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.

中文翻译：

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A+ 索引：图数据库管理系统中的可调且节省空间的邻接列表

图数据库管理系统 (GDBMS) 被高度优化以执行快速遍历，即通过索引邻接列表中顶点的邻域，将顶点与其邻域连接起来。然而，现有的 GDBMS 具有特定于系统的固定邻接列表结构，这使得每个系统仅在一组固定的工作负载上高效。我们为 GDBMS 描述了一个新的可调索引子系统，我们称之为 A+ 索引，具有物化视图支持。该子系统由两种类型的索引组成： (i) 顶点分区索引，将 1 跳物化视图划分为源或目标顶点 ID 上的邻接列表；(ii) 边缘分区索引，将 2 跳视图分区为边缘 ID 之一上的邻接列表。与现有的 GDBMS 一样，默认情况下，系统需要一个前向和一个后向顶点分区索引，我们称之为主 A+ 索引。用户可以通过添加嵌套的分区和排序标准来调整主索引或二级索引。我们的二级索引节省空间，并使用一种我们称为偏移列表的技术。我们的索引子系统允许更广泛的应用程序受益于 GDBMS 的快速连接功能。我们通过对三个工作负载的大量实验证明了 A+ 索引的可调性和空间效率。快速加入功能。我们通过对三个工作负载的大量实验证明了 A+ 索引的可调性和空间效率。快速加入功能。我们通过对三个工作负载的大量实验证明了 A+ 索引的可调性和空间效率。