Analytic Data Storage in Hadoop Training Video

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Analytic Data Storage in Hadoop Training Video A Practical Training Course That Teaches Real World Skills In this project-based Analytic Data Storage in Hadoop video tutorial series, you'll quickly have relevant skills for real-world applications. Follow along with our expert instructor in this training course to get: Concise, informative and broadcast-quality Analytic Data Storage in Hadoop training videos delivered to your desktop The ability to learn at your own pace with our intuitive, easy-to-use interface A quick grasp of even the most complex Analytic Data Storage in Hadoop subjects because they're broken into simple, easy to follow tutorial videos Practical working files further enhance the learning process and provide a degree of retention that is unmatched by any other form of Analytic Data Storage in Hadoop tutorial, online or offline... so you'll know the exact steps for your own projects. Course Fast Facts: Only 6 hours to complete this course 43 tutorial videos Expert instructors lead each course Download to any Windows PC or Mac and save for viewing off line Course is accessible 24/7 from any computer once downloaded You can study from home or at work at your own pace in your own time Course Description In this Analytic Data Storage in Hadoop training course, expert author Ryan Blue will teach you about typical storage and ingest patterns in Hadoop. This course is designed for users that are already familiar with Hadoop.

You will start by learning how to create the dataset, load sample data, and query a dataset. From there, Ryan will teach you about partitioning, formats, and Avro. This video tutorial also covers parquet, bulk data drops, and database snapshots and mirroring. Finally, you will learn about event stream processing, including how to build a test pipeline and move to production.

Once you have completed this computer based training course, you will have gained a solid...

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O que se aprende nesse curso?

Database training
Skills and Training


  • 01. Introduction
    • Introduction And What To Expect
    • About The Author
    • Introduction To The Movielens Dataset
    • 0104 How To Access Your Working Files
  • 02. Getting Started With Hadoop
    • Your First Hadoop Dataset - CSV To SQL Query
    • Describing Your Data With A Schema
    • Creating The Dataset
    • Loading Sample Data
    • Querying A Dataset
  • 03. Partitioning
    • Introduction to Partitioning
    • Testing Partition Strategies
    • Partitioning Patterns
  • 04. Formats
    • 0401 Introduction To File Formats
    • 0402 Hadoop File Formats - Why Splitability Matters
    • 0403 Hadoop File Formats Review
  • 05. Avro
    • 0501 Avro
    • 0502 Avro File Format
    • 0503 Avro Shemas
    • 0504 Avro Object Models
    • 0505 Avro Tools
  • 06. Parquet
    • 0601 Parquet
    • 0602 Parquet File Formats
    • 0603 Parquet Object Models
    • 0604 Parquet Tools
  • 07. Bulk Data Drops
    • 0701 Application Pattern Overview - Bulk Data Drops
    • 0702 Apache Nifi - Part 1
    • 0703 Apache Nifi - Part 2
    • 0704 Using Apache Nifi
    • 0705 Preparing The Datasets
    • 0706 Building The Data Flow - Part 1
    • 0707 Building The Data Flow - Part 2
  • 08. Database Snapshots And Mirroring
    • 0801 Application Pattern Database Snapshots And Mirroring
    • 0802 Introduction To Apache Sqoop
    • 0803 Table Snapshots
    • 0804 Incremental Mirroring - Part 1
    • 0805 Incremental Mirroring - Part 2
    • 0806 Moving To Production
  • 09. Event Stream Processing
    • 0901 Application Pattern - Event Streams
    • 0902 Introduction To Apache Flume
    • 0903 Building A Pipeline - Part 1
    • 0904 Building A Pipeline - Part 2
    • 0905 Moving to Production
  • 10. Conclusion
    • 1001 Wrap Up

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