A+ 索引：图数据库管理系统中可调优且空间高效的邻接表
A+ Indexes: Tunable and Space-Efficient Adjacency Lists in Graph Database Management Systems
AI总结：
针对现有图数据库管理系统固定邻接表结构仅适配特定工作负载的问题，提出支持物化视图的可调优A+索引子系统，含顶点/边分区两类索引，采用偏移列表实现二级索引空间高效，经三类工作负载实验验证了可调优性与空间效率。
摘要：
图数据库管理系统（GDBMS）通过在邻接表中为顶点邻域建立索引，针对快速遍历（即顶点与其邻居的连接操作）进行了高度优化。然而，现有GDBMS的邻接表结构是特定于系统且固定的，这导致每个系统仅在固定的工作负载集合上具备高效性。我们提出了一种适用于GDBMS的新型可调优索引子系统，命名为A+索引，该子系统支持物化视图。子系统包含两类索引：（i）顶点分区索引，将1跳物化视图按源顶点ID或目的顶点ID划分为邻接表；（ii）边分区索引，将2跳视图按其中一个边ID划分为邻接表。与现有GDBMS一致，系统默认需要一个正向和一个反向顶点分区索引，我们将其称为主A+索引。用户可通过添加嵌套分区与排序准则来调优主索引或二级索引。我们的二级索引空间效率高，采用了一种我们称为偏移列表的技术。该索引子系统能让更广泛的应用受益于GDBMS的快速连接能力。我们通过在三种工作负载上开展的大量实验，验证了A+索引的可调优性与空间效率。
英文摘要：
Graph database management systems (GDBMSs) are highly optimized to perform fast traversals, i.e., joins of vertices with their neighbours, by indexing the neighbourhoods of vertices in adjacency lists. However, existing GDBMSs have system-specific and fixed adjacency list structures, which makes each system efficient on only a fixed set of workloads. We describe a new tunable indexing subsystem for GDBMSs, we call A+ indexes, with materialized view support. The subsystem consists of two types of indexes: (i) vertex-partitioned indexes that partition 1-hop materialized views into adjacency lists on either the source or destination vertex IDs; and (ii) edge-partitioned indexes that partition 2-hop views into adjacency lists on one of the edge IDs. As in existing GDBMSs, a system by default requires one forward and one backward vertex-partitioned index, which we call the primary A+ index. Users can tune the primary index or secondary indexes by adding nested partitioning and sorting criteria. Our secondary indexes are space-efficient and use a technique we call offset lists. Our indexing subsystem allows a wider range of applications to benefit from GDBMSs' fast join capabilities. We demonstrate the tunability and space efficiency of A+ indexes through extensive experiments on three workloads.
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