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AWS云端的Big Data

5 Steps 小时 51 积分

科学家,开发者和其他来自各行各业地技术人员可以利用AWS来进行大数据分析,以满足不断增加地数据量,数据种类和快速访问数字信息的需求带来的挑战。AWS提供云计算服务的服务组合,可以帮助你降低成本,弹性扩展来满足业务需求,并且加快创新的步伐。在本任务中,你将学习使用大数据的基本服务。

Objectives:

This quest is designed to teach you how to work with AWS services to perform big data analytics on the cloud.

Quest Outline

Hands-On Lab

使用 Amazon Redshift

本实验演示了如何使用 Amazon RedShift 来创建集群、加载数据、运行查询以及监控性能。注意:在本实验中,学员需要下载免费的 SQL 客户端。

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Hands-On Lab

Exploring Google Ngrams with Amazon EMR

This lab demonstrates how to launch an Amazon Elastic MapReduce (EMR) cluster for Big Data processing and use Hive with SQL-style queries to analyze data. You will create a Hadoop cluster using Amazon EMR which will allow to run interactive Hive queries against data stored in Amazon S3. You will use Hive to normalize the data in a more useful way, and you will run queries to analyze the data.

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Hands-On Lab

Analyze Big Data with Hadoop

In this lab, you will deploy a fully functional Hadoop cluster, ready to analyze log data in just a few minutes. You will start by launching an Amazon EMR cluster and then use a HiveQL script to process sample log data stored in an Amazon S3 bucket. HiveQL is a SQL-like scripting language for data warehousing and analysis. You can then use a similar setup to analyze your own log files.

Hands-On Lab

warning Advanced Amazon Redshift: Table Layout and Schema Design

In this lab, you will take a close look at different types of table layout and schema design. You will create tables using various methods for data compression and distribution, and analyze which methods work best, including incorporating Amazon Redshift recommendations. You will conclude the lab by building five different versions of the same table, and analyzing how the differences impact storage requirements and query performance. Pre-requisites: To successfully complete this lab, you should be familiar with Redshift concepts. Knowledge of SQL programming is required, although full solution code is provided.

Hands-On Lab

warning Advanced Amazon Redshift: Data Loading

In this lab, you will experiment with and compare different types of data loading using Amazon Redshift. You will create tables, load data using S3, remote hosts, and practice troubleshooting data loading errors. For the lab to function as written, please DO NOT change the auto assigned region.

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