Name: Data Intelligence 19 of 21 ; Using REST API Operators
Uploaded: 2023-9-6
Duration: 398 s

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<div><div><div>In this video series, we'll introduce some of the applications when using Data Intelligence. In this video, we'll go through using the Modeler to create a pipeline which uses the OpenAPI operator to expose data as an API.<br><br>0:00 - Introduction<br>0:55 - Create a new graph and add the OpenAPI Servlow operator<br>2:30 - Add Wiretap, Write File, and Workflow Terminator<br>5:45 - Save and execute<br><br><br>Please note:<br>                     This video was originally published on the SAP HANA Academy YouTube Channel                      and therefore may contain references to SAP HANA Academy and YouTube.                      The tech world is always evolving and the SAP HANA Academy YouTube channel                      is set to close on December 31, 2023.                      At that time, references will no longer be valid                      and will gradually be removed when the videos are updated.<br>Also, this video includes automatically generated captions                      and therefore might misrepresent the spoken content or display incorrect product names.</div></div></div>

Data Intelligence 19 of 21 ; Using REST API Operators

Welcome to the SAP HANA Academy. My name is Bob and in this series of videos by Digital Partner Engineering and the SAP HANA Academy we'll be looking at Data Intelligence 3.1. This video shows how we can use REST APIs when using the Modeler. In this video we're going to be creating a REST API service that can be called by devices to save performance data to a file. In one of our earlier videos we built this file called performance.csv and it resides in our semantic data lake and what we might want to do is add data using a REST API. So one of the uses for this would be, for example, one of your IoT devices to write directly to your performance.csv file. So back in the modeler, what we'll do is we'll build ourselves a new graph. The first object we need to add is the REST API operator called open API servlo. So once we've added that we can go to the documentation and as it says it's a server-side component that is suitable for providing services described in Swagger OpenAPI or unspecified HTTP services. So that means we can use tools such as Mailman or apps or programming languages such as Python to send data to your semantic data lake. So what we need to do is some configuration. So we'll go to the configuration tab and firstly we need to set that base path. So for me the base path is going to be teched2020 forward slash SHA performance with an underscore. Quite simply this means when we're performing a post using Mailman or an application for example, this will be part of our endpoint. There's only one other thing that we have to change here and that's to do with responses. So if I scroll down we've got one way and I'll need to set that to true. This means that the operator won't wait for a response but will immediately send back a HTTP 204. Now of course the base path isn't the whole path, so I'll show you later on when it comes to using Mailman how to discover what the whole path is. Now it would be a good idea to be able to see the data that we actually send here when we're running this graph. So what I'll also do is add a wiretap. So if I do a search for wiretap, we'll select it and we'll just put the output of the open API servlo into the wiretap. Now we want to write the data. So to do this, if I do a search for write file, this operator will enable us to take the data that we receive in mailman or an app and then write it to a file. So then what we need to do, of course, is join the wiretap to the write file and we'll be prompted with the conversion method that we want to choose. We just want the actual message so we'll choose that first option. Next it'll be a good idea to choose where we save the data. So what I'll do is if I configure my write file, on the right hand side we can choose our connection. So if I modify it and we use the connection manager, I'm going to choose my semantic data lake. The name of that is di-datalake and I'll click on save. We've got a few more options to change. We need to choose the path mode and we're going to choose that from which is static from configuration. And that's because we're going to actually set the path here. Now the path I'm going to write to, we can see that if we go back to the Metadata Explorer, we're going to write to this path, we're going to put the file in this folder in this connection. So that means the path is going to be in my Shared folder and it will be in the forward slash SHA folder. Now we've got a couple of options. One of them is we can write to an existing file, and of course we could write to that performance.csv file, and then we can just append record to that file. All what I'm going to do is write to a new file, so you can clearly see very quickly that we're writing the data. So I'll give the file the name as follows, and of course what that means is that we should see a new file appear here within that folder. That means the mode we're going to select is, we've got a different mode, Overwrite, Append or Create Only, but I'm going to choose Overwrite. If I overwrite, that means each subsequent time I send any messages for testing, we'll see the new data appear. The last operator we need to add is a workflow terminator. So I'll do a search for workflow terminator, and I'll drag that onto the screen. And of course, I'll put the output of the right file, not the error, the outputs of the file into the workflow terminator. Now, what this will mean for us is when we send the message via the app, or whether we send it through Mailman or Python, what will happen is because we receive the message, the actual graph will stop running. But as you can imagine, in a productive environment, if you want to keep consistently receiving messages, you would want the graph to remain running, which means you wouldn't have any form of terminator. So lastly we just need to save, and I'll give my graph a name. We can see in the log file that we've created that graph. At the moment nothing is running. So, of course, the last step is to run this graph. And it should stay in a running status until we receive a message. So, let's just make sure it doesn't error. And here we can see it's running. Now, of course, even though it's running, if I go to my wiretap, we're not going to receive any messages until we actually send a message. So, we'll cover how to do that in mailman in the next video. You can find more tutorials on our YouTube channel and if you'd like to be informed as soon as new video tutorials are published, then please subscribe. Thanks for watching.