Compressed positionally encoded record filters in distributed query processing.

Different from a centralized database system, distributed query processing involves data transmission among distributed sites, which makes reducing transmission cost a major goal for distributed query optimization. A Positionally Encoded Record Filter (PERF) has attracted research attention as a cost-effective operator to reduce transmission cost. A PERF is a bit array generated by relation tuple scan order instead of hashing, so that it inherits the same compact size benefit as a Bloom filter while suffering no loss of join information caused by hash collisions. Our proposed algorithm PERF_C (Compressed PERF) further reduces the transmission cost in algorithm PERF by compressing both the join attributes and the corresponding PERF filters using arithmetic coding. We prove by time complexity analysis that compression is more efficient than sorting, which was proposed by earlier research to remove duplicates in algorithm PERF. Through the experiments on our synthetic testbed with 36 types of distributed queries, algorithm PERF_C effectively reduces the transmission cost with a cost reduction ratio of 62%--77% over IFS. And PERF_C outperforms PERF with a gain of 16%--36% in cost reduction ratio. A new metric to measure the compression speed in bits per second, compression bps , is defined as a guideline to decide when compression is beneficial. When compression overhead is considered, compression is beneficial only if compression bps is faster than data transfer speed. Tested on both randomly generated and specially designed distributed queries, number of join attributes, size of join attributes and relations, level of duplications are identified to be critical database factors affecting compression. Tested under three typical real computing platforms, compression bps is measured over a wide range of data size and falls in the range from 4M b/s to 9M b/s. Compared to the present relatively slow data transfer rate over Internet, compression is found to be an effective means of reducing transmission cost in distributed query processing. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .Z565. Source: Masters Abstracts International, Volume: 43-01, page: 0249. Adviser: J. Morrissey. Thesis (M.Sc.)--University of Windsor (Canada), 2004

A New Client-Server Architecture for Distributed Query Processing

This paper presents the idea of "tuple bit-vectors" for distributed query processing. Using tuple bit-vectors, a new two-way semijoin operator called 2SJ++ that enhances the semijoin with an essentially "free" backward reduction capability is proposed. We explore in detail the benefits and costs of 2SJ++ compared with other semijoin variants, and its effect on distributed query processing performance. We then focus on one particular distributed query processing algorithm, called the "one-shot" algorithm. We modify the one-shot algorithm by using 2SJ++ and demonstrate the improvements achieved in network transmission cost compared with the original one-shot technique. We use this improvement to demonstrate that equipped with the 2SJ++ technique, one can improve the performance of distributed query processing algorithms significantly without adding much complexity to the algorithms

Comparative Evaluation of Techniques for n-way Stream Joins in Wireless Sensor Networks

In wireless sensor networks, sensor data are accessed using relational queries. Join queries are commonly used to retrieve the data from multiple tables stored in different parts of a wireless sensor network. However, such queries require large amounts of energy. Many studies have intended to reduce query energy consumption. However, most of the proposed techniques addressed binary joins which are performed between static tables. N-way joins between data streams were rarely considered. Join queries using data streams work continuously and require increasing energy, which is why n-way joins involving several tables consume so much energy. Thus, the challenge lies in reducing energy dissipation. Additionally, it is necessary to determine the appropriate execution order for an n-way join. The number of possible implementations of an n-way join grows exponentially with the tables’ number. In this paper, interesting approaches for n-way joins between streams of data are evaluated. The methods that have been compared are extern-join, Sens-join of Stern et al, and the two techniques NSLJ (N-way Stream Local Join) and NSLSJ (N-way Stream Local Semi-Join). Comparisons are conducted according to several parameters to determine which use case is appropriate for each technique. NSLSJ works best for join queries with low join selectivity factors, while extern-join is more suitable for queries with very high selectivity factors

A filtering technique for n-way stream joins in wireless sensors networks

Purpose ”“ The join operations between data streams need more time and request more energy than traditional joins. In wireless sensor networks, energy is a critical factor. The survival of the network depends on this energy, thus it is necessary to consider, for this type of queries in such networks, the reduction of the sensors’ energy consumption. While works that have been done to treat n-way join operations between data streams are rare so far, we propose a technique, named NSLSJ (N-way Stream Local Semi-Join) to perform this type of join operations. The principal aim is to considerably reduce the consumed energy. Methodology/approach/design ”“ The technique 'N-way Stream Local Semi-Join (NSLSJ) proposed in this paper is based on an in-network execution, and on filtering tuples strategy for an important gain in energy. Findings ”“ Compared to NSLJ and Sens-Join techniques, NSLSJ shows better performances in the realized tests as it consumes less energy.Purpose ”“ The join operations between data streams need more time and request more energy than traditional joins. In wireless sensor networks, energy is a critical factor. The survival of the network depends on this energy, thus it is necessary to consider, for this type of queries in such networks, the reduction of the sensors’ energy consumption. While works that have been done to treat n-way join operations between data streams are rare so far, we propose a technique, named NSLSJ (N-way Stream Local Semi-Join) to perform this type of join operations. The principal aim is to considerably reduce the consumed energy. Methodology/approach/design ”“ The technique 'N-way Stream Local Semi-Join (NSLSJ) proposed in this paper is based on an in-network execution, and on filtering tuples strategy for an important gain in energy. Findings ”“ Compared to NSLJ and Sens-Join techniques, NSLSJ shows better performances in the realized tests as it consumes less energy.Purpose ”“ The join operations between data streams need more time and request more energy than traditional joins. In wireless sensor networks, energy is a critical factor. The survival of the network depends on this energy, thus it is necessary to consider, for this type of queries in such networks, the reduction of the sensors’ energy consumption. While works that have been done to treat n-way join operations between data streams are rare so far, we propose a technique, named NSLSJ (N-way Stream Local Semi-Join) to perform this type of join operations. The principal aim is to considerably reduce the consumed energy. Methodology/approach/design ”“ The technique 'N-way Stream Local Semi-Join (NSLSJ) proposed in this paper is based on an in-network execution, and on filtering tuples strategy for an important gain in energy. Findings ”“ Compared to NSLJ and Sens-Join techniques, NSLSJ shows better performances in the realized tests as it consumes less energy

Processing of an iceberg query on distributed and centralized databases

Master'sMASTER OF SCIENC