Explore large-scale graph analysis using Scala and Akka in this 33-minute conference talk from Scala Days New York 2016. Delve into the architecture and implementation of a graph analysis engine that leverages Scala, Akka, and HBase. Learn about the motivations behind this type of processing, implementation considerations, and the creation of a query parser and Akka cluster for processing. Discover how to produce stream output of results and gain insights into Scala, Akka, Big Data, stream processing, and graph analysis. Follow the journey from problem definition to optimization techniques, including consistent hashing and in-memory graphs. Understand the main components and concepts, such as node actors and the actor system/cluster, and explore future possibilities in this field.
Overview
Syllabus
Intro
THE NEED GET DATA FOR ANALYTICAL AND OPERATIONAL PURPOSE
THE NEED DET DATA FOR ANALYTICAL AND OPERATIONAL PURPOS
THE PROBLEM
LIKE A DATABASE BUT A BIT MORE...
WHY A GRAPH
PATTERN MATCHING GRAPH QUERY
DATA MODEL IN HBASE
MAIN COMPONENTS/CONCEPTS
NODE ACTOR
OPTIMIZATIONS
CONSISTENT HASHING/IN-MEMORY GRAPH
ACTOR NODE
END TO END
WHEN DOES IT END?
WHAT NEXT
WE ARE HIRING
WHY NOT [X] YOU SHOULD HAVE USED
ACTOR SYSTEM/CLUSTER
Taught by
Scala Days Conferences
