• Based on your application's business processes, you need to identify which tables to partition with the correct partitioning key.

    您需要根据应用程序的业务流程,确定用正确的分区键划分哪些表。

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  • In some cases, you might find that guidelines for choosing the proper partitioning key based on collocation and data balancing contradict one another.

    在某些情况下,您可能会发现根据并置和数据平衡选择恰当的分区键的准则会相互矛盾。

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  • This article provided guidance and tooling for choosing the best partitioning keys based on your needs.

    本文提供了如何根据您自己的需要选择最佳分区键的指导和工具。

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  • In my last column, I explained how you can use table partitioning to organize data across multiple storage objects based on values in one or more columns.

    在我的上一期专栏中,我阐述了如何使用表分区,基于一列或多列中的值,跨多个存储对象组织数据。

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  • Based on your data model, you should select partitioning keys that favor frequent joins and that are based on a primary key.

    基于数据模型,选择那些有利于频繁合并且基于主键的分区键。

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  • Choosing appropriate partitioning keys is essential for optimizing database performance in a partitioned environment based on DB2 software.

    选择适当的分区键对于优化基于DB 2软件的分区环境中的数据库性能非常关键。

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  • In addition, it is not a good idea to select partitioning keys based on a handful of SQL statements.

    此外,基于为数不多的sql语句选择分区键也不是一个好的做法。

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  • After configuring all the Network Based Installation Settings, the next step of the wizard is disk selection or custom disk partitioning.

    配置好所有Net workBasedInstallation设置后,向导的下一步是磁盘选择或自定义磁盘分区。

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  • In such cases, it is recommended that you choose a partitioning key based on even data balancing.

    在这些情况下,建议您基于数据平衡选择分区键。

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  • Autopartition, or automatic partitioning, sets partitions based on the selected installation type.

    Autopartition(或自动分区)会根据所选择的安装类型来设置分区。

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  • In the following example, Table1 is created on database partitions 1, 2, 3, and 4, and is redistributed based on a partitioning key on column col1.

    在如下的例子中,Table1创建于数据库分区1、2、3和4并且会基于列COL1上的一个分区键重新分配。

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  • Figure 1 illustrates some of the fundamental differences between the different types of partitioning and hypervisor-based virtualization solutions.

    图1演示了不同类型的分区和基于管理程序的虚拟化解决方案之间的一些基本差异。

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  • Typically, the partitioning key is time-based, resulting in a design that directs data for a given week, month, or quarter to be stored in a certain partition.

    通常,分区键是基于时间的,因此这种设计会把某一周、月或季度的数据存储在特定分区中。

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  • If you choose a partitioning key based on your query workload, the partitioning key should typically consist of either a joined column or a set of columns that is frequently used in many queries.

    如果基于查询工作负载选择一个分区键,那么此分区键通常应该包含一个合并列或常被用于很多查询的一组列。

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  • Logical partitioning provides POWER processor-based servers with the capability to do server consolidation and optimize system resources.

    逻辑分区为基于POWER处理器的服务器提供了进行服务器合并和优化系统资源的能力。

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  • The biggest difference is the use of namespaces for partitioning the elements into framework elements, elements based on basic CCs, and those based on aggregate CCs.

    最大的变化是使用名称空间将元素分成了框架元素、基于基本CC的元素和基于聚合 CC 的元素。

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  • A typical design for a database with monthly roll-out based on sale_date, would be to use sale_date as the table partitioning key and create a separate partition for each month.

    对于需要每月根据sale_date转出数据的数据库,一种典型的设计是使用sale_date作为表分区键,并为每个月创建一个单独的分区。

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  • Automatic, hash-function based data partitioning and distribution.

    支持自动地基于hash函数的数据分片策略。

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  • One emphasis of this paper is to present a hybrid search algorithm based on grid partitioning.

    本文的一个重点是提出了一种基于网格划分的混合搜索算法。

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  • The interactive partitioning system embody the platform based design character of SOC-CDE environment, and make good use of the design programming result in algorithm level.

    交互式划分系统体现了SOC - CDE环境基于平台设计的特点,并且充分利用了算法级设计规划提供的结果。

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  • A clustering algorithm based on density and partitioning method is presented according to the analysis of the strengths and weaknesses of traditional clustering algorithms.

    在分析常用聚类算法的特点和适应性基础上提出一种基于密度与划分方法的聚类算法。

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  • Motivated by this observation, a structural join algorithm based on range partitioning is proposed in this paper.

    基于这样的观察,提出了一种基于区域划分的结构连接算法。

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  • To deal with the hierarchical FPGA architectures, a modified partitioning algorithm was introduced here according to special hierarchical FPGA model based on the previous works.

    为了处理层次化FPGA结构,本文在前人划分工作的基础上,针对特定的层次化FPGA模型,提出了一种改进的划分算法。

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  • Based on the characteristics of a valid partitioning, it evaluates the partitioning result and merges the cells evaluated as invalid.

    它根据场景有效划分的特点,对分割结果进行评估,融合那些被过度划分的无效区域。

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  • Considering the problem of binary image code based on rectangular partitioning, an improved BSP binary image compression algorithm is provided.

    针对二值图像矩形划分编码在划分时存在的问题,本文提出一种改进的BSP二值图像的压缩算法。

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  • In order to raise compress ratio while accelerating encoding process, an algorithm com - bining fast convolution with quadtree partitioning based on neighbor search is adopted.

    为了在加速编码过程的同时提高压缩比,将快速卷积算法与基于四叉树分割的邻域搜索算法相结合。

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  • A new global optimization reliability method, knowledge-based clustered partitioning method (KCP) for reliability problems involving correlated non-normal random variables, is proposed.

    提出了分析相关非正态变量可靠度问题一种新的全局优化方法——认知聚类分区方法。

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  • The clustering method based on partitioning is mainly included K-Means and K-Medoids; the other methods are the mutation of these two methods.

    基于划分的聚类算法主要有K均值和K中心点算法,其他的方法都是这两种算法的变种。

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  • To reduce this high computational complexity, a new method is proposed to deal with the over-complete dictionary based on the signal set partitioning method.

    为此,本文提出了利用信号集合划分研究过完备原子库的新方法。

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  • To reduce this high computational complexity, a new method is proposed to deal with the over-complete dictionary based on the signal set partitioning method.

    为此,本文提出了利用信号集合划分研究过完备原子库的新方法。

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