Understanding SAC Performance Analysis

Performance analysis in SAC encompasses an array of metrics, including stability, speed, scalability, and responsiveness. Essentially, it’s about how efficiently the platform handles workloads, from loading dashboards to executing queries.

You can access it by, Choose System > Performance

And there are some tools that can help you with the whole performance analysis paradigm. Let’s discuss them.

Measurement Tool

The Measurement Tool within SAC serves as a compass for gauging your system’s performance. By assessing factors like client time, network latency, and SAC responsiveness, it provides valuable insights into areas that demand improvement. The normalized scores generated by the Measurement tool offer a Measurement against best practices, guiding optimization efforts effectively.

The Measurement Tool tab consists of two Performance tests which are Client test and Network test.

(The above test is done in our internal system where Client score is 83 and Network latency is 280ms.)

• The client Measurement tool calculates a normalized score that can be compared against best practices.
  
• Network tests are essential for measuring client latency and bandwidth to the SAP Analytics Cloud Service.
  
• Both CPU-intensive applications and network performance significantly impact load times for Stories and Analytic Applications.
  
• It is crucial to be mindful of these factors to ensure optimal system performance.

Performance Analysis Tool

SAC’s Performance Analysis Tool revolutionizes the way administrators monitor system performance. Gone are the days of grappling with complex tools and manual data interpretation. This tool automates the collection and storage of performance information, empowering administrators to identify and resolve issues swiftly. With features like Page Load Time and Widget Drilldown, administrators can pinpoint bottlenecks and optimize performance at a granular level.

To begin using the tool, you can narrow down your search criteria by specifying a combination

of Date, Resource, and/or User.

• we have a selected a Resource and chosen a story

• We have used the below story for demonstrating Performance analysis tool

• Upon selecting the Story that we want to analyze; we have presented with the initial view of Performance analysis tool.
  
• The tool calculates the time at which pages, widgets, and model but no specific methods are there to control load time.

Page Load Time

• It’s mainly used to dig deeper into the story by looking at widgets, models, and pages. It gives a list of items sorted by how long they take to load, starting with the slowest.
  
• It displays time for Pages in a deeper level like page preparation time. Maximum/Minimum backend time etc.

Widget Drilldown

• It is used to drill down the widget wise measure’s which is used to calculate Widget time, Network time and Backend time like shown in the below image

• When clicking any particular widget or action it pops up a certain window that displays the front-end time, connected Model and Backend Request.

• If any particular widget is selected it changes the below graph which calculates Median backend time, Median Network time, Median Frontend Time.

Runtime Distribution

• Below image shows the runtime distribution. It displays time for widget, backend, network, frontend.

Unveiling Insights with Statistics and Analysis

The Statistics and Analysis tool in SAC bridges the gap between technical backend operations and user-facing frontend experiences. By providing comprehensive statistical analysis, it offers a holistic view of system performance. From backend query execution times to frontend load times, this tool equips administrators with the insights needed to fine-tune performance across the board.

• The Overview Page displays KPIs for Number of Logons, Frontend and Backend Kpi’s as well as Top 10 Users by Logon Time and Top 10 Stories by Load Time.

• In SAP Analytics Cloud, a model can be used in multiple stories. Sometimes, the model itself works fine, but when combined with a specific story, it can cause performance issues. We identify these combinations that have the most impact on the backend system. This helps us understand which specific combinations of models and stories might be causing slowdowns or other problems in the system.

• We use this charts to see how quickly query get answers and how many times they have run over time. We also check where the time goes in the process of running this query. This helps us understand how well the query are doing and if they’re getting faster or slower over time

The Importance of SAC Performance Analysis

In today’s data-centric landscape, SAC performance analysis isn’t just a nicety—it’s a necessity. Here’s why:

• Optimized Efficiency: By identifying and rectifying performance bottlenecks, SAC performance analysis streamlines operations, ensuring optimal efficiency.
  
• Enhanced User Experience: A responsive and stable SAC platform translates to a seamless user experience, fostering user adoption and satisfaction.
  
• Cost Savings: Proactive performance analysis helps mitigate the risk of system downtime and inefficiencies, ultimately resulting in cost savings for organizations.
  
• Data-Driven Decision Making: With SAC performing at its peak, organizations can trust the accuracy and timeliness of the insights derived, facilitating informed decision-making.
  
• Competitive Advantage: Leveraging SAC performance analysis to continuously optimize the platform provides organizations with a competitive edge, enabling them to stay ahead in today’s dynamic business landscape.

In conclusion, SAC performance analysis isn’t just a technical endeavor—it’s a strategic imperative. By harnessing the power of performance analysis tools, organizations can unlock the full potential of SAC, driving innovation, efficiency, and success.

So, embark on the journey of SAC performance analysis today, and witness firsthand the transformative impact it can have on your organization’s analytical capabilities and bottom line.

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This tutorial is designed for SAP HANA on premise and SAP HANA, express edition. It is not designed for SAP HANA Cloud. I have used SAP HANA XS Advanced (SAP Web IDE).

When you want to expose data from a HANA database to a third party (In my case they were going to use the data to build a user interface application using ReactJS), the recommended best practice is to use OData.

xsodata services use the proprietary XSJS dialect of JavaScript to create an OData service. To use XSJS, SAP adds Node.js modules to provide XSJS compatibility.

Before we proceed further, let’s have a quick look at our system.

