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1
Intro
2
Modern Analytics
3
Separate Systems
4
Key Question
5
Graph-Parallel Pattern
6
Graph System Optimizations
7
Representation
8
Graph Operators (Scala)
9
Join Site Selection using Routing Tables Routing Vertex
10
Additional Optimizations
11
PageRank Benchmark
12
Connected Comp. Benchmark
13
A Small Pipeline in GraphX
Description:
Explore GraphX, a graph processing framework embedded within Apache Spark, in this conference talk from OSDI '14. Dive into the advantages of using general-purpose distributed dataflow systems for graph processing, challenging the notion that specialized graph systems are necessary. Learn how GraphX implements graph-specific optimizations using basic dataflow operators and achieves performance parity with specialized systems. Discover how this approach enables low-cost fault tolerance and supports a wider range of computations. Examine real-world workload evaluations, benchmarks for PageRank and Connected Components, and a demonstration of a small pipeline in GraphX. Gain insights into modern analytics, graph-parallel patterns, representation techniques, and join site selection using routing tables.

GraphX - Graph Processing in a Distributed Dataflow Framework

USENIX
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