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MapReduce
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Classroom Contents
Harnessing the Power of Spark & Cassandra within Your Spring App
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- 1 Introduction
- 2 Relational Databases
- 3 Sharding
- 4 Who this talk is for
- 5 Big Data
- 6 Agenda
- 7 Spark
- 8 Gray Sort
- 9 Spark vs Hadoop
- 10 Spark history
- 11 MOSS
- 12 Spark Context
- 13 Working with Spark
- 14 RDD Example
- 15 MapReduce
- 16 Demo Code
- 17 Spark Modules
- 18 Spark Sequel
- 19 Spark DataFrame
- 20 Spark Streaming
- 21 Spark Window Functions
- 22 Cassandra
- 23 Token Rings
- 24 quorum
- 25 Replication across data centers
- 26 Why use Cassandra
- 27 What happens if a node goes down
- 28 Linear scalability
- 29 Performance
- 30 What is Cassandra
- 31 Tables
- 32 Terminus
- 33 Query
- 34 Data Model
- 35 Partition Keys
- 36 Clustered Rows
- 37 Spark vs Cassandra
- 38 Weaknesses
- 39 Companies
- 40 Spark Cassandra Connector
- 41 Spark Cassandra Smart Algorithms
- 42 Spark Cassandra Cluster Design
- 43 Why Spark Cassandra
- 44 Spark Cassandra Example
- 45 How many nodes should you use
- 46 Common data pipeline patterns
- 47 Spring Cloud Dataflow
- 48 Programming Model
- 49 Code
- 50 Spark Configuration
- 51 Resource Management
- 52 Java Functions
- 53 Warning
- 54 Managing Cassandra
- 55 Pricing
- 56 Understanding where your code lives
- 57 Mapping into classes
- 58 Mapping into local packages
- 59 Spring app demo
- 60 Spark master URL
- 61 Commandline tool
- 62 Demo web
- 63 Demo client app
- 64 Demo client project
- 65 Thank you
