In this post we will discover how to:
GitHub source code: https://github.com/vunvulear/IoTHomeProject
Push content from Azure Stream Analytics to Azure Service Bus
This step is the most simple one. We just need to Add a new output to Stream Analytics and specify the Service Bus Topic where we want to push data. After this, we'll need to update the Stream Analytic query by adding:
Remarks: Don't forget to create a subscription for the topic. I send all the information to topic (not only temperature), because I plan in the future to add filters to each subscription and root data based on this parameters.
Azure Function to push data from Service Bus Topic to Azure Table
Offtopic: This step is done artificially in our case, we could forward content directly to Azure Table from Stream Analytics. I wanted to do this because the main scope is to play with as many Azure Services as possible. Additional to this, inside Azure Function we could aggregate information from other sources to decide if we want to start/stop the heating system.
Now, we will create a Azure Table in our storage with two rows, that contain current temperature and desired temperature. We could also add another row that contain a flag that specify to the system to start/stop the heating system, but for now we will not add it.
The table should look like this:
From Azure Portal, in the moment when we want need to create the Function itself we shall specify that for Trigger we want to have Service Bus Topic. For output we'll specify Azure Tables. At this step you need to specify connection information for Service Bus and Azure Table. Once you done this, you'll be ready to write your first Azure Function in Node.JS
Surprise! Even if the function is written as in the book, an error will pop-up. This happens because in this moment Azure Function allows us only to add new rows to an Azure Table. Updating existing one is not possible.
The good news is that there is a small hack that we can do. Nothing block us to install Azure Storage module from npm and use it directly inside our function. To do this, you'll need to access the Kudu portal of you Azure Function. The URL is https://[FunctionAppName]scm.azurewebsites.net/ and you'll authenticate with Azure credentials.
From there, go to 'Debug Console' and type 'npm install azure-storage'. Once you install this module you can make any calls to Azure Storage using Node.JS module.
I prefered to use process environments values to specify storage connection information. There is another way to do this, by specifying this data when you make the call to 'createTableService'. There is no error handling done, being a sample code.
ASP.NET Core that plays the role of heating system
There not to many things to say about it. It is a simple web application, that display minimum temperature, current temperature and heating system status.
Remember:
- Push content from Azure Stream Analytics to Azure Service Bus
- Write an Azure Function in Node.JS that fetch data from Azure Service Bus Topic and push it to Azure Table
- Develop a ASP.NET Core application that plays the role of a heating system that start/stop the heating in a house
- Use temperature data collected from sensors connected to Raspberry PI to start/shop a heating system from a house
GitHub source code: https://github.com/vunvulear/IoTHomeProject
Push content from Azure Stream Analytics to Azure Service Bus
This step is the most simple one. We just need to Add a new output to Stream Analytics and specify the Service Bus Topic where we want to push data. After this, we'll need to update the Stream Analytic query by adding:
SELECT
*
INTO
outputSensorDataTopic
FROM
avgdata
, where 'outputSensorDataTopic' is the name of the output that we created a few seconds ago.Remarks: Don't forget to create a subscription for the topic. I send all the information to topic (not only temperature), because I plan in the future to add filters to each subscription and root data based on this parameters.
Azure Function to push data from Service Bus Topic to Azure Table
Offtopic: This step is done artificially in our case, we could forward content directly to Azure Table from Stream Analytics. I wanted to do this because the main scope is to play with as many Azure Services as possible. Additional to this, inside Azure Function we could aggregate information from other sources to decide if we want to start/stop the heating system.
Now, we will create a Azure Table in our storage with two rows, that contain current temperature and desired temperature. We could also add another row that contain a flag that specify to the system to start/stop the heating system, but for now we will not add it.
The table should look like this:
From Azure Portal, in the moment when we want need to create the Function itself we shall specify that for Trigger we want to have Service Bus Topic. For output we'll specify Azure Tables. At this step you need to specify connection information for Service Bus and Azure Table. Once you done this, you'll be ready to write your first Azure Function in Node.JS
module.exports = function (context, myQueueItem) {
context.bindings.outputtable = {
"partitionkey": "system",
"rowkey":"currenttemperature",
"status": myqueueitem.avgtemp
};
context.log('Avg. temp: ', myQueueItem.avgtemp);
context.done();
};
Surprise! Even if the function is written as in the book, an error will pop-up. This happens because in this moment Azure Function allows us only to add new rows to an Azure Table. Updating existing one is not possible.
The good news is that there is a small hack that we can do. Nothing block us to install Azure Storage module from npm and use it directly inside our function. To do this, you'll need to access the Kudu portal of you Azure Function. The URL is https://[FunctionAppName]scm.azurewebsites.net/ and you'll authenticate with Azure credentials.
From there, go to 'Debug Console' and type 'npm install azure-storage'. Once you install this module you can make any calls to Azure Storage using Node.JS module.
process.env["AZURE_STORAGE_ACCOUNT"] = "vunvuleariotstorage";
process.env["AZURE_STORAGE_ACCESS_KEY"] = "@@@";
process.env["AZURE_STORAGE_CONNECTION_STRING "] = "@@@";
module.exports = function (context, myQueueItem) {
var azure = require('azure-storage');
var tableSvc = azure.createTableService();
tableSvc.createTableIfNotExists('systemstatus', function (error, result, response) {
if (!error) {
var entityToUpdate = new Object();
entityToUpdate.PartitionKey = "system";
entityToUpdate.RowKey = "currenttemperature";
entityToUpdate.Status = myQueueItem.avgtemp.toString();
tableSvc.insertOrReplaceEntity('systemstatus', entityToUpdate, function (error, result, response) {
if (!error) {
context.log('Avg. temp: ', myQueueItem.avgtemp);
}
});
};
});
context.done();
};
I prefered to use process environments values to specify storage connection information. There is another way to do this, by specifying this data when you make the call to 'createTableService'. There is no error handling done, being a sample code.
ASP.NET Core that plays the role of heating system
There not to many things to say about it. It is a simple web application, that display minimum temperature, current temperature and heating system status.
Remember:
- There is not yet full support for all Azure Storage actions from Azure Function
- You can load any module in Azure Function using NPM
- You can add or remove inputs and outputs for of a Stream Analytics as you wish
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