Video description
There are a variety of useful applications for real-time data, including quick identification of general patterns and trends in data, performing sentiment analysis, crafting responses in real-time, and—perhaps one of the most important uses—when having analysis immediately will change the outcome of the situation. This Learning Path provides an in-depth tour of technologies used in processing and analyzing real-time data.
Publisher resources
Table of contents
-
Introduction To Cassandra
- Introducing The Course 00:04:41
- Understanding What Cassandra Is 00:04:58
- Learning What Cassandra Is Being Used For 00:04:56
- Understanding The System Requirements 00:06:54
- Opening The Main Virtual Machine 00:02:53
- Pop Quiz - Intro to Cassandra 00:01:24
-
Getting Started With The Architecture
- Understanding That Cassandra Is A Distributed Database 00:02:23
- Learning What Snitch Is For 00:03:53
- Learning What Gossip Is For 00:01:52
- Learning How Data Gets Distributed 00:05:35
- Learning About Replication 00:02:12
- Learning About Virtual Nodes 00:03:01
- Pop Quiz - Getting Started with Architecture 00:01:25
-
Installing Cassandra
- Downloading Cassandra 00:02:48
- Ensuring Oracle Java 7 Is Installed 00:02:02
- Installing Cassandra 00:03:44
- Viewing The Main Configuration File 00:02:46
- Providing Cassandra With Permission To Directories 00:01:46
- Starting Cassandra 00:03:41
- Checking Status 00:04:00
- Accessing The Cassandra system.log File 00:02:06
- Pop Quiz - Installing Cassandra 00:01:28
-
Communicating With Cassandra
- Understanding Ways To Communicate With Cassandra 00:03:47
- Using CQLSH 00:02:29
- Pop Quiz - Communicating with Cassandra 00:01:08
-
Creating A Database
- Understanding A Cassandra Database 00:01:54
- Defining A Keyspace 00:04:57
- Deleting A Keyspace 00:00:52
- Pop Quiz - Creating a Database 00:01:53
- Lab: Create A Second Database 00:02:39
-
Creating A Table
- Creating A Table 00:01:49
- Defining Columns And Data Types 00:02:48
- Defining A Primary Key 00:01:49
- Recognizing A Partition Key 00:02:44
- Specifying A Descending Clustering Order 00:03:02
- Pop Quiz - Creating a Table 00:01:54
- Lab: Create A Second Table 00:02:33
-
Inserting Data
- Understanding Ways To Write Data 00:01:28
- Using The INSERT INTO Command 00:04:45
- Using The COPY Command 00:05:53
- How Data Is Stored In Cassandra 00:04:21
- How Data Is Stored On Disk 00:05:29
- Pop Quiz - Inserting Data 00:02:15
- Lab: Insert Data 00:09:10
-
Modeling Data
- Understanding Data Modeling In Cassandra 00:01:21
- Using A WHERE Clause 00:04:17
- Understanding Secondary Indexes 00:02:18
- Creating A Secondary Index 00:01:38
- Defining A Composite Partition Key 00:09:34
- Pop Quiz - Modeling Data 00:03:34
-
Creating An Application
- Understanding Cassandra Drivers 00:02:31
- Exploring The DataStax Java Driver 00:03:14
- Setting Up A Development Environment 00:04:04
- Creating An Application Page 00:04:51
- Acquiring The DataStax Java Driver Files 00:03:24
- Getting The DataStax Java Driver Files Through Maven 00:02:23
- Providing The DataStax Java Driver Files Manually 00:02:36
- Connecting To A Cassandra Cluster 00:03:39
- Executing A Query 00:07:47
- Displaying Query Results - Part 1 00:05:59
- Displaying Query Results - Part 2 00:07:20
