Java + Redis与普通Java在数据密集型应用程序中的效率？ [英] Java+Redis vs plain Java efficiency for data intensive applications?

问题描述

在Java中使用Redis来开发Java中的数据密集型应用程序（例如数据挖掘）是否有帮助？

Does it help to use Redis with Java to develop data intensive applications (e.g. data-mining) in Java?

与普通Java相比，在大量数据上进行类似操作，它的工作速度更快还是消耗的内存更少？

Does it work faster or consume less memory comparing to plain Java for similar operation on high volume of data?

编辑：我的问题主要是关于在一台机器上运行。例如，使用大量列表/集合/地图并对其进行查询和排序。

My question is mostly about running on single machine. For example for working with a large number of list/set/maps and query and sort them.

推荐答案

Redis绝对不会在一台机器上的本机Java速度更快。它可以让您分配处理，但如果数据块确实很大，则无论如何它们都不可能放入内存中。在不了解您在做什么的情况下，建议您将数据存储在磁盘上。当您获得多台计算机时，可以通过网络挂载分区并以这种方式共享数据。另外，带有MapReduce的Hadoop听起来像您正在做的事情。

Redis will definitely not be faster that native Java on a single machine. It would allow you to distribute processing, but if the chunks of data really are large, they're not likely to fit into memory anyway. Without knowing more about what you're doing, I would suggest storing the data on disk. When you get multiple machines, you can network mount the partition and share the data that way. Alternatively, Hadoop with MapReduce sounds like the right sort of thing for what you're doing.

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