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AWS云端的Big Data

3 个步骤 5 个小时 26 个积分

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。

目标:

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

Quest Outline

实操实验

Working with Amazon Redshift

The lab demonstrates how to use Amazon RedShift to create a cluster, load data, run queries and monitor performance. Note: Students will download a free SQL client as part of this lab.

English 日本語
实操实验

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.

English 日本語
实操实验

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.

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