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HDP > Hadoop を使用した開発 > 入門編の基本

Hadoop Tutorial – Getting Started with HDP

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Hello World is often used by developers to familiarize themselves with new concepts by building a simple program. This tutorial aims to achieve a similar purpose by getting practitioners started with Hadoop and HDP. We will use an Internet of Things (IoT) use case to build your first HDP application.

This tutorial describes how to refine data for a Trucking IoT Data Discovery (aka IoT Discovery) use case using the Hortonworks Data Platform. The IoT Discovery use cases involves vehicles, devices and people moving across a map or similar surface. Your analysis is targeted to linking location information with your analytic data.

For our tutorial we are looking at a use case where we have a truck fleet. Each truck has been equipped to log location and event data. These events are streamed back to a datacenter where we will be processing the data.  The company wants to use this data to better understand risk.

Here is the video of Analyzing Geolocation Data to show you what you’ll be doing in this tutorial.

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Hadoop Tutorial – Getting Started with HDP

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limit number of paragraphs in sandboxed Zeppelin
by Tom Celuszak on November 29, 2018 at 11:20 am

Good tutorial, introduced me to Zeppelin and let me exercise some of its functions. Had a problem with the final query - the join of riskfactor and geolocation - hanging. I could get the same query to complete using Ambari and Hive View 2. Finally found that removing all but one paragraph, of which I had... 20 or so? ...let the query run to completion in 23 seconds. I had been creating a new paragraph each step; best to reuse the first paragraph. My config is the sandbox on VirtualBox on Windows 7.

Good tutorial, introduced me to Zeppelin and let me exercise some of its functions.

Had a problem with the final query – the join of riskfactor and geolocation – hanging. I could get the same query to complete using Ambari and Hive View 2. Finally found that removing all but one paragraph, of which I had… 20 or so? …let the query run to completion in 23 seconds. I had been creating a new paragraph each step; best to reuse the first paragraph.

My config is the sandbox on VirtualBox on Windows 7.

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Easy to understand
by Dennis Suhari on October 19, 2018 at 12:27 am

Informative and good practical description of the steps

Informative and good practical description of the steps

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Great Tutorial
by scott payne on July 24, 2018 at 8:55 pm

Tutorial was an excellent introduction to HDP data processing using a realistic data set. Each concept is presented succinctly with suggestions to explore the concept further. My only suggestion is that not enough emphasis is placed on how much faster it is to run your queries using a shell than it is to use the sandbox.

Tutorial was an excellent introduction to HDP data processing using a realistic data set. Each concept is presented succinctly with suggestions to explore the concept further.

My only suggestion is that not enough emphasis is placed on how much faster it is to run your queries using a shell than it is to use the sandbox.

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Outstanding
by Christian Lopez on May 8, 2018 at 8:29 pm

This review is written from the perspective of a new HDP user interested in understanding this environment and the tools included in the Sandbox. First you will be introduced to the technologies involved in the tutorial namely Hadoop, Ambari, Hive, Pig Latin, SPARK, HDFS, and most importantly HDP. Next, you will use IoT data to calculate the risk factor for truck drivers by using the truck's information and their geo-location, you will accomplish this goal by uploading the needed data to your VM and storing the data as Hive tables. Additionally, you will learn to use… Show More

This review is written from the perspective of a new HDP user interested in understanding this environment and the tools included in the Sandbox.

First you will be introduced to the technologies involved in the tutorial namely Hadoop, Ambari, Hive, Pig Latin, SPARK, HDFS, and most importantly HDP. Next, you will use IoT data to calculate the risk factor for truck drivers by using the truck’s information and their geo-location, you will accomplish this goal by uploading the needed data to your VM and storing the data as Hive tables. Additionally, you will learn to use PIG Latin and SPARK to extrapolate the data needed to find the risk factor for all drivers in the set and storing the information you found back into the database. Accomplishing the same task using two different tools (SPARK, and PIG) highlights the robustness and flexibility of HDP as all the operations happen flawlessly.

I highly recommend this tutorial as it is highly informative, shows a realistic use-case, and as a new user of HDP I learned about all the cool technologies enabled to work through the Hortonworks platform, most importantly I was left with a great sense of accomplishment and that’s reason alone to try the tutorial.

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Excellent Tutorial!
by Ana Castro on May 8, 2018 at 4:05 pm

The tutorial was very informative and had an excellent flow. It had just the right amount of detail per concept. Great introduction to Hadoop and other Apache projects.

The tutorial was very informative and had an excellent flow. It had just the right amount of detail per concept. Great introduction to Hadoop and other Apache projects.

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