Boost Your Performance: Parallelize Record Processing with Stream Replicas
In today's data-driven world, efficient processing of large volumes of records is crucial for businesses to maintain a competitive edge. By implementing Stream Replicas, you can boost your record processing capabilities significantly, reducing the time it takes to handle your data, by parallelizing the processing.
When dealing with a substantial number of records, processing them one by one in sequence can be a major bottleneck. If a lot of time is spent on processing records, it can lead to businesses facing delays in generating insights, making critical decisions, and providing timely services to customers.
To overcome the constraint of processing a large number of records in the shortest time possible, configuring your stream to use replicas offers an efficient solution. By configuring multiple stream replicas, you can parallelize the processing of your input files. This means that instead of waiting for each record to be processed sequentially, you can leverage the power of parallel computing to distribute the workload across multiple replicas, saving you precious time and boosting overall performance.
How It Works
Each stream replica acts as an independent processing unit, capable of running its transactions, or a series of transactions. How many replicas you need to configure depends on the scale of your data and the desired performance gains. When you initiate the processing of your records, these replicas work in harmony to handle the workload concurrently. As a result, you can process a significantly larger number of records within the same timeframe, enabling faster data analysis, quicker decision-making, and improved customer experiences.
For information on how to organize your input files efficiently, and maximize the benefits of stream replicas, see our user documentation. It provides detailed instructions on how to configure and set up stream replicas according to your specific requirements, see https://infozone.atlassian.net/wiki/spaces/DAZ/pages/7894668.
Improved UI and Added Parameter for SAP Subscription Billing
The user interface in the SAP Subscription Billing Forwarder function has gone through a major makeover to provide a modern look with enhanced usability.
The SAP’s Usage Record API has been updated with a new parameter called Items which can contain an array of rating parameters enabling more flexible rating and advanced business models in Subscription Billing. The update allows for any number of rating parameters to be sent out to the Subscription Billing function in a single record. The SAP Subscription Billing can with its new feature "Individual Usage Rating" rate and close bills for invoicing immediately instead of waiting for the billing cycle to complete.
The SAP Subscription Billing forwarder can now help determine how pricing procedures can be mapped to quote items or header fields. Pricing conditions can be mapped to the fields in a customizable order. The SAP Subscription Billing function is aligned with the way usage records are processed. This is SAP’s mechanism for creating and updating usage records to store consumption data from external systems. The validity of each record is valid for the delegated aggregation period.
Using The Updated Function
The update allows any number of rating parameters to be sent to the Subscription Billing forwarder in a single record. With the new Individual Usage Rating feature, SAP Subscription Billing can rate and close bills for invoicing immediately instead of waiting for the billing cycle to complete.
The SAP Subscription Billing Function allows all essential parameters to be placed in the Required Fields section.
Streams now include configuration information in versions, providing the possibility to save specific configurations within the functions. You can explore different configurations for each function(s) within the stream.
The parameters and configurations are separated for a more convenient setup — configurations refer to the parameters that define the behavior of the individual Functions placed within the stream while the parameters define the operational aspects.
Versioning provides control mechanisms on when to save a working stream version.
Streams created in this way allow for easier comparison between the exports. The addition of tags and comments allows for easier organization and management of complex use cases.
Stream Versions List
Creating a Test Environment for Stream Testing
In this use case, you can create a test environment for stream testing without the need to modify the logic of the original stream. When you want to test a stream in a different environment, a new copy of the stream is generated, ensuring the integrity of the original stream's configuration. The only adjustment required is to modify the parameters of the copied stream, directing them to the test environment. By doing so, you can safely evaluate the stream's functionality and performance without introducing any risks associated with modifying the original stream. This allows for thorough testing while maintaining the reliability and stability of the production stream.
Stream Optimization and Configuration Replacement
This use case focuses on stream optimization by allowing you to create a copy of the stream and test different codes, add or remove nodes, and experiment with a new configuration. Once you are satisfied with the optimized version, the existing stream can be seamlessly replaced with the new version, all while preserving traceability through logs and audits. By enabling you to make changes and evaluate the performance of the new configuration, this use case ensures that stream optimization can be achieved without sacrificing accountability and traceability. The ability to replace the existing stream with the optimized version streamlines the implementation of improvements and enhances the overall efficiency of the system.
Improved Stream Handling
A new mode called View, has been introduced to prevent unintended changes to the stream configuration. In contrast, the Edit mode grants the flexibility to modify all aspects of the stream.
The introduction of View and Edit modes ensures the protection of the stream when multiple individuals are editing simultaneously. Versions are initially created in Edit mode and subsequently opened in View mode. This distinction helps maintain the integrity of the stream configuration. It is important to note that only users with delegated permissions have the authority to revise the stream's configuration and parameters, ensuring proper control and governance.
To prevent the loss of any changes made to a configuration, the stream management system includes an integrated autosave functionality. When editing a stream in Edit Mode, the system automatically saves the changes as an autosave version. This ensures that the latest modifications are securely stored until the user commits the changes. By keeping a single autosave version, the system avoids cluttering the ViewHistory with multiple versions. The primary purpose of this functionality is to safeguard against unintended loss of configuration changes and provide users with the ability to revert to a previous configuration if desired. This streamlined approach ensures efficient management of changes while maintaining the integrity of the stream's configuration.
This functionality simplifies the tracking of changes during stream development, making it more convenient to monitor the progress. Versions are easily identifiable in the logs and audit information, providing a clear history of modifications. The ability to handle versions brings valuable usability benefits, allowing updated configurations to seamlessly update existing streams while preserving their states, history, logs, and audit information. This ensures a smooth transition and enhanced manageability of the stream environment.