- Using An MVC Pattern 00:04:59
- Pop Quiz - Creating an Application 00:02:50
- Lab: Create A Second Application - Part 1 00:05:20
- Lab: Create A Second Application - Part 2 00:09:49
- Lab: Create A Second Application - Part 3 00:03:08
-
Updating And Deleting Data
- Updating Data 00:03:39
- Understanding How Updating Works 00:03:55
- Deleting Data 00:07:10
- Understanding Tombstones 00:07:18
- Using TTLs 00:05:09
- Updating A TTL 00:02:38
- Pop Quiz - Updating and Deleting Data 00:02:38
- Lab: Update And Delete Data 00:07:00
-
Selecting Hardware
- Understanding Hardware Choices 00:00:30
- Understanding RAM And CPU Recommendations 00:02:45
- Selecting Storage 00:04:08
- Deploying In The Cloud 00:04:07
- Pop Quiz - Selecting Hardware 00:02:06
-
Adding Nodes To A Cluster
- Understanding Cassandra Nodes 00:03:39
- Having A Network Connection - Part 1 00:05:35
- Having A Network Connection - Part 2 00:05:02
- Having A Network Connection - Part 3 00:04:46
- Specifying The IP Address Of A Node In Cassandra 00:04:12
- Specifying Seed Nodes 00:06:30
- Bootstrapping A Node 00:06:18
- Cleaning Up A Node 00:02:59
- Using cassandra-stress 00:10:33
- Pop Quiz - Adding Nodes to a Cluster 00:01:39
- Lab: Add A Third Node 00:10:42
-
Monitoring A Cluster
- Understanding Cassandra Monitoring Tools 00:00:46
- Using Nodetool 00:04:54
- Using JConsole 00:03:24
- Learning About OpsCenter 00:03:24
- Pop Quiz - Monitoring a Cluster 00:01:49
-
Repairing Nodes
- Understanding Repair 00:05:17
- Repairing Nodes 00:04:17
- Understanding Consistency - Part 1 00:06:26
- Understanding Consistency - Part 2 00:04:33
- Understanding Hinted Handoff 00:03:30
- Understanding Read Repair 00:01:58
- Pop Quiz - Repairing Nodes 00:03:30
- Lab: Repair Nodes For A Keyspace 00:05:45
-
Removing A Node
- Understanding Removing A Node 00:00:54
- Decommissioning A Node 00:04:36
- Putting A Node Back Into Service 00:06:38
- Removing A Dead Node 00:06:42
- Pop Quiz - Removing a Node 00:04:10
- Lab: Put A Node Back Into Service 00:05:00
-
Redefining A Cluster For Multiple Data Centers
- Redefining For Multiple Data Centers - Part 1 00:04:50
- Redefining For Multiple Data Centers - Part 2 00:05:59
- Changing Snitch Type 00:05:25
- Modifying cassandra-rackdc.properties 00:07:45
- Changing Replication Strategy - Part 1 00:05:55
- Changing Replication Strategy - Part 2 00:03:58
- Pop Quiz - Redefining a Cluster 00:02:30
-
Resources For FurTher Learning
- Accessing Documentation 00:02:51
- Reading Blogs And Books 00:04:53
- Watching Video Recordings 00:04:05
- Posting Questions 00:04:10
- Attending Events 00:03:00
- Wrap Up 00:01:03
- The Case for Kafka 00:11:23
- The Basics 00:09:10
- Setting up a Kafka Cluster 00:15:30
- Writing a Kafka Producer 00:14:33
- Writing a Kafka Consumer 00:16:34
- Using Kafka from Python 00:08:03
- Troubleshooting Kafka 00:29:29
- Integrating Kafka and Hadoop with Flafka 00:26:06
- Kafka Availability and Consistency 00:22:38
- Kafka Ecosystem 00:13:13
- Future of Kafka 00:08:53
- Pre-Flight Check 00:13:08
- Spark Deconstructed 00:14:31
- A Brief History 00:23:28
- Simple Spark Apps 00:25:07
- Spark Essentials 00:35:18
- Spark Examples 00:21:55
- Unifying the Pieces - Spark SQL 00:24:07
- Unifying the Pieces - Spark Streaming 00:14:48
