This is usually the second worst performing strategy due to its cache lock requirement and the heavy "push" update policy for clustered caches.
这通常是性能倒数第二的策略，因为它要求有缓存锁，缓存集群中使用重量级的“推”更新策略。
Use the "nonstrict-read-write" strategy if your data is read-mostly or concurrent cache access and update is rare.
如果你的数据读很多或者很少有并发缓存访问和更新，那么可以使用“nonstrict - read - write”策略。
Next, to optimize Rh you can improve the chances that an object will be found in the remote cache by using either a preloading strategy or a predictive loading strategy.
接下来，优化Rh，您可以使用预加载策略或预测性加载策略提高在远缓存中找到对象的几率。
Predictive loading is a strategy by which when you load an object (say, upon a cache miss) and then guess which other related objects might also need at the same time and load them as well.
而当您加载一个对象(比如缓存缺失之后)然后推测同时还需要哪些其他相关对象并加载它们时，则需要用到预测性加载策略。
The assumption on a lazy-load strategy is that once a piece of data has been loaded into the cache it will likely be used again.
延迟加载策略的构想是，如果将一个数据加载到了缓存中，就有可能再次用到它。
Whether or not you can cache-between-transactions depends on the concurrency strategy
是否可以在事务间缓存取决于并发策略
If this strategy is the one you choose, be careful of cache incoherency.
如果你选用了这种控制策略，要小心缓存区的不连续性。
The digital video signals bit plane separation strategy is applied in the circuit design, and the sub-field writing-in and sub-area readout to the cache memory method is used.
该电路的设计，应用了数字视频数据信号位面分离的策略，采用了分场写入、分区读出缓存存储器的方法。
Design of cache system for streaming media based on MOC strategy, discuss the key technology deeply.
基于MOC策略的流媒体代理缓存系统的设计，并对其实现的关键技术进行了深入探讨。
Using correlative query cache to replace tradition cache, the article designs and implements the cache structure, query matching, strategy of consistency and strategy of replacement.
设计使用基于查询相关查询的缓存代替传统缓存，对于缓存的结构、查询匹配、一致性维护策略及替换策略均作了详细设计。
If enable this strategy, the user cannot be examined and change the setting of exterior of record of homepage, cache, history, webpage and auxiliary function.
如果启用此策略，则用户无法查看和更改主页、缓存、历史记录、网页外观以及辅助功能的设置。
Because of the user's mobility and the location dependency of data, new challenge has been brought to cache replacement strategy for location Dependent Query (LDQ).
在位置相关查询(LDQ)中由于用户的移动性和数据的位置相关性，给缓存替换策略带来了新的挑战。
Because of the user's mobility and the location dependency of data, new challenge has been brought to cache replacement strategy for location Dependent Query (LDQ).
在位置相关查询(LDQ)中由于用户的移动性和数据的位置相关性，给缓存替换策略带来了新的挑战。
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