GAIA: A System for Interactive Analysis on Distributed Graphs Using a High-Level Language
Zhengping Qian, Chenqiang Min, Longbin Lai, Yong Fang, Gaofeng Li, Youyang Yao, Bingqing Lyu, Xiaoli Zhou, Zhimin Chen, Jingren Zhou
摘要
GAIA (GrAph Interactive Analysis) is a distributed system designed specifically to make it easy for a variety of users to interactively analyze big graph data on large clusters at low latency. It adopts a high-level language called Gremlin for graph traversal, and provides automatic parallel execution. In particular, we advocate a powerful new abstraction called Scope that caters to the specific needs in this new computation model to scale graph queries with complex dependencies and runtime dynamics, while at the same time maintaining the simple and concise programming model. GAIA has been deployed in production clusters at Alibaba to support a variety of business-critical scenarios. Extensive evaluations using both benchmarks and real-world applications have validated the effectiveness of the proposed techniques, which enables GAIA to execute complex Gremlin traversal with orders-ofmagnitude better performance than existing high-performance engines, and at much larger scales than recent state-of-the-art Gremlin-enabled systems such as JanusGraph.
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