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HLDB: Location-based services in databases
- In Proceedings of the 20th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems (GIS’12), 339–348. ACM Press. Best Paper Award
, 2012
"... This paper introduces HLDB, the first practical system that can answer exact spatial queries on continental road net-works entirely within a database. HLDB is based on hub la-bels (HL), the fastest point-to-point algorithm for road net-works, and its queries are implemented (quite naturally) in stan ..."
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This paper introduces HLDB, the first practical system that can answer exact spatial queries on continental road net-works entirely within a database. HLDB is based on hub la-bels (HL), the fastest point-to-point algorithm for road net-works, and its queries are implemented (quite naturally) in standard SQL. Within the database, HLDB answers exact distance queries and retrieves full shortest-path descriptions in real time, even on networks with tens of millions of ver-tices. The basic algorithm can be extended in a natural way (still in SQL) to answer much more sophisticated queries, such as finding the ten closest fast-food restaurants. We also introduce efficient new HL-based algorithms for even harder problems, such as best via point, ride sharing, and point of interest prediction. The HLDB framework makes it easy to implement these algorithms in SQL, enabling interactive applications on continental road networks.
Horton+: A Distributed System for Processing Declarative Reachability Queries over Partitioned Graphs
"... Horton+ is a graph query processing system that executes declarative reachability queries on a partitioned attributed multi-graph. It employs a query language, query optimizer, and a distributed execution engine. The query language expresses declarative reachability queries, and supports closures an ..."
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Horton+ is a graph query processing system that executes declarative reachability queries on a partitioned attributed multi-graph. It employs a query language, query optimizer, and a distributed execution engine. The query language expresses declarative reachability queries, and supports closures and predicates on node and edge attributes to match graph paths. We introduce three algebraic operators, select, traverse, and join, and a query is compiled into an execution plan containing these operators. As reachability queries access the graph elements in a random access pattern, the graph is therefore maintained in the main memory of a cluster of servers to reduce query execution time. We develop a distributed execution engine that processes a query plan in parallel on the graph servers. Since the query language is declarative, we build a query optimizer that uses graph statistics to estimate predicate selectivity. We experimentally evaluate the system performance on a cluster of 16 graph servers using synthetic graphs as well as a real graph from an application that uses reachability queries. The evaluation shows (1) the efficiency of the optimizer in reducing query execution time, (2) system scalability with the size of the graph and with the number of servers, and (3) the convenience of using declarative queries. 1.
Shortest Path Computation over Disk-resident Large Graphs based on Extended Bulk Synchronous Parallel Methods
"... Abstract. The Single Source Shortest Path (SSSP) computation over large graphs has raised significant challenges to the memory capacity and processing efficiency. Utilizing disk-based parallel iterative computing is an economic solution. However, costs of disk I/O and communication affect the perfo ..."
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Abstract. The Single Source Shortest Path (SSSP) computation over large graphs has raised significant challenges to the memory capacity and processing efficiency. Utilizing disk-based parallel iterative computing is an economic solution. However, costs of disk I/O and communication affect the performance heavily. This paper proposes a state-transition model for SSSP and then designs two optimization strategies based on it. First, we introduce a tunable hash index to reduce the scale of wastef ul data loaded from the disk. Second, we propose a new iterative mechanism and design an Across-step Message Pruning (ASMP) policy to deal with the communication bottleneck. The experimental results illustrate that our SSSP computation is 2 times faster than a basic Giraph (a memoryresident parallel framework) implementation. Compared with Hadoop and Hama (disk-resident parallel frameworks), the speedup is 21 to 43.
PrefixSolve: Efficiently Solving Multi-Source Multi-Destination Path Queries on RDF Graphs by Sharing Suffix Computations ABSTRACT
"... Uncovering the “nature ” of the connections between a set of entities e.g. passengers on a flight and organizations on a watchlist can be viewed as a Multi-Source Multi-Destination (MSMD) Path Query problem on labeled graph data models such as RDF. Using existing graph-navigational path finding tech ..."
