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004 What is Big Data

004 What is Big Data

002 Tools & Setup Windows

002 Tools & Setup Windows

028 Million Song Dataset Part 2

028 Million Song Dataset Part 2

013 Introduction to MapReduce

013 Introduction to MapReduce

031 Page Ranking Part 3

031 Page Ranking Part 3

017 Combiner

017 Combiner

009 Working With HDFS

009 Working With HDFS

025 Complex Types

025 Complex Types

023 Loading & Projecting Datasets

023 Loading & Projecting Datasets

027 Million Song Dataset Part 1

027 Million Song Dataset Part 1

026 Pig Latin Joins

026 Pig Latin Joins

001 Course Structure

001 Course Structure

003 Tools & Setup Linux

003 Tools & Setup Linux

014 Dissecting MapReduce Components

014 Dissecting MapReduce Components

022 Introduction to Apache Pig

022 Introduction to Apache Pig

015 Dissecting MapReduce Program Part 1

015 Dissecting MapReduce Program Part 1

008 Blocks

008 Blocks

010 HDFS Read & Write

010 HDFS Read & Write

006 History of Hadoop

006 History of Hadoop

018 Counters

018 Counters

011 HDFS Read & Write Program

011 HDFS Read & Write Program

007 HDFS Why Another Filesystem

007 HDFS Why Another Filesystem

005 Understanding Big Data Problem

005 Understanding Big Data Problem

019 Facebook Mutual Friends

019 Facebook Mutual Friends

020 New York Times Time Machine

020 New York Times Time Machine

024 Solving a Problem

024 Solving a Problem

030 Page Ranking Part 2

030 Page Ranking Part 2

029 Page Ranking Part 1

029 Page Ranking Part 1

040 Buckets

040 Buckets

054 Amazon EMR

054 Amazon EMR

050 Vendors & Hosting

050 Vendors & Hosting

036 Simple Selects

036 Simple Selects

048 MRv1 Architechture

048 MRv1 Architechture

053 Cluster Setup Part 3

053 Cluster Setup Part 3

059 AVRO

059 AVRO

049 YARN

049 YARN

057 Compression

057 Compression

052 Cluster Setup Part 2

052 Cluster Setup Part 2

063 Working with RCFile

063 Working with RCFile

055 Cloudera Manager Introduction

055 Cloudera Manager Introduction

058 Sequence File

058 Sequence File

060 File Formats Pig

060 File Formats Pig

034 Dissect a Hive Table

034 Dissect a Hive Table

061 File Formats Hive

061 File Formats Hive

043 Twitter Part 2

043 Twitter Part 2

038 Order By vs Sort By vs Cluster By

038 Order By vs Sort By vs Cluster By

039 Partitions

039 Partitions

035 Loading Hive Tables

035 Loading Hive Tables

037 Managed Table vs External Table

037 Managed Table vs External Table

046 Secondary Namenode

046 Secondary Namenode

064 Introduction to ORC

064 Introduction to ORC

041 Hive QL Joins

041 Hive QL Joins

056 Cloudera Manager Installation

056 Cloudera Manager Installation

051 Cluster Setup Part 1

051 Cluster Setup Part 1

062 Introduction to RCFile

062 Introduction to RCFile

045 HDFS Architechture

045 HDFS Architechture

042 Twitter Part 1

042 Twitter Part 1

033 Introduction to Apache Hive

033 Introduction to Apache Hive

089 Preparing For Hadoop Interviews

089 Preparing For Hadoop Interviews

068 MRUnit

068 MRUnit

084 Tolerating Failures Brokers

084 Tolerating Failures Brokers

079 Consolidation & Mutliplexing

079 Consolidation & Mutliplexing

067 Exploring Logs

067 Exploring Logs

074 Sqoop File Formats

074 Sqoop File Formats

075 Jobs & Incremental Imports

075 Jobs & Incremental Imports

077 Introduction to Flume

077 Introduction to Flume

069 MapReduce Tuning

069 MapReduce Tuning

082 Kafka Concepts

082 Kafka Concepts

081 Kafka The Why & the What

081 Kafka The Why & the What

086 Experiments with Kafka

086 Experiments with Kafka

087 Streaming Meetup with Kafka Part 1

087 Streaming Meetup with Kafka Part 1

066 Parquet Another Columnar Format

066 Parquet Another Columnar Format

088 Streaming Meetup with Kafka Part 2

088 Streaming Meetup with Kafka Part 2

085 Kafka Installation

085 Kafka Installation

072 Hive Join Optimizations

072 Hive Join Optimizations

071 Pig Join Optimizations Part 2

071 Pig Join Optimizations Part 2

076 Hive Exports

076 Hive Exports

080 Streaming Twitter with Flume

080 Streaming Twitter with Flume

070 Pig Join Optimizations Part 1

070 Pig Join Optimizations Part 1

073 Sqoop Imports

073 Sqoop Imports

065 Working with ORC

065 Working with ORC

