT | Shipment Header and Item (Inbound) | ZV\$1INB\$1SHIPMENT based with join condition: VTTK.MANDT = VTTP.MANDT and VTTK.TKNUM = VTTP.TKNUM | ZINB\$1SHIPMENT\$1SRV | Table | Transactional | Full |
| ZAUFK | Order Master Data | AUFK | ZAUFK\$1SRV | Table | Master data | Full |
| ZMARM | Unit of Measure for Material | MARM | ZMARM\$1SRV | Table | Master data | Full |
| ZEBAN | Purchase requisitions | EBAN | ZEBAN\$1SRV | Table | Transactional data | Delta |