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Harnessing the Power of Spark & Cassandra within Your Spring App

Spring I/O via YouTube

Overview

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Explore a comprehensive conference talk from Spring I/O 2017 that delves into harnessing the power of Apache Spark and Apache Cassandra within Spring applications. Learn about the advantages of these cutting-edge data analysis tools and their integration with Spring frameworks. Discover how Spark, a cluster-computing framework, enables rapid processing of large datasets using distributed in-memory computations and functional programming. Gain insights into Cassandra, a highly scalable and fault-tolerant decentralized datastore used by major tech companies. Understand the synergy between Spark and Cassandra, and how they can be leveraged in Spring applications. Explore code examples, learn about potential pitfalls and their solutions, and see real-world applications of these technologies. The talk covers topics such as Spark's modules, Cassandra's architecture, data modeling, and integration with Spring XD and Data. Get practical advice on cluster design, resource management, and common data pipeline patterns. Witness demonstrations of Spark and Cassandra in action within a Spring application, including configuration, coding practices, and deployment considerations.

Syllabus

Introduction
Relational Databases
Sharding
Who this talk is for
Big Data
Agenda
Spark
Gray Sort
Spark vs Hadoop
Spark history
MOSS
Spark Context
Working with Spark
RDD Example
MapReduce
Demo Code
Spark Modules
Spark Sequel
Spark DataFrame
Spark Streaming
Spark Window Functions
Cassandra
Token Rings
quorum
Replication across data centers
Why use Cassandra
What happens if a node goes down
Linear scalability
Performance
What is Cassandra
Tables
Terminus
Query
Data Model
Partition Keys
Clustered Rows
Spark vs Cassandra
Weaknesses
Companies
Spark Cassandra Connector
Spark Cassandra Smart Algorithms
Spark Cassandra Cluster Design
Why Spark Cassandra
Spark Cassandra Example
How many nodes should you use
Common data pipeline patterns
Spring Cloud Dataflow
Programming Model
Code
Spark Configuration
Resource Management
Java Functions
Warning
Managing Cassandra
Pricing
Understanding where your code lives
Mapping into classes
Mapping into local packages
Spring app demo
Spark master URL
Commandline tool
Demo web
Demo client app
Demo client project
Thank you

Taught by

Spring I/O

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