083 Tolerating Failures Producers & Consumers

083 Tolerating Failures Producers & Consumers

078 Replication

078 Replication

005 HDFS What it is and how it works

005 HDFS What it is and how it works

002 Hadoop Overview and History

002 Hadoop Overview and History

004 Tips for Using This Course

004 Tips for Using This Course

001 Activity Introduction and install Hadoop on your desktop

001 Activity Introduction and install Hadoop on your desktop

003 Overview of the Hadoop Ecosystem

003 Overview of the Hadoop Ecosystem

025 Datasets and Spark 2 0

025 Datasets and Spark 2 0

009 How MapReduce distributes processing

009 How MapReduce distributes processing

014 Activity Check your results against mine

014 Activity Check your results against mine

010 MapReduce example Break down movie ratings by rating score

010 MapReduce example Break down movie ratings by rating score

012 Activity Code up the ratings histogram MapReduce job and run it

012 Activity Code up the ratings histogram MapReduce job and run it

011 Activity Installing Python MRJob and nano

011 Activity Installing Python MRJob and nano

033 Exercise Use Hive to find the movie with the highest average rating

033 Exercise Use Hive to find the movie with the highest average rating

035 Integrating MySQL with Hadoop

035 Integrating MySQL with Hadoop

023 The Resilient Distributed Dataset RDD

023 The Resilient Distributed Dataset RDD

013 Exercise Rank movies by their popularity

013 Exercise Rank movies by their popularity

024 Activity Find the movie with the lowest average rating with RDDs

024 Activity Find the movie with the lowest average rating with RDDs

027 Activity Movie recommendations with MLLib

027 Activity Movie recommendations with MLLib

029 Activity Check your results against mine

029 Activity Check your results against mine

019 More Pig Latin

019 More Pig Latin

006 Activity Install the MovieLens dataset into HDFS using the Ambari UI

006 Activity Install the MovieLens dataset into HDFS using the Ambari UI

026 Activity Find the movie with the lowest average rating with DataFrames

026 Activity Find the movie with the lowest average rating with DataFrames

034 Compare your solution to mine

034 Compare your solution to mine

018 Activity Find old 5 star movies with Pig

018 Activity Find old 5 star movies with Pig

007 Activity Install the MovieLens dataset into HDFS using the command line

007 Activity Install the MovieLens dataset into HDFS using the command line

017 Example Find the oldest movie with a 5 star rating using Pig

017 Example Find the oldest movie with a 5 star rating using Pig

008 MapReduce What it is and how it works

008 MapReduce What it is and how it works

031 Activity Use Hive to find the most popular movie

031 Activity Use Hive to find the most popular movie

020 Exercise Find the most rated one star movie

020 Exercise Find the most rated one star movie

022 Why Spark

022 Why Spark

015 Introducing Ambari

015 Introducing Ambari

028 Exercise Filter the lowest rated movies by number of ratings

028 Exercise Filter the lowest rated movies by number of ratings

032 How Hive works

032 How Hive works

030 What is Hive

030 What is Hive

021 Pig Challenge Compare Your Results to Mine

021 Pig Challenge Compare Your Results to Mine

016 Introducing Pig

016 Introducing Pig

055 Activity Install Phoenix and query HBase with it

055 Activity Install Phoenix and query HBase with it

060 YARN explained

060 YARN explained

038 Activity Use Sqoop to export data from Hadoop to MySQL

038 Activity Use Sqoop to export data from Hadoop to MySQL

049 Choosing a database technology

049 Choosing a database technology

046 MongoDB overview

046 MongoDB overview

063 Mesos explained

063 Mesos explained

053 Activity Querying across multiple databases with Drill

053 Activity Querying across multiple databases with Drill

043 Cassandra overview

043 Cassandra overview

048 Activity Using the MongoDB shell

048 Activity Using the MongoDB shell

051 Overview of Drill

051 Overview of Drill

056 Activity Integrate Phoenix with Pig

056 Activity Integrate Phoenix with Pig

057 Overview of Presto

057 Overview of Presto

039 Why NoSQL

039 Why NoSQL

058 Activity Install Presto and query Hive with it

