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Titlebook: Beginning Apache Spark Using Azure Databricks; Unleashing Large Clu Robert Ilijason Book 2020 Robert Ilijason 2020 Azure Spark.Cloud Analy

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發(fā)表于 2025-3-21 16:42:19 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Beginning Apache Spark Using Azure Databricks
期刊簡稱Unleashing Large Clu
影響因子2023Robert Ilijason
視頻videohttp://file.papertrans.cn/183/182234/182234.mp4
發(fā)行地址Teaches you how to extract value from massive datasets, using a toolset that can be up and running the same day.Shows you why Azure Databricks is an up-and-coming, fast-growing tool that anyone in dat
圖書封面Titlebook: Beginning Apache Spark Using Azure Databricks; Unleashing Large Clu Robert Ilijason Book 2020 Robert Ilijason  2020 Azure Spark.Cloud Analy
影響因子.Analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud. Learn the fundamentals, and more, of running analytics on large clusters in Azure and AWS, using Apache Spark with Databricks on top. Discover how to squeeze the most value out of your data at a mere fraction of what classical analytics solutions cost, while at the same time getting the results you need, incrementally faster...This book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. You will begin by learning how cloud infrastructure makes it possible to scale your code to large amounts of processing units, without having to pay for the machinery in advance. From there you will learn how Apache Spark, an open source framework, can enable all those CPUs for data analytics use. Finally, you will see how services such as Databricks provide the power of Apache Spark, without you having to know anything aboutconfiguring hardware or software. By removing the need for expensive experts and hardware, your resources can instead be allocated to actually finding business value in the data...This book guides you through
Pindex Book 2020
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沙發(fā)
發(fā)表于 2025-3-21 22:33:41 | 只看該作者
板凳
發(fā)表于 2025-3-22 03:42:06 | 只看該作者
https://doi.org/10.1007/978-3-322-85729-3Let’s start at the very top. This book is about large-scale data analytics. It‘ll teach you to take a dataset, load it into a database, scrub the data if necessary, analyze it, run algorithms on it, and finally present the discoveries you make.
地板
發(fā)表于 2025-3-22 06:38:48 | 只看該作者
https://doi.org/10.1007/978-3-322-85729-3Apache Spark has taken the world by storm the last few years. In this chapter, we’ll go through why it’s so and what Apache Spark actually is. We’ll also take a look at what Databricks brings to the table.
5#
發(fā)表于 2025-3-22 10:47:28 | 只看該作者
https://doi.org/10.1007/978-3-322-85729-3In this chapter, I’ll show you how to get Databricks up and running in different cloud solutions. We’ll go through the different options you have to choose from and the pricing model that comes with them.
6#
發(fā)表于 2025-3-22 16:06:56 | 只看該作者
Organization: From Substance to Image?Finally, you have Databricks up and running on whatever your platform of choice is. For the most part, it doesn’t really matter if you’re on AWS or Azure from a user interface standpoint; Databricks looks the same.
7#
發(fā)表于 2025-3-22 18:20:20 | 只看該作者
https://doi.org/10.1007/978-3-030-67784-8All the processing power in the world is of no use unless you have data to work with. In this chapter, we’ll look at different techniques to get your data into Databricks. We’ll also take a closer look at file types that you are likely to come across in your data work.
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發(fā)表于 2025-3-22 22:20:10 | 只看該作者
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發(fā)表于 2025-3-23 03:20:51 | 只看該作者
https://doi.org/10.1007/978-1-4419-7350-4Python has quickly become one of the most important tools in the data science and data engineering communities. This chapter digs deeper into how you can use this language together with the Apache Spark DataFrames API to work with data in an efficient way.
10#
發(fā)表于 2025-3-23 06:24:59 | 只看該作者
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