Method for updating cache of key-value distributed memory system

Abstract

The invention discloses a method for updating cache of a key-value distributed memory system. The method includes: initiating inquiry operation, distributing a column name for each list, and building a keyword; inquiring database and storing a result S if data of the keyword corresponding to cache do not exist, and directly returning to the result S if corresponding cache exists; inputting the returned result S in a key-value system by the inquiry operation using the keyword key, and enabling a corresponding value of the keyword to be S; building a keyword group by the inquiry operation according to the column names; registering the keyword in the corresponding value of the keyword group; returning to the result S; initiating updating operation and building the keyword group according to updated conditions; inquiring whether the corresponding value exists in the cache according to the keyword group, and deleting the corresponding value and completing updating if the corresponding value exists; and otherwise, stopping updating. By the method for updating cache of the key-value distributed memory system, the cache of the key-value distributed memory system can be kept persistently, and the related cache can be eliminated immediately during data updating, and a user can be guaranteed to see the latest data.

Description

technical field [0001] The invention relates to the field of computers, in particular to a method for updating the cache of a key-value distributed storage system. Background technique [0002] With the rapid development of the Internet, more and more people use the Internet. How to quickly respond to user requests has become one of the most important means for various Internet companies to win users. For example, the content provided by a website is very good and valuable, but users have to wait for dozens of seconds for each visit, so users will definitely lose after a long time. The core technical point to solve the fast response is how to use the cache efficiently, because compared with querying from the relational database, it is much faster to fetch data directly from the cache. Usually fetching data from the cache is at least faster than fetching data from the relational database. Data is more than 10 times faster and can support greater concurrent access. [0003] ...

AI Technical Summary

Problems solved by technology

But there are generally two problems. First, when a table is not updated, it can support a large amount of visits, but when the table is updated, because the relevant cache cannot be deleted accurately, only the cache of the entire table can be deleted. They are all cleared, so that although the next time the cache data is consistent with the database, the moment the cache is cleared, the pressure on the database will immediately increase, and the system is likely to crash

Second, for the former case, keep the cache for a shorter time. When there is data update, you don’t need to clear the cache of the entire table and wait for it to expire naturally. The advantage of this is that the pressure on the data will not suddenly increase. But the disadvantage is also obvious, that is, new data cannot be seen by users in real time

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