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The SAP NetWeaver component uses the SAP Java Connector (SAP JCo) to connect to SAP systems via the SAP RFC protocol, letting you retrieve your SAP NetWeaver data to load into a table in your data warehouse (Snowflake, Databricks, or Amazon Redshift) or cloud storage solution (Amazon S3, Azure Blob Storage, or Google Cloud Storage). Loading the data into your cloud data warehouse stages the data, so the table is reloaded each time. You can then use transformations to enrich and manage the data in permanent tables. You do not need to set up a Create Table component when using this component.
This component is only available for use with Hybrid SaaS agents.
If the component requires access to a cloud provider (AWS, Azure, or GCP), it will use the cloud credentials associated with your environment to access resources. To stage data to Azure Blob Storage, the Azure credentials associated with your environment must be assigned the Storage Blob Data Contributor role. For more information, read User assigned with the Storage Blob Data Contributor role.

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Uploading SAP drivers

Drivers for SAP NetWeaver are not natively included in Hybrid SaaS agents, but can be uploaded to your agent instance using the process in Uploading external drivers to the agent. Two driver files are required:
  • sapjco3.jar
  • libsapjco3.so
You can obtain these drivers as a single ZIP file from Download SAP Java Connector 3.1 SDK, selecting Linux for Intel compatible processors. Unzip the file and place the drivers in the storage location you specified as described in Uploading external drivers to the agent. Do not change the driver file names.

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Properties

Reference material is provided below for the Connect, Configure, Destination, and Advanced Settings properties.
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Name
string
required
A human-readable name for the component.

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Connect

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Authentication Type
drop-down
required
Select the method through which to authenticate to SAP. Currently supports Username and Password.
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Host
string
Input the host name or IP address of the SAP NetWeaver server.Read Connecting to an SAP load balancer if you wish to configure your SAP environment to use a load balancer. In such instances, keep the Host parameter empty.
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Username
string
required
A valid SAP NetWeaver username.
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Password
string
required
The secret definition holding your password tied to your username for your SAP account. Your password should be saved as a secret definition before using this component.
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Client
string
required
Specify the client authenticating to the SAP system.
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System Number
integer
required
A two-digit identifier (ranging from 00 to 99) that uniquely identifies an instance of the SAP system in the host machine.
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Connection Options
column editor
  • Parameter: A JDBC parameter supported by the database driver. The available parameters are explained in the data model. Manual setup is not usually required, since sensible defaults are assumed.
  • Value: A value for the given parameter.
Click the Text Mode toggle at the bottom of the Connection Options dialog to open a multi-line editor that lets you add items in a single block. For more information, read Text mode.

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Configure

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Data Source
drop-down
required
Select a single data source to be extracted from the source system and loaded into a table in the destination. The source system defines the data sources available. Use multiple components to load multiple data sources.
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Data Selection
dual listbox
required
Choose one or more columns to return from the query. The columns available are dependent upon the data source selected. Move columns left-to-right to include in the query.To use grid variables, select the Use Grid Variable checkbox at the bottom of the Data Selection dialog.
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Data Source Filter
column editor
Define one or more filter conditions that each row of data must meet to be included in the load.
  • Input Column: Select an input column. The available input columns vary depending upon the data source.
  • Qualifier:
    • Is: Compares the column to the value using the comparator.
    • Not: Reverses the effect of the comparison, so “Equals” becomes “Not equals”, “Less than” becomes “Greater than or equal to”, etc.
  • Comparator: Choose a method of comparing the column to the value. Possible comparators include: “Equal to”, “Greater than”, “Less than”, “Greater than or equal to”, “Less than or equal to”, “Like”, “Null”. “Equal to” can match exact strings and numeric values, while other comparators, such as “Greater than” and “Less than”, will work only with numerics. The “Like” operator allows the wildcard character % to be used at the start and end of a string value to match a column. The Null operator matches only null values, ignoring whatever the value is set to. Not all data sources support all comparators, meaning that it is likely that only a subset of the above comparators will be available to choose from.
  • Value: The value to be compared.
Click the Text Mode toggle at the bottom of the Connection Options dialog to open a multi-line editor that lets you add items in a single block. For more information, read Text mode.
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Combine Filters
drop-down
The data source filters you have defined can be combined using either And or Or logic. If And, then all filter conditions must be satisfied to load the data row. If Or, then only a single filter condition must be satisfied. The default is And.If you have only one filter, or no filters, this parameter is essentially ignored.
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Row Limit
integer
Set a numeric value to limit the number of rows that are loaded. The default is an empty field, which will load all rows.

