网格映射防止任意一个数据网格占用所有可用的弹性缓存容量。
Grid capping prevents any one data grid from consuming all of the available elastic cache capacity.
总而言之，您需要使用缓存来优化数据的高容量和高访问频率。
In general, you want to use caching to optimize only high volume, high frequency access of data.
当服务处理更多的外部LSID时，缓存的容量会增加，以允许加速对外部数据的访问。
As the service handles more requests for external LSIDs, the cache grows, allowing increasingly rapid access to external data.
受限于内存容量，向缓存中加载大量数据通常也意味着它们很快会被清除出去，这会增加GC开销。
Loading large amounts of data into your cache also usually means that it will be evicted quickly due to your limited memory capacity, which increases GC overhead.
查询优化集中于cpu密集型(CPUbound)执行路径，而全缓存数据库将仍然集中于优化取页到大容量存储器的操作，而这已不再是问题。
Query optimization focuses on CPUbound execution paths, while a fully cached database will still be preoccupied with optimizing page fetches to mass storage that are no longer an issue.
为频繁访问的数据提供缓存可以节省时间或降低数据库的争用和总体请求容量。
Providing a cache for frequently-accessed data might time-shift or reduce contention and overall request volumes to the database.
后一个是分布式缓存器，当存储空间的容量用光的时候，就需要一种可扩展的机制来存储这些数据。
The latter is a distributed cache since this is where the bulk of storage space is used up, and a scalable mechanism is needed to store the data.
如果你能够从大容量的闪存缓存读取数据，而不是转动硬盘，就可以大大节省电源。
If you could get data from a large flash memory cache instead of spinning up the hard drive, you'd save a lot of power.
如果你能够从大容量的闪存缓存读取数据，而不是转动硬盘，就可以大大节省电源。
If you could get data from a large flash memory cache instead of spinning up the hard drive, you'd save a lot of power.
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