NitroFlare Udemy - Hadoop In Real World Become an Expert Hadoop Developer

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  1. kocogi

    kocogi Active Member

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    Udemy - Hadoop In Real World: Become an Expert Hadoop Developer
    WEBRip | MP4/AVC, ~145 kb/s | 1280 x 720 | English: AAC, 58.7 kb/s (2 ch), 48.0 KHz | 1.49 GB
    Genre: IT & Software | Language: English | +Project Files

    "Learn all the must know concepts to survive as a Hadoop developer in REAL WORLD Hadoop environments (hands-on + bonuses) From the creators of the successful Hadoop Starter Kit course hosted in Udemy, comes Hadoop In Real World course. This course is designed for anyone who aspire a career as a Hadoop developer. In this course we have covered all the concepts that every aspiring Hadoop developer must know to SURVIVE in REAL WORLD Hadoop environments."



    The course covers all the must know topics like HDFS, MapReduce, YARN, Apache Pig and Hive etc. and we go deep in exploring the concepts. We just don't stop with the easy concepts, we take it a step further and cover important and complex topics like file formats, custom Writables, input/output formats, troubleshooting, optimizations etc.
    All concepts are backed by interesting hands-on projects like analyzing million song dataset to find less familiar artists with hot songs, ranking pages with page dumps from wikipedia, simulating mutual friends functionality in Facebook just to name a few.

    What are the requirements?

    Although you don't have to be an expert in Java, basic knowledge in Java programming is required as we will be looking at programs in Java.
    Basic Linux commands

    What am I going to get from this course?

    Over 65 lectures and 13 hours of content!
    Understand what is Big Data, the challenges with Big Data and how Hadoop propose a solution for the Big Data problem
    Work and navigate Hadoop cluster with ease
    Install and configure a Hadoop cluster on cloud services like Amazon Web Services (AWS)
    Understand the difference phases of MapReduce in detail
    Write optimized Pig Latin instruction to perform complex data analysis
    Write optimized Hive queries to perform data analysis on simple and nested datasets
    Work with file formats like SequenceFile, AVRO etc
    Understand Hadoop architecture, Single Point Of Failures (SPOF), Secondary/Checkpoint/Backup nodes, HA configuration and YARN
    Tune and optimize slowing running MapReduce jobs, Pig instructions and Hive queries
    Understand how Joins work behind the scenes and will be able to write optimized join statements
    Wherever possible, students will be introduced to difficult questions that are asked in real Hadoop interviews

    What is the target audience?

    This course is for anyone who aspire a career as a Hadoop Developer
    This course is for anyone who want to learn and understand in depth about Hadoop and Big Data

    Curriculum
    Section 1: Thank You and Let's Get Started
    Lecture 1 Course Structure 11:03
    Lecture 2 Tools & Setup (Windows) 09:09
    Lecture 3 Tools & Setup (Linux) 07:42
    Section 2: Introduction To Big Data
    Lecture 4 What is Big Data? 17:47
    Lecture 5 Understanding Big Data Problem 14:24
    Lecture 6 History of Hadoop 03:46
    Quiz 1 Test your understanding of HDFS 6 questions
    Section 3: HDFS
    Lecture 7 HDFS - Why Another Filesystem? 13:20
    Lecture 8 Blocks 07:50
    Lecture 9 Working With HDFS 16:09
    Lecture 10 HDFS - Read & Write 09:31
    Lecture 11 HDFS - Read & Write (Program) 08:38
    Quiz 2 Test your understanding of HDFS 5 questions
    Lecture 12 HDFS Assignment Text
    Section 4: MapReduce
    Lecture 13 Introduction to MapReduce 08:51
    Lecture 14 Dissecting MapReduce Components 18:03
    Lecture 15 Dissecting MapReduce Program (Part 1) 12:00
    Lecture 16 Dissecting MapReduce Program (Part 2) 16:09
    Lecture 17 Combiner 06:20
    Lecture 18 Counters 06:43
    Lecture 19 Facebook - Mutual Friends 17:38
    Lecture 20 New York Times - Time Machine 15:43
    Quiz 3 Test your understanding of MapReduce 12 questions
    Lecture 21 MapReduce Assignment Text
    Section 5: Apache Pig
    Lecture 22 Introduction to Apache Pig 12:52
    Lecture 23 Loading & Projecting Datasets 13:41
    Lecture 24 Solving a Problem 13:32
    Lecture 25 Complex Types 21:12
    Lecture 26 Pig Latin - Joins 19:53
    Lecture 27 Million Song Dataset (Part 1) 10:29
    Lecture 28 Million Song Dataset (Part 2) 15:01
    Lecture 29 Page Ranking (Part 1) 08:11
    Lecture 30 Page Ranking (Part 2) 19:26
    Lecture 31 Page Ranking (Part 3) 12:17
    Quiz 4 Test your understanding of Apache Pig 13 questions
    Lecture 32 Apache Pig Assignment Text
    Section 6: Apache Hive
    Lecture 33 Introduction to Apache Hive 09:58
    Lecture 34 Dissect a Hive Table 10:14
    Lecture 35 Loading Hive Tables 11:17
    Lecture 36 Simple Selects 06:07
    Lecture 37 Managed Table vs. External Table 06:20
    Lecture 38 Order By vs. Sort By vs. Cluster By 09:44
    Lecture 39 Partitions 19:31
    Lecture 40 Buckets 07:27
    Lecture 41 Hive QL - Joins 09:21
    Lecture 42 Twitter (Part 1) 09:33
    Lecture 43 Twitter (Part 2) 08:43
    Quiz 5 Test your understanding of Apache Hive 18 questions
    Lecture 44 Apache Hive Assignment Text
    Section 7: Architechture
    Lecture 45 HDFS Architechture 12:46
    Lecture 46 Secondary Namenode 11:24
    Lecture 47 Highly Available Hadoop 08:48
    Lecture 48 MRv1 Architechture 10:49
    Lecture 49 YARN 11:22
    Quiz 6 Test your understanding of Hadoop Architechture 10 questions
    Section 8: Cluster Setup
    Lecture 50 Vendors & Hosting 06:35
    Lecture 51 Cluster Setup (Part 1) 23:43
    Lecture 52 Cluster Setup (Part 2) 25:35
    Lecture 53 Cluster Setup (Part 3) 18:01
    Quiz 7 Test your understanding of Cluster Setup 7 questions
    Section 9: File Formats
    Lecture 54 Compression 14:55
    Lecture 55 Sequence File 18:32
    Lecture 56 AVRO 19:08
    Lecture 57 File Formats - Pig 18:08
    Lecture 58 File Formats - Hive 11:03
    Quiz 8 Test your understanding of File Formats 10 questions
    Section 10: Troubleshooting and Optimizations
    Lecture 59 Exploring Logs 08:49
    Lecture 60 MRUnit 09:31
    Lecture 61 MapReduce Tuning 12:39
    Lecture 62 Pig Join Optimizations (Part 1) 17:17
    Lecture 63 Pig Join Optimizations (Part 2) 13:56
    Lecture 64 Hive Join Optimizations 19:36
    Quiz 9 Test your understanding of Troubleshooting & Optimizations 15 questions
    Section 11: Bonus
    Lecture 65 Preparing For Hadoop Interviews 19:18
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