为了提高性能，JCS在文件磁盘上存储实际缓存数据的同时，会在内存中存储缓存数据键。
To improve performance, JCS stores the cached data keys in memory while storing the actual cached data on the file disk.
如果目标模型跨多个表，数据差异分析还必须考虑数据键和键关系，以便有效地链接数据元素。
Where the target model is spread across multiple tables, the data Gap Analysis must also consider data keys and key relationships to effectively link data elements together.
例如，可能需要先输入数据，然后才能知道或验证外键是什么。
For example, you might need to enter data before you know or can validate what the foreign value is.
否则，其数据或键将分散在该表或索引所占用的所有区段中。
Otherwise, its data or keys will be scattered throughout the extents that have been occupied by the table or index.
在这种情况下，每个KPI都具有唯一的标识符，可以作为访问历史记录数据的键使用。
In this case, each KPI has a unique identifier, which can be used as a key to access the history data.
在这一部分中，您将看到如何生成为每一个用户会话存储数据所用的键。
In this section, you see how to generate keys that let you store data for each user session.
在这些情况下，建议您基于数据平衡选择分区键。
In such cases, it is recommended that you choose a partitioning key based on even data balancing.
试图使用片段或者试图从不存在的键访问数据就会抛出异常，指出相关的错误。
Trying to use slicing or trying to access data from nonexistent keys throws exceptions, indicating the relevant error.
关系分析以之前的域完整性分析和结构分析为基础，旨在发现共同的键或数据元素和域。
Relationship Analysis builds off of previous domain integrity and Structural Analysis to find common keys or data elements and domains.
索引是用来定位数据页的顺序指针或键的集合。
Indexes are collections of sequentially ordered Pointers or keys used for locating data pages.
可以根据具体的用途，将内核的数据划分为不同的内核键。
The kernel's data is classified into kernel keys according to intended use.
此参数的目的是改善性能并在用新分区键估算数据倾斜时最小化空间使用。
The purpose of this parameter is to improve performance and minimize the space usage when estimating data skew with new partitioning keys.
这个输入参数指定要被用在数据倾斜估算中的新分区键。
This input parameter specifies the new partitioning keys to be used in the estimation of data skews.
但是，在很多情况下，重要的实体是一个记录的一个子集，或者跨多个表，需要通过公共键链接数据。
However, in many cases, an entity of importance is a subset of a record, or spans several tables and requires data to be joined through a common key.
随着时间的推移，因数据的改变，旧的分区键有可能会不如之前那么好。
It is also possible that over time, as your data changes, old partitioning keys become less optimal than they were previously.
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。
In some cases, you might find that guidelines for choosing the proper partitioning key based on collocation and data balancing contradict one another.
第2部分将介绍关于MQT、MDC和DPF分区键的更多细节，重点分析数据仓库环境。
Part 2 covers additional details related to MQTs, MDCs, and DPF partitioning keys, focusing on the data warehouse environment.
没有索引sarg时，索引扫描将使用索引访问数据，但是会返回索引中的所有键。
Without an index sarg, an index scan will use the index to access the data, but will return every key in the index.
当按下的键准备读出时，数据准备线可用来作处理器的标志。
The data ready line can be used to flag the processor when a keystroke is ready to be read .
JSON格式是一组键和值，可以是各种数据形式，比如字符串、整型或浮点型——往下看。
The format of JSON is a collection of keys and values, which can be different data types, such as strings, ints or floats – see below.
是一种异构的、易变的容器，依赖键到数据值的映射(而不是特定的数字次序)来访问容器中的元素。
Is a heterogeneous, mutable container that relies on a key - to - data value mapping, rather than a particular numerical order to access items from the container.
当按下的键准备读出时，数据准备线可用来作处理器的标志。
The data ready line can be used to flag the processor when a keystroke is ready to be read.
您是否具有可用于跨多个系统匹配数据的键或标识符？
Do you have keys or identifiers that can be used for data matching across the participating systems?
可帮助您评估新的和已有分区键的数据倾斜的例程。
Routines that can help you estimate the data skew for new and existing partitioning keys.
新例程用来评估已有的和新的分区键的数据倾斜。
New routines to estimate data skews for existing and new partitioning keys.
为此，它将使用指定的字段作为唯一标识对应流程实例的键来对输入数据的内容进行检查。
It does this by examining the contents of the input data, using a specified field as a kind of key that uniquely identifies the corresponding process instance.
在这种环境下，应该查看数据模型来决定分区键的最佳选择。
In this kind of environment, you should examine your data model to determine the best choice for partitioning keys.
尽管概念很简单(如图1所示)，但是bucket、对象和键共同为构建数据存储解决方案提供很强的灵活性。
Though the concepts are simple, as shown in Figure 1, buckets, objects, and keys together provide a lot of flexibility for building your data storage solutions.
物理数据或键的连续性对于表扫描或键-索引扫描的速度十分重要。
Contiguity of physical data or keys is important to the speed of table scans or key-index scans.
为了有效访问大小为 >~1GB 的数据，分区应沿着合理的键进行。
In order to get efficient access to data sizes >~1 GB, partitioning should be done along a reasonable key.
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