- Unifying the Pieces - MLlib and GraphX 00:20:00
- Unified Workflows Demo 00:22:35
- The Full SDLC 00:04:01
- Developer Certification 00:06:10
- Resources 00:04:44
- Introduction - Why DataFrames? 00:02:28
- ETL to Prepare the Data from Capital Bikeshare 00:02:46
- Create a DataFrame, Explore using SQL 00:02:47
- Data Preparation for Machine Learning Models 00:05:33
- Build a Classifier Using Naive Bayes 00:04:43
- Build a Classifier Using Decision Trees 00:02:26
- Build a Classifier Using Random Forests 00:02:20
- Use a DataFrame to Compare Models 00:04:15
- Parquet as a Best Practice with DataFrames 00:00:58
- How to Store a DataFrame with Parquet 00:03:25
- How to Read a DataFrame Back in From Parquet 00:02:57
- Use SQL to Estimate Route Durations 00:01:41
- Data Preparation for GraphX - Model Route Costs 00:04:43
- Use PageRank to Rank Popular Stations 00:03:14
- Optimize Routes to Columbus Circle 00:03:43
- Compare Results with Google Maps 00:01:58
- Analyze a Popular Tourist Route 00:02:30
- Examples of How to Use DataFrames in Python 00:02:57
- Summary - The New DataFrames Features in Spark 00:01:03
- Introduction - Large-scale real time stream processing and analytics at Strata+Hadoop World - Ben Lorica 00:01:08
- Going Real-time: Data Collection and Stream Processing with Apache Kafka - Jay Kreps 00:39:29
- Say goodbye to batch - Tyler Akidau (Google) 00:42:35
- Stream Processing Everywhere - What to Use? - Jim Scott 00:39:06
- From Source to Solution: Building A System for Machine and Event-Oriented Data - Eric Sammer 00:41:59
- Spark Streaming - The State of the Union, and Beyond - Tathagata Das 00:36:46
- Dynamic Events in Massive Data Streams, from Astrophysics to Marketing Automation - Kirk Borne 00:40:06
- TSAR (the TimeSeries AggregatoR) - How to Count Tens of Billions of Daily Events in Real Time Using Open Source Technologies - Anirudh Todi 00:41:28
- Streaming Analytics: It’s Not The Same Game - Subutai Ahmad 00:38:46
- Realtime Data Analysis Patterns - Mikio Braun (streamdrill) 00:39:24
- The IoT P2P Backbone - Bruno Fernandez-Ruiz 00:27:05
- Practical Methods for Identifying Anomalies That Matter in Large Datasets - Robert Grossman 00:36:43
-
Introduction
- Introduction to Time Series Problems 00:09:58
-
Kafka
- Kafka Architecture and Deployment 00:11:33
- Kafka Usage 00:03:42
-
Spark
- Introduction to Spark 00:15:43
- Spark Architecture 00:12:02
- Spark Streaming
-
Cassandra
- Introduction to Cassandra 00:08:56
- Cassandra Basic Architecture 00:11:59
- Replication, High Availability and Multi Datacenter 00:14:06
- Cassandra Weather Website Example 00:11:46
- Cassandra Query Language (CQL) 00:18:00
- Cassandra Partitions & Clustering 00:08:22
- Cassandra Read and Write Path 00:12:17
- Working with Cassandra 00:06:32
- Cassandra Drivers and Access Patterns 00:10:37
-
Spark and Cassandra
- Spark and Cassandra Architecture 00:12:00
- Analyzing Cassandra Data & Spark SQL 00:12:12
- Spark and Cassandra DataStax Enterprise 00:04:31
- Real World Use Cases
Product information
- Title: Learning Path: Real-Time Data Applications
- Author(s):
- Release date: November 2015
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491952610
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