Opa Application Development by Li Wenbo

By Li Wenbo


Opa program improvement dives into the entire recommendations and elements required to construct an online program with Opa. the 1st 1/2 this publication indicates the elemental development blocks that you'll want to improve an Opa program, together with the syntax of Opa, net improvement facets, patron and server conversation, in addition to cutting, plugins, databases, and so on.

Opa is a full-stack open resource internet improvement framework for JavaScript that permits you to write safe and scalable net functions. It generates the normal Node.js and MongoDB purposes, natively helps HTML5 and CSS, and automates many facets of recent net program programming. It handles all features of internet programming written in a single constant language and is compiled to net standards.

This publication is a pragmatic, hands-on consultant that gives you with a few step by step routines. It covers just about all the facets of constructing an online software with Opa, so that it will assist you benefit from the genuine strength of Opa to construct safe and robust internet purposes rapidly.

Required wisdom for this publication is as follows:

•Basic wisdom approximately HTML and CSS
•Basic wisdom approximately JavaScript
•Some programming experience

Software required for this ebook is as follows:

•The Opa framework
•A textual content editor software, SublimeText is suggested

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Sample text

It is likely that in the coming months and years there will be additional entries, so just because a tool or service isn’t mentioned here doesn’t mean that it doesn’t exist. Chapter 2, “BigQuery Fundamentals,” goes into more detail about the individual components, but this is a quick survey of the offerings. You can divide the cloud offerings into three portions: processing, storage, and analytics. Chapter 1 ■ The Story of Big Data at Google Cloud Processing The cloud processing components enable you to run arbitrary computations over your data: ■ Google Compute Engine (GCE): The base of Google’s Cloud Platform, GCE is infrastructure-as-a-service, plain and simple.

Multitenancy and Parallel Execution When you run a query on MySQL that takes one second, you get to occupy a single processor core for one second. If you have eight processors, you can run eight queries at once. Amazon Redshift lets you run a single query in parallel, but on a fixed number of cores that are all yours for the entire time you are renting the Redshift instance. BigQuery operates on a fundamentally different model; your query will run on thousands of cores in parallel. If you have eight queries, those may all run on a thousand cores in parallel.

This type of failure still wouldn’t take BigQuery Chapter 2 ■ BigQuery Fundamentals down, however, since BigQuery runs in multiple geographically distributed datacenters and will fail over automatically. Of course, this is where we have to remind you that all software is fallible. Just because your data is replicated nine ways doesn’t mean that it is completely immune to loss. A buggy software release could cause data to be inadvertently deleted from all nine of those disks. If you have critical data, make sure to back it up.

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