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Reasonable allocation of MySQL cache to improve cache hit rate

It is well known that the system reads data from memory hundreds of times times faster than it does from the hard disk. So now most of the application system, will maximize the use of caching (in memory, a storage area) to improve the system's operational efficiency. MySQL database is no exception.   Here, the author will combine their own work experience, with you to explore the MySQL database Cache management skills: How to properly configure the MySQL database cache, improve cache hit rate.   When will the application get the data from the cache? Database read from server ...

Silverlight assembly Cache Smart Settings optimize user experience

The assembly cache in Silverlight can place separate assemblies outside the XAP package and can slow down the client's browser, which reduces the time it will take to download the XAP package when the program starts.   Silverlight does not open the assembly cache by default, so it needs to be started on its own. Right-click to open the properties of the project and hook up the smaller xap size option by using the threading cache, as shown in figure: Compile the project before you select this item look at the DLL in XAP, figure: Recompile project, select ...

Anatomy of Twitter "7" as a progressive not thorough

"7" as a progressive not completely incomplete way of working, for architectural design is a progress. When a user from a browser requests to reach the Twitter backend, the first one to greet it is the Apache Web Server. The second exit is Mongrel Rails Server. Mongrel is responsible for handling requests for uploads as well as for downloading requests. Mongrel processing upload and download business logic is very concise, but the simple appearance, but contains the unconventional ...

Spark Streaming fault-tolerant improvements and 0 data loss

This article comes from a blog article from the spark streaming project leader Tathagata Das, who is now working for the Databricks company. In the past, the Amplab laboratory in UC Berkeley has been working on large data and spark streaming.   This paper mainly talks about the improvement of spark streaming fault tolerance and 0 data loss. The following is the original: the real-time streaming system must be able to work within 24/7 hours, so it needs to have from various systems ...

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