OData Services (Non-ODP Sources)

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Full Load

For Non-ODP (Operational Data Provisioning) systems, a Full Load involves extracting the entire dataset from the source system and loading it into the target system. Since Non-ODP systems do not inherently support advanced data extraction mechanisms like deltas, the process is straightforward but can be resource-intensive depending on the size of the data.

Incremental Load

For systems or entities that do not support ODP (Operational Data Provisioning), incremental data transfer can be managed manually by implementing a timestamp based mechanism to track and extract changes.

Timestamp based Incremental Transfers

For non-ODP enabled entities(or for ODP enabled entities that don’t use the ENABLE_CDC flag), we can use a filteringExpression option in the connector to indicate the datetime interval for which we want to retrieve data. This method relies on a timestamp field in you data that represents when each record was last created/modified.

Example

Retrieving records that changed after 2024-01-01T00:00:00.000

sapodata_df = glueContext.create_dynamic_frame.from_options(
    connection_type="SAPOData",
    connection_options={
        "connectionName": "connectionName",
        "ENTITY_NAME": "entityName",
        "filteringExpression": "LastChangeDateTime >= 2024-01-01T00:00:00.000"
    }, transformation_ctx=key)
                
            

Note: In this example, LastChangeDateTime is the field that represents when each record was last modified. The actual field name may vary depending on your specific SAP OData entity.

To get a new subset of data in subsequent runs, you would update the filteringExpression with a new timestamp. Typically, this would be the maximum timestamp value from the previously retrieved data.

Example

max_timestamp = get_max_timestamp(sapodata_df)  # Function to get the max timestamp from the previous run
next_filtering_expression = f"LastChangeDateTime > {max_timestamp}"

# Use this next_filtering_expression in your next run

In the next section, we will provide an automated approach to manage these timestamp-based incremental transfers, eliminating the need to manually update the filtering expression between runs.