Learn Azure Data Lake Analytics by Example

Learn Azure Data Lake Analytics by Example

Learn Azure Data Lake Analytics by Example

Azure Data Lake Analytics, is a powerful on-demand analytics job service on Microsoft Azure. By reading this article, you can learn Azure Data Analytics by Example.

 

The Example

Since this is an introductory article on Azure Data Lake Analytics, the example that will be presented, will be a simple one just to showcase the technology. The rest is left to your imagination and creativity!

More specifically, in this simple example, I will create and submit for execution 2 jobs:

  • Job 1
    • Create a sample database and table
    • Populate the table with sample data
  • Job 2
    • Query the sample table and extract the data into a .csv file

 

Creating an Azure Data Lake Analytics Account

Step 1: Create a new resource

The first step, is to create an Azure Data Lake Analytics account, in case you don’t already have one.

You can easily do this, by creating a new resource – Data Lake Analytics:

Learn Azure Data Lake Analytics by Example

 

Then, you will need to specify some details, as shown in the below screenshot:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Right after the above steps, within a few minutes, the Azure Data Lake Analytics account is ready for use:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Step 2: Configure firewall

The next step is to configure the Firewall rules for the newly created Azure Data Lake Analytics account. In my example, I have just added the IP of my client.

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Creating and Submitting Jobs on Azure Data Lake Analytics

Now that the Azure Data Lake Analytics account is ready to accept jobs for execution, let’s create and submit a new job.

 

Define First Job

As mentioned earlier, in this example I will create and submit for execution 2 simple jobs.

The first job is to create a sample database and table, and then populate it with sample data.

So, in order to create the job, within the Azure Data Lake Analytics account, you click on the link “New job”.

Then, in this example, I used U-SQL, in order to define the job:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Submit First Job for Execution

After submitting the job for execution, I can see that it was successfully executed.

Below, you can see the relevant job graph that illustrates the job’s execution steps, as created by the powerful engine behind Azure Data Lake Analytics.

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

AU Analysis

Moreover, in the “AU analysis” tab, you can get more statistics and shortcuts to further optimize your job (i.e. for performance, balanced execution, etc.).

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Data Explorer

Now, let’s check also via Data Explorer, to see our table:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Define Second Job

Now, let’s define the second which will extract the data from the sample table into a .csv file.

This time, I have created the job right from within Data Explorer:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Submit Second Job for Execution

After submitting the second job for execution, again, I can see that it was successfully executed.

Below, you can see the relevant job graph that illustrates the job’s execution steps:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

 

Check the Second Job’s Outcome

Let’s check the second job’s outcome. As you can see in the below screenshot, the .csv file has been successfully created, and we can check its contents:

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Job Insights

When we click on “Job insights”, we can see useful information and statistics about our jobs executed in Data Lake Analytics.

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Azure Data Lake Tools

Azure Data Lake Analytics, integrate with many tools that you can use to create and submit different jobs.

For example, if you click on the “Tools” link, you will easily get started with the below tools:

  • Data Lake Tools for Visual Studio
  • Data Lake Tools for Visual Studio Core
  • Azure PowerShell
  • Azure CLI

Learn Azure Data Lake Analytics by Example - SQLNetHub

 

Conclusion

Azure Data Lake Analytics, is a powerful engine, which allows you to create and execute heavy jobs on Microsoft Azure. Depending on the job type, Azure Data Lake Analytics automatically scale, thus making efficient use of its powerful engine, in order to execute the job. Moreover, it provides in-depth insights and statistics, which help you assess each job’s execution, or even change how each jobs should execute.

 

With Azure Data Lake Analytics, you can process any data (relational, unstructured, big data, and more) through its job system fast and efficiently.

 

Learn More

 

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Reference: SQLNetHub.com (https://www.sqlnethub.com)

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Artemakis Artemiou
Artemakis Artemiou is a Senior SQL Server and Software Architect, Author, and a 9 Times Microsoft Data Platform MVP (2009-2018). He has over 15 years of experience in the IT industry in various roles. Artemakis is the founder of SQLNetHub and TechHowTos.com. Artemakis is the creator of the well-known software tools Snippets Generator and DBA Security Advisor. Also, he is the author of many eBooks on SQL Server. Artemakis currently serves as the President of the Cyprus .NET User Group (CDNUG) and the International .NET Association Country Leader for Cyprus (INETA). Artemakis's official website can be found at aartemiou.com.