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Uncovering the “nature ” of the connections between a set of entities e.g. passengers on a flight and organizations on a watchlist can be viewed as a Multi-Source Multi-Destination (MSMD) Path Query problem on labeled graph data models such as RDF. Using existing graph-navigational path finding techniques to solve MSMD problems will require queries to be decomposed into multiple single-source or destination path subqueries, each of which is solved independently. Navigational techniques on disk-resident graphs typically generate very poor I/O access patterns for large, disk-resident graphs and for MSMD path queries, such poor access patterns may be repeated if common graph exploration steps exist across subqueries. In this paper, we propose an optimization technique for general MSMD path queries that generalizes an efficient algebraic approach for solving a variety of single-source path problems. The generalization enables holistic evaluation of MSMD path queries without the need for query decomposition. We present a conceptual framework for sharing computation in the algebraic framework that is based on “suffix equivalence”. Suffix equivalence amongst subqueries captures the fact that multiple subqueries with different prefixes can share a suffix and as such share the computation of shared suffixes, which allows prefix path computations to share common suffix path computations. This approach offers orders of magnitude better performance than current existing techniques as demonstrated by a comprehensive experimental evaluation over real and synthetic datasets.
Evaluation of SPARQL Property Paths via Recursive SQL
"... Abstract. Property paths, a part of the proposed SPARQL 1.1 standard, allow for non-trivial navigation in RDF graphs. We investigate the evaluation of SPARQL queries with property paths in a relational RDF store. We propose a translation of SPARQL property paths into recursive SQL and discuss possib ..."
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Abstract. Property paths, a part of the proposed SPARQL 1.1 standard, allow for non-trivial navigation in RDF graphs. We investigate the evaluation of SPARQL queries with property paths in a relational RDF store. We propose a translation of SPARQL property paths into recursive SQL and discuss possible optimization strategies. 1
Towards Unified Ad-hoc Data Processing
"... It is important to provide efficient execution for ad-hoc data pro-cessing programs. In contrast to constructing complex declarative queries, many users prefer to write their programs using procedural code with simple queries. As many users are not expert program-mers, their programs usually exhibit ..."
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It is important to provide efficient execution for ad-hoc data pro-cessing programs. In contrast to constructing complex declarative queries, many users prefer to write their programs using procedural code with simple queries. As many users are not expert program-mers, their programs usually exhibit poor performance in practice and it is a challenge to automatically optimize these programs and efficiently execute the programs. In this paper, we present UniAD, a system designed to simpli-fy the programming of data processing tasks and provide efficien-t execution for user programs. We propose a novel intermediate representation named UniQL which utilizes HOQs to describe the operations performed in programs. By combining both procedural and declarative logics, we can perform various optimizations across the boundary between procedural and declarative codes. We de-scribe optimizations and conduct extensive empirical studies using UniAD. The experimental results on four benchmarks demonstrate that our techniques can significantly improve the performance of a wide range of data processing programs.
Raghavan Raman Oracle Labs
"... The problem of efficiently analyzing graphs of various shapes and sizes has been recently enjoying an increased level of at-tention both in the academia and in the industry. This trend prompted creation of specialized graph databases that have been rapidly gaining popularity of late. In this paper w ..."
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The problem of efficiently analyzing graphs of various shapes and sizes has been recently enjoying an increased level of at-tention both in the academia and in the industry. This trend prompted creation of specialized graph databases that have been rapidly gaining popularity of late. In this paper we ar-gue that there exist alternatives to graph databases, provid-ing competitive or superior performance, that do not require replacement of the entire existing storage infrastructure by the companies wishing to deploy them. 1.
Finding the CostOptimal Path with Time Constraint over TimeDependent Graphs
"... Shortest path query is an important problem and has been well s-tudied in static graphs. However, in practice, the costs of edges in graphs always change over time. We call such graphs as timedependent graphs. In this paper, we study how to find a costoptimal path with time constraint in time-depend ..."
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Shortest path query is an important problem and has been well s-tudied in static graphs. However, in practice, the costs of edges in graphs always change over time. We call such graphs as timedependent graphs. In this paper, we study how to find a costoptimal path with time constraint in time-dependent graphs. Most existing works regarding the Time-Dependent Shortest Path (TD-SP) problem focus on finding a shortest path with the minimum travel time. All these works are based on the following fact: the earliest arrival time at a vertex v can be derived from the earliest arrival time at v’s neighbors. Unfortunately, this fact does not hold for our problem. In this paper, we propose a novel algorithm to compute a cost-optimal path with time constraint in time-dependent graphs. We show that the time and space complexities of our algorithm are O(knlogn + mk) and O((n + m)k) respectively. We confirm the effectiveness and efficiency of our algorithm through conducting experiments on real datasets with synthetic cost. 1.
Continuous query processing; Temporal analytics; Dynamic social
"... networks; Incremental computation. ..."
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