Welcome to the Cloud Computing Applications course, the first part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this first course we cover a multitude of technologies that comprise the modern concept of cloud computing. Cloud computing is an information technology revolution that has just started to impact many enterprise computing systems in major ways, and it will change the face of computing in the years to come. We start the first week by introducing some major concepts in cloud computing, the economics foundations of it and we introduce the concept of big data. We also cover the concept of software defined architectures, and how virtualization results in cloud infrastructure and how cloud service providers organize their offerings. In week two, we cover virtualization and containers with deeper focus, including lectures on Docker, JVM and Kubernates. We finish up week two by comparing the infrastructure as a service offering by the big three: Amazon, Google and Microsoft. Week three moves to higher level of cloud offering, including platform as a service, mobile backend as a service and even serverless architectures. We also talk about some of the cloud middleware technologies that are fundamental to cloud based applications such as RPC and REST, JSON and load balancing. Week three also covers metal as a service (MaaS), where physical machines are provisioned in a cloud environment. Week four introduces higher level cloud services with special focus on cloud storage services. We introduce Hive, HDFS and Ceph as pure Big Data Storage and file systems, and move on to cloud object storage systems, virtual hard drives and virtual archival storage options. As discussion on Dropbox cloud solution wraps up week 4 and the course.
3.3.5 JSON
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來自 University of Illinois at Urbana-Champaign 的課程
Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure
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Module 3: MAAS, PAAS, Web Services
Welcome to the third module, where we introduce Metal as a Service (provision real hardware in the cloud), Platform as a Service (provide a platform to run user code on) and Web Middleware as the glue technology that empowers cloud computing.
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Roy H. CampbellProfessor of Computer Science
Department of Computer Science
Reza FarivarData Engineering Manager at Capital One, Adjunct Research Assistant Professor of Computer Science
Department of Computer Science
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So it's worth mentioning how does JSON differ from XML.
What is JSON?
Why is it so popular these days?
JSON works with JavaScript.
It's very efficient to use with JavaScript,
and is very familiar if you already know JavaScript.
Then JSON is very, very simple to actually use.
So, we're looking at lightweight data interchange format across the web.
We are looking for one that's easy for humans to read,
because then it's easy to program and it's easy to debug.
It turns out if it's easy for humans to read, it's also easy for
machines to pass and generate.
And there's a JSON.org that's dedicated to that cause.
It really is just a subset of JavaScript.
If you know JavaScript,
then JSON is just one of the structures that you program with within JavaScript.
But now it's actually used to record what
the documents are that you're passing in a message across the way.
So what does it look like?
Well, we mentioned that it had braces and this expands what we described.
It shows you that, in fact, those braces can designate various fields.
Those fields can Include different types of stretches.
Here we've got a firstName, a lastName, and address.
And associated with firstName, we have instances of that name, ie John.
Associated with lastName, we have Smith.
Associated with address, well we can go into a hierarchy,
we can have another record.
And repeat the same structure so
you see street address, you see city, state, postal code.
And then we can have instances of street address, 21 2nd Street City, New York.
So this is a generalizable format
in a hierarchical manner to pretty much any data.
And it tells you not only what the data is, the value of the data like John Smith.
But it tells you, what is John?
Well it's his first name.
It gives you use some semantics to deal with the data structure.
So, these are basically name value pairs.
You have a name for well, for John.
And the value for John is obviously John, the letters, the person.
And so, in each of these different instances that occurs again.
If you're talking about address,
that you have a complicated data structure associated with a dress.
It's a hierarchical one.
Those are called child properties.
And basically they consist of a number of name value pairs again.
If you have a number you can insert it.
So postal code and the number in there.
That number is Is a valid way.
You don't need to put in quotes because it will be actually encoded as
a straight forward number from zero to ten, up to however many digits.
If you need more sophisticated data types
you can put them in between quotes and have strings.
And there's some examples of phone numbers
to string arrays associated with phone numbers.
And you can have any arbitrary number of those telephone numbers.
And they're just a list associated with the name phone number.
So, why is this good?
Well, JSON Uses a sort of railway diagram type of scenario for
coding and decoding its data structures.
And pretty much can use that directly for doing this messaging.
So if you are thinking about how to analyze,
to take the request you want, put it into a message.
Or to take a message and transcribe it back.
And these railway diagrams allow you to follow a very simple algorithm to turn
the data into a message, or message into the data.
It starts off when you can see here a very simple one for
the strings the name, and a value.
What will happen is this will get
decoded into a bigger railroad diagram describing, well, what's a string?
Well, it's starts with a quotation mark, and
then you can put all sorts of things in the string.
And then at the end, there'll be another quotation mark.
And that takes you off.
The railway diagram.
So this is sort of like a shunting yard, if you like, for characters.
But it's very simple.
It's just a straight forward type of state machine, type of description.
The key thing is that JavaScript will allow you to do this trivially.
And so it makes use of JSON very simple.
Now some of the other user data structures,
the values get encoded into different types of railway diagrams.
Different other data structures will get coding similarly.
This one gets here coded into something that will recognize numbers.
So you can sort of go down this list, and you can notice
actually it's this sort of recursive descent algorithm that's being employed to
actually decode these strings and transfer the data.
And that's really one of the nice things about this is
it's really a state machine based system.
Where the transitions will take you to different diagrams,
allow you to decode the diagrams, and then let you rebuild.
The values that you've got from it.
So here we've got an array, and the array will consist of multiple values.
And when you see the closing parenthesis, you know you're finished with the array.
So those data disks, data structures are very simple.
If you sit down and you want to compare that with XML It's a great exercise.
What you'll see is XML is very difficult to keep track of.
It's still organized as a hierarchy.
It's still machine and user readable.
They both employ hierarchical data structures.
JSON doesn't have the validation system because JavaScript essentially does that.
XML, on the other hand, does have XSD that validates the structures.
It's okay.
The namespaces, there are no namespaces.
It's just what you write.
The XML does have namespaces in case you should need them.
Passing, well.
Essentially there's just JavaScript.
You can evaluate JavaScript data structure with an eval.
Just bringing the thing in and it decodes it into JavaScript.
It's fast.
There are security issues with that.
But it's very easy to write.
Parsing, on the other hand, for
XML, you need some sort of description on how to parse it.
You need a parser.
You need to understand how to organize things.
There's a processor called x path to do that, which is totally separate.
So, as you can see there's more overhead with XML.
With JavaScript you can work with objects, run time evaluation of types.
It's all very simple.
If you use JavaScript for XML you can work with string,s but
you might require additional parsing mechanisms to actually parse the XML and
convert it into things you can use in the JavaScript.
Security, both JSON and XML have their problems with security.
Because in JSON it decodes it fairly automatically,
and you could get any sort of thing in it a descriptor.
And JSON would decode it, and if you can break in or
call some action that's detrimental.
That is very easy to do.
There are libraries to make that more resilient.
But the basic mechanism is not very secure.
The XML, the security is text parsing.
It's not code execution, so there's a parser that would operate.
So, you have a little bit of distance between
text parsing and the actual code that you're going to use in the server.
But, never the less you could generally put anything XML and
the text parsing will break it apart.
If it's correct XML you would still need some sort of security at the processing
level of the actual information you could add to the XML document.
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