本文利用数据分片和并行处理策略，提出一种采用直接连接的查询优化算法，能有效地缩减查询处理的响应时间。
This paper presents an optimized query algorithm, which adopts direct-join using data partition and parallel processing. It can reduce the response time of query process.
对于使用超大数据集工作的开发者来说，水平的分区和分片都是很重要的工具。
Horizontal partitioning is an important tool for developers working with extremely large datasets.
对于横向分片数据，Mnesia在伸缩性和低延迟事务上表现突出，接下来的一个挑战可能是对于超大规模数据集它如何伸展。
While Mnesia excels at scalability and low latency in transactions on horizontally fragmented data, one remaining challenge may be how it will scale in terms of very large datasets.
论文的研究工作着眼于分片式流处理器的数据并行存储系统的分析、设计和实现。
This dissertation focuses on the analysis, design and implementation of data-parallel memory system for Tiled Stream Processor.
分片包括两个部分：数据库分片和查询分片。
Partition falls into two categories: database partition and query partition.
对应用数据分块，使得数据块大小符合通信子网mtu有效负载的要求，避免IP层分片需要重新分配缓冲区、计算校验和以及数据复制的费时操作。
Therefore, it can reduce one time data handling, 3 divide application data into blocks that content the demand of effective load of communication subnet MTU to avoid IP fragments.
所述播放方法是利用全局索引和分片索引定位数据包，进行播放操作。
The method for playing utilizes the global index and a slicing index to position the data packet so as to carry out the operation of playing.
所述播放方法是利用全局索引和分片索引定位数据包，进行播放操作。
The method for playing utilizes the global index and a slicing index to position the data packet so as to carry out the operation of playing.
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