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Hello everyone, I'm Saveen Reddy,
a Group Program Manager in Microsoft's big data team.
And I'm gonna show you how easy it is to be productive as a developer
with Azure Data Lake.
Now, Azure Data Lake has great integration with Visual Studio.
We not only have IntelliSense,
we can also let you extend U-SQL as C# Code Behind, submit and
monitor those jobs, and most importantly we've made
debugging your code, executing in a distributed framework.
Amazingly simple, and this is what we're gonna show in the demo.
So what we're looking at here is Azure Daylight Tool for
Visual Studio inside the Visual Studio 2015.
I have a simple U-SQL script up.
As you can see, I have clarity row set called A.
Which is just two tweets, and I'm declaring the row set called B,
which selects a single column for row set A.
And I output that as a CSV file.
Now, you can see here, as I hit the .symbol, that full IntelliSense
is supported because the used SQL types are the C# or .NET types.
So I can do ToUpper as some column.
Now, what if I have something that's more complex than that?
And I want not just a simple little C# expression, but
I need to put it in a bigger method.
We have a code behind file, and I'll show you that file, and
I have pre-created a function called normalize author and in this case
I've designed this thing to trim a string and make it uppercase.
And in addition,
I've actually created a simple deliberate error in this.
So we're gonna use this to debut a problem during script execution.
Let's close this and paste in this code.
Now, as you can see the code that I have and the code behind can
immediately be accessed by the U-SQL without any uploading,
any registration.
All just works seamlessly.
So if I hit Submit, this group will run and
as I mentioned before, this script is designed to fail.
This is the next step,
not only have you made this simple with IntelliSense and
this code behind C# editing have also made it simple to debug a job.
Let's take a look at a job that I ran previously and
this is the same script.
And you can see that it's actually failed.
And of course we know the reason why.
But let's see what happens, how we can investigate this issue.
Because this code ran in a cluster that you don't have access to it.
So how do we make debugging simple?
We will click on this job, we'll click Open.
And then, what's interesting
is the new instance of Video Studio will launch.
In this case, in fact, Visual Studio 2017 and
the very piece of code that failed in our cluster will be downloaded.
That means the code you wrote, the U-SQL code,
our U-SQL run time as well as any C# code.
And as soon as Visual Studio 2017 launches you will see a new project
that's automatically being created which is called in this case,
automatically.
ADL tool, code behind debugging.
Now, as any .NET developer would, let me get a solution,
a project, and someone tells us hey, there's an error.
An exception is being thrown.
What's our first instinct?
Start debugging the project.
So without any further configuration of the system or the tooling or
configuring our Azure service, let's just start debugging and
see if you can find the error.
So I clicked Start and
what's happening is that the script is being compiled.
The full U-SQL runtime is running it in the context of Visual Studio
debugging.
And let's see if it, and look at there.
We've actually, the break point has been thrown exactly on
the line of code that failed.
And even though this code was all run in a distributed environment in
the cloud, our debugging is now seamless just as you would expect
within Visual Studio.
Wasn't that amazing?
If you're a .NET developer,
this is exactly what you'd imagine debugging should be in the cloud.
All made possible through the tight integration of
Azure Data Lake Analytics, U-SQL, and Visual Studio.
For more, go to aka.ms/azuredatalake nd find out everything you need to
know to get started now.
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