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Destination

Select your cloud data warehouse.
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Destination
drop-down
required
Select the destination for your data. This is either in Snowflake as a table or as files in cloud storage.
  • Snowflake: Load your data into a table in Snowflake. The data must first be staged via Snowflake or a cloud storage solution.
  • Cloud Storage: Load your data directly into files in your preferred cloud storage location. The format of these files can differ between source systems and will not have a file extension so we suggest inspecting the output to determine the format of the data.
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Warehouse
drop-down
required
The Snowflake warehouse used to run the queries. The special value [Environment Default] uses the warehouse defined in the environment. Read Overview of Warehouses to learn more.
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Database
drop-down
required
The Snowflake database to access. The special value [Environment Default] uses the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.
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Schema
drop-down
required
The Snowflake schema. The special value [Environment Default] uses the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.
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Table Name
string
required
The name of the table to be created in your Snowflake database. You can use a Table Input component in a transformation pipeline to access and transform this data after it has been loaded.
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Load Strategy
drop-down
required
Define what happens if the table name already exists in the specified Snowflake database and schema.
  • Replace: If the specified table name already exists, that table will be destroyed and replaced by the table created during this pipeline run.
  • Truncate and Insert: If the specified table name already exists, all rows within the table will be removed and new rows will be inserted per the next run of this pipeline.
  • Fail if Exists: If the specified table name already exists, this pipeline will fail to run.
  • Append: If the specified table name already exists, then the data is inserted without altering or deleting the existing data in the table. It’s appended onto the end of the existing data in the table. If the specified table name doesn’t exist, then the table will be created, and your data will be inserted into the table.
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Clean Staged files
boolean
required
  • Yes: Staged files will be destroyed after data is loaded. This is the default setting.
  • No: Staged files are retained in the staging area after data is loaded.
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Stage Access Strategy
drop-down
Select the stage access strategy. The strategies available depend on the cloud platform you select in Stage Platform.
  • Credentials: Connects to the external stage (AWS, Azure) using your configured cloud provider credentials. Not available for Google Cloud Storage.
  • Storage Integration: Use a Snowflake storage integration to grant access to Snowflake to read data from and write to a cloud storage location. This will reveal the Storage Integration property, through which you can select any of your existing Snowflake storage integrations.
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Stage Platform
drop-down
required
Use the drop-down menu to choose where the data is staged before being loaded into your Snowflake table.
  • Amazon S3: Stage your data on an AWS S3 bucket.
  • Snowflake: Stage your data on a Snowflake internal stage.
  • Azure Storage: Stage your data in an Azure Blob Storage container.
  • Google Cloud Storage: Stage your data in a Google Cloud Storage bucket.

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Advanced Settings

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Page Size
integer
The default is 50000.

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Connecting to SAP products

The RFC protocol is used to connect to the following SAP systems:
  • SAP BW
  • SAP ECC
  • SAP ERP
  • SAP R/3
  • SAP S/4 HANA

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Connecting to an SAP Load Balancer

You can configure an SAP environment to use a load balancer, called a message server. This load balancer may have its own port, which must be specified for a connection to succeed. Read below to learn how to connect to an SAP load balancer.
  1. The Host parameter must be left empty.
  2. Set the User and Password parameters as normal with the correct credentials.
  3. In Connection Options, set up three connection options as per the table below.
ParameterValue
MessageServerexample.8u98900
MessageServerService3603
GroupPUBLIC
The Host parameter is not set because the MessageServer connection option takes its place.

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Deactivate soft delete for Azure blobs (Databricks)

If you intend to set your destination as Databricks and your stage platform as Azure Storage, you must turn off the “Enable soft delete for blobs” setting in your Azure account for your pipeline to run successfully. To do this:
  1. In the Azure portal, navigate to your storage account.
  2. In the menu, under Data management, click Data protection.
  3. Clear the Enable soft delete for blobs checkbox. For more information, read Soft delete for blobs.