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コース概要
Introduction
- Graph databases and libraries
Understanding Graph Data
- The graph as a data structure
- Using vertices (dots) and edges (lines) to model real-world scenarios
Using Graph Databases to Model, Persist and Process Graph Data
- Local graph algorithms/traversals
- neo4j, OrientDB and Titan
Exercise: Modeling Graph Data with neo4j
- Whiteboard data modeling
Beyond Graph Databases: Graph Computing
- Understanding the property graph
- Graph modeling different scenarios (software graph, discussion graph, concept graph)
Solving Real-World Problems with Traversals
- Algorithmic/directed walk over the graph
- Determining circular cependencies
Case Study: Ranking Discussion Contributors
- Ranking by number and depth of contributed discussions
- A note on sentiment and concept analysis
Graph Computing: Local, In-Memory Graph toolkits
- Graph analysis and visualization
- JUNG, NetworkX, and iGraph
Exercise: Modeling Graph Data with NetworkX
- Using NetworkX to model a complex system
Graph Computing: Batch Processing Graph Frameworks
- Leveraging Hadoop for storage (HDFS) and processing (MapReduce)
- Overview of iterative algorithms
- Hama, Giraph, and GraphLab
Graph Computing: Graph-Parallel Computation
- Unifying ETL, exploratory analysis, and iterative graph computation within a single system
- GraphX
Setup and Installation
- Hadoop and Spark
GraphX Operators
- Property, structural, join, neighborhood aggregation, caching and uncaching
Iterating with Pregel API
- Passing arguments for sending, receiving and computing
Building a Graph
- Using vertices and edges in an RDD or on disk
Designing Scalable Algorithms
- GraphX Optimization
Accessing Additional Algorithms
- PageRank, Connected Components, Triangle Counting
Exercis: Page Rank and Top Users
- Building and processing graph data using text files as input
Deploying to Production
Closing Remarks
要求
- An undersanding of Java programming and frameworks
- A general understanding of Python is helpful but not required
- A general understanding of database concepts
Audience
- Developers
28 時間
お客様の声 (2)
Broad coverage and deep knowledge about Semantic Web
XINJIAN GUO - Yale University
コース - Semantic Web Overview
Very nice training
