On relatively small amounts of data these queries will be processe quickly and with an increase in the size of the database they will slow down. The reason lies in the attachment mechanism. It is base on a line by line comparison of two or more tables according to the join condition for example the equality of chat id in messages and id in chat. And this puts a load on the database server which only increases with the growth of its size.
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To optimize this kind of queries there is a denormalization mechanism. Link table during denormalization Duplicate fields of the chat name chat name and avatar chat logo have been adde to the user chat link link table. It also displays the last message last msg and the number of unread messages unread msg count . Now you can use the user chat link table to get Denmark Email List the above fields and perform analytics on them without the nee to connect to the messages table. However this approach has limitations. Due to additional fields requests for reading and data aggregation are optimize however the price of this is force reundancy and complication of the business logic of the application. In particular writing queries for changing data update and delete as well as modifying the structure of the database create becomes more complicate.
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The use of denormalization must be carefully considere. You nee to be sure that the normalize structure optimize queries and properly tune indexes are no longer able to meet the performance criteria. Benefits of the relational approach definition of complex BM Leads relationships between objects data normalization and denormalization structure query language rich history of development and wide distribution the main tool in the development of various applications and services . Disadvantages of the approach a rigid structure of information about objects. Examples MySQL MariaDB PostgreSQL SQLite etc.