Many applications require sorting a table over multiple sort orders: generation of multiple reports from a table, evaluation of a complex query that involves multiple instances of a relation, and batch processing of a set of queries. In this paper, we study how multiple sortings of a table can be efficiently performed. We introduce a new evaluation technique, called cooperative sort, that exploits the relationships among the input set of sort orders to minimize I/O operations for the collection of sort operations. To demonstrate the efficiency of the proposed scheme, we implemented it in PostgreSQL and evaluated its performance using both TPC-DS benchmark and synthetic data. Our experimental results show significant performance improvement over the traditional non-cooperative sorting scheme.

Recent interests on XML, the Semantic Web, and Web ontology, among other topics, have sparked a renewed interest on graph-structured databases. A fundamental query on graphs is the reachability test of nodes. Recently, 2-hop labeling has been proposed to index a large collection of XML and/or graphs for efficient reachability tests. However, there has been few work on updates of 2-hop labeling. This is compounded by the fact that data may often change over time. In response to these, this paper studies incremental maintenance of 2-hop labeling. We identify the main reason for the inefficiency of updates of existing 2-hop labels. We propose three updatable 2-hop labelings, hybrids of 2-hop labeling, and their incremental maintenance algorithms. The proposed 2-hop labeling is derived from graph connectivity, as opposed to set cover which is used by most previous works. Our experimental evaluation illustrates the space efficiency and update performance of various kinds of 2-hop labelings. Our results show that our incremental maintenance algorithm can be two orders of magnitude faster than previous methods and the size of our 2-hop labeling can be comparable to existing 2-hop labeling. We conclude that there is a natural way to spare some index size for update performance in 2-hop labeling.

Recent interests on XML, Semantic Web, and Web ontology, among other topics, have sparked a renewed interest on graph-structured databases. A fundamental query on graphs is the reachability test of nodes. Recently, 2-hop labeling has been proposed to index large collections of XML and/or graphs for efficient reachability tests. However, there has been few work on updates of 2-hop labeling. This is compounded by the fact that Web data changes over time. In response to these, this paper studies the incremental maintenance of 2-hop labeling. We identify the main reason for the inefficiency of updates of existing 2-hop labels. We propose two updatable 2-hop labelings, hybrids of 2-hop labeling, and their incremental maintenance algorithms. The proposed 2-hop labeling is derived from graph connectivities, as opposed to set cover which is used by all previous work. Our experimental evaluation illustrates the space efficiency and update performance of various kinds of 2-hop labeling. The main conclusion is that there is a natural way to spare some index size for update performance in 2-hop labeling.