{aDFS}: An Almost {Depth-First-Search} Distributed {Graph-Querying} System
2021 USENIX Annual Technical Conference (USENIX ATC 21), 2021•usenix.org
Graph processing is an invaluable tool for data analytics. In particular, pattern-matching
queries enable flexible graph exploration and analysis, similar to what SQL provides for
relational databases. Graph queries focus on following connections in the data; they are a
challenging workload because even seemingly trivial queries can easily produce billions of
intermediate results and irregular data access patterns.
queries enable flexible graph exploration and analysis, similar to what SQL provides for
relational databases. Graph queries focus on following connections in the data; they are a
challenging workload because even seemingly trivial queries can easily produce billions of
intermediate results and irregular data access patterns.
Abstract
Graph processing is an invaluable tool for data analytics. In particular, pattern-matching queries enable flexible graph exploration and analysis, similar to what SQL provides for relational databases. Graph queries focus on following connections in the data; they are a challenging workload because even seemingly trivial queries can easily produce billions of intermediate results and irregular data access patterns.
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