058 Activity Install Presto and query Hive with it

052 Activity Setting up Drill

052 Activity Setting up Drill

064 ZooKeeper explained

064 ZooKeeper explained

059 Activity Query both Cassandra and Hive using Presto

059 Activity Query both Cassandra and Hive using Presto

047 Activity Install MongoDB and integrate Spark with MongoDB

047 Activity Install MongoDB and integrate Spark with MongoDB

065 Activity Simulating a failing master with ZooKeeper

065 Activity Simulating a failing master with ZooKeeper

061 Tez explained

061 Tez explained

062 Activity Use Hive on Tez and measure the performance benefit

062 Activity Use Hive on Tez and measure the performance benefit

040 What is HBase

040 What is HBase

044 Activity Installing Cassandra

044 Activity Installing Cassandra

036 Activity Install MySQL and import our movie data

036 Activity Install MySQL and import our movie data

054 Overview of Phoenix

054 Overview of Phoenix

041 Activity Import movie ratings into HBase

041 Activity Import movie ratings into HBase

037 Activity Use Sqoop to import data from MySQL to HFDSHive

037 Activity Use Sqoop to import data from MySQL to HFDSHive

045 Activity Write Spark output into Cassandra

045 Activity Write Spark output into Cassandra

050 Exercise Choose a database for a given problem

050 Exercise Choose a database for a given problem

042 Activity Use HBase with Pig to import data at scale

042 Activity Use HBase with Pig to import data at scale

066 Oozie explained

066 Oozie explained

077 Activity Set up Flume and publish logs with it

077 Activity Set up Flume and publish logs with it

071 Hue overview

071 Hue overview

081 Exercise Monitor Flume published logs for errors in real time

081 Exercise Monitor Flume published logs for errors in real time

083 Apache Storm Introduction

083 Apache Storm Introduction

085 Flink An Overview

085 Flink An Overview

088 Review How the pieces fit together

088 Review How the pieces fit together

092 Exercise Design a system to report web sessions per day

092 Exercise Design a system to report web sessions per day

084 Activity Count words with Storm

084 Activity Count words with Storm

075 Activity Publishing web logs with Kafka

075 Activity Publishing web logs with Kafka

082 Exercise solution Aggregating HTTP access codes with Spark Streaming

082 Exercise solution Aggregating HTTP access codes with Spark Streaming

069 Activity Use Zeppelin to analyze movie ratings part 1

069 Activity Use Zeppelin to analyze movie ratings part 1

073 Kafka explained

073 Kafka explained

093 Exercise solution Design a system to count daily sessions

093 Exercise solution Design a system to count daily sessions

089 Understanding your requirements

089 Understanding your requirements

086 Activity Counting words with Flink

086 Activity Counting words with Flink

070 Activity Use Zeppelin to analyze movie ratings part 2

070 Activity Use Zeppelin to analyze movie ratings part 2

074 Activity Setting up Kafka and publishing some data

074 Activity Setting up Kafka and publishing some data

068 Zeppelin overview

068 Zeppelin overview

087 The Best of the Rest

087 The Best of the Rest

078 Activity Set up Flume to monitor a directory and store its data in HDFS

078 Activity Set up Flume to monitor a directory and store its data in HDFS

080 Activity Analyze web logs published with Flume using Spark Streaming

080 Activity Analyze web logs published with Flume using Spark Streaming

090 Sample application consume webserver logs and keep track of top sellers

090 Sample application consume webserver logs and keep track of top sellers

076 Flume explained

076 Flume explained

072 Other technologies worth mentioning

072 Other technologies worth mentioning

094 Books and online resources

094 Books and online resources

091 Sample application serving movie recommendations to a website

091 Sample application serving movie recommendations to a website

067 Activity Set up a simple Oozie workflow

067 Activity Set up a simple Oozie workflow

095 Bonus lecture Discounts on my other big data data science courses

095 Bonus lecture Discounts on my other big data data science courses

079 Spark Streaming Introduction

079 Spark Streaming Introduction