Our Project name is DUMMY_PROJECT and DB name is DUMMY_DATABASE.

There are two calculation Views: –

1. CV_EMP – calculation view without parameter.

Its Output: –

2. CV_EMP_WITH_PARAMETER – Same calculation view as above but with parameter on

‘DEPT_NAME’ column named as IP_DEPARTMENT.

Its Output: – With ‘FINANCE’ as an input for the Input Parameter IP_DEPARTMENT.

Step 1: Create a Node.js module in your project

Right-click on the project (DUMMY_PROJECT) and select New->Node.js Module.

Give it a name (DUMMY_ODATA) and click “Next”, on next screen add description (Dummy OData Application) and be sure to Enable XSJS Support by selecting a checkbox:

Click “Finish” and validate that module is available under the project as shown below.

Right click on Node.js module just created (DUMMY_ODATA) and build it.

Step 2: Check Node.js module availability in mta.yaml file and set dependency from DB module

Double click on mta.yaml file and switch to “MTA Editor” view, Node.js module (DUMMY_ODATA) should be available there.

For Node.js module to be linked with DB module scroll down to “Requires” section, hit “+” icon and select our reporting container DB(DUMMY_DATABASE) for it to appear as on screenshot below, and save the changes.

Step 3: Create OData service for customer-facing CV

1. For CV without Input Parameter
   
2. For CV with Input Parameter

• For CV without Input Parameter

Let’s create new folder under “lib” folder and name it “odata”. This will be the place where we will store OData service files.

Right click on our newly created “odata” folder and create new file with “.xsodata” extension for our CV_EMPLOYEE Calculation View as “reporting_employee.xsodata”.

Double click on created file to open code editor and specify code as below.

service
{
"DUMMY_PROJECT.DUMMY_DATABASE.models::CV_EMP" as "EMPLOYEE"
with("EMP_CODE","EMP_NAME","DEPT_NAME","LOCATION","MANAGER");
}

Path to calculation view, “with” section where we specify fields for output and specify which column is a key (in current key is not defined).

Save file and build Node.js module (DUMMY_ODATA in our sample).

1. For CV without Input Parameter

Double click on created file in the above step “reporting_employee.xsodata” to open code editor and specify code as below.

service
{
"DUMMY_PROJECT.DUMMY_DATABASE.models::CV_EMP_WITH_PARAMETER" as "EMPLOYEE_WITH_IP"
with("EMP_CODE","EMP_NAME","DEPT_NAME","LOCATION","MANAGER")
key ("DEPT_NAME") parameters via key and entity;
}

Path to calculation view, “with” section where we specify fields for output and specify which column is a key and for CV with input parameter, we also need to specify by which entity parameters will be used (“DEPT_NAME” in our sample).

Save file and build Node.js module (DUMMY_ODATA in our sample).

Step 4: Build Project and deploy to XS Advanced

Right click on project name (DUMMY_PROJECT) and click on “Build”-> “Build”.

If build successful, we will see appropriate message in log.

Building a project will form/update an .mtar file under mta_archives folder.

As a final step we need to deploy our project .mtar file to XS Advanced.

Right click on it and click on Deploy -> Deploy to XS Advanced.

Choose Organization and Space and click “Deploy”.

After successful deployment we should see appropriate message and entry in logs.

Step 5: Check in XSA-COCKPIT that our application is running

click on Tools -> SAP HANA XS Advanced Cockpit. A page will be opened in a new tab.

Click on the Organization Space and search with Node.js module / Application (DUMMY_ODATA in our sample).

Click on our application name DUMMY_ODATA and copy application Routes link/URL which we will use:

Click on this URL and a new tab will open with message something like this.

Apart from this you can also get a link or URL by following the below steps.

Right click on xsodata file (reporting_employee.xsodata) and click on “Run”-> “Run as Node.js Application”.

After successful run we should see appropriate message and link/URL generated in logs.

Click on this URL and a new tab will open with same message as above “Hello World“.

NOTE: – Both the links/URLS generated might differ, but both will work, because the one which is generated from the XSA cockpit is DB deployed version that is from the DB host server and the second one is from the local server. However, better is to use the link generated using SAP HANA XS Advanced Cockpit.

Step 6: Access the application through URL

1. For CV without Input Parameter
2. For CV with Input Parameter
3. For CV without Input Parameter

To access that service/OData URL works correctly we can check it via link which is formed by combination of

Link or URL generated in the above step (ABOVE_GENERATED_LINK) + Path to service as shown below: –

ABOVE_GENERATED_LINK/odata/reporting_employee.xsodata/EMPLOYEE –> Paste this URL in a web browser to see data.

Data/Output: –

1. For CV with Input Parameter

Link or URL generated in the above step (ABOVE_GENERATED_LINK) + Path to service + Input Parameter Value as shown below: –

ABOVE_GENERATED_LINK/odata/reporting_employee.xsodata/EMPLOYEE_WITH_IP(IP_DEPARTMENT=’FINANCE’) Paste the above URL in a web browser to see data

Data/Output: – You will get the output in JSON format as shown below

1. For CV with Input Parameter

Link or URL generated in the above step (ABOVE_GENERATED_LINK) + Path to service + Input Parameter Value as shown below: –

ABOVE_GENERATED_LINK/odata/reporting_employee.xsodata/EMPLOYEE_WITH_IP(IP_DEPARTMENT=’FINANCE’) Paste the above URL in a web browser to see data

Data/Output: –

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