Browsing by Subject "Query"

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Open Access
Cache hierarchy-aware query mapping on emerging multicore architectures
(IEEE, 2017) Öztürk, Özcan; Orhan, U.; Ding, W.; Yedlapalli, P.; Kandemir, M. T.
One of the important characteristics of emerging multicores/manycores is the existence of 'shared on-chip caches,' through which different threads/processes can share data (help each other) or displace each other's data (hurt each other). Most of current commercial multicore systems on the market have on-chip cache hierarchies with multiple layers (typically, in the form of L1, L2 and L3, the last two being either fully or partially shared). In the context of database workloads, exploiting full potential of these caches can be critical. Motivated by this observation, our main contribution in this work is to present and experimentally evaluate a cache hierarchy-aware query mapping scheme targeting workloads that consist of batch queries to be executed on emerging multicores. Our proposed scheme distributes a given batch of queries across the cores of a target multicore architecture based on the affinity relations among the queries. The primary goal behind this scheme is to maximize the utilization of the underlying on-chip cache hierarchy while keeping the load nearly balanced across domain affinities. Each domain affinity in this context corresponds to a cache structure bounded by a particular level of the cache hierarchy. A graph partitioning-based method is employed to distribute queries across cores, and an integer linear programming (ILP) formulation is used to address locality and load balancing concerns. We evaluate our scheme using the TPC-H benchmarks on an Intel Xeon based multicore. Our solution achieves up to 25 percent improvement in individual query execution times and 15-19 percent improvement in throughput over the default Linux-based process scheduler. © 1968-2012 IEEE.
Open Access
An index structure for moving objects in video databases
(1999) Yavuz, Tuba
Modeling moving objects and Iiandling various types of motion queries are interesting topics to investigate in the area of video databases. In one type of motion queries, motion of multiple objects is specified by the changes in relative spatial positions of objects. Answering such kind of queries, that involve motion of multiple objects whose identifications cire not specified, requires some type of indexing because the time complexity of processing such a query in the absence of an index structure is 0{N \l{N — n)!), where N is the number of objects in the database and n is the number of objects in the query. In this work, we propose a spatio-temporal index structure, which we call ,S'M/A7-index, and compare its performance against a similar scheme proposed in [18]. The scheme presented in [18] consists of a constraint satisfaction algorithm, which is called Join Window Reduction (JW R ), combined with a spatial index structure (R*- tree). Experimental results indicate thcit SMIST-'mdex outperforms the JW R algorithm. Also, SMIST-'mdex is shown to be scalable to increasing number of frames and objects.