MySQL details (19) ---------- paging Query Optimization for massive data, mysql ----------

MySQL details (19) ---------- paging Query Optimization for massive data, mysql ----------

The detailed explanation of the paging, please see the http://blog.csdn.net/u011225629/article/details/46775947

View the code print 1 SELECT * FROM table order by id LIMIT, 10;
The preceding SQL statement does not have any problems in principle or in practice. However, when the data volume of the table exceeds 100,000, the preceding statement is executed again, it may take more than 10 seconds to execute, and the execution time will be longer when the page number gets back, in this case, we need to find a faster query method to replace this operation.

There are already many optimization methods on the internet, basically like this:

View the code print 1 SELECT * FROM table WHERE id> = (SELECT id FROM table LIMIT 1000000, 1) LIMIT 10;
The preceding SQL statement is a good solution. The speed of querying by page is kept within one second. However, we can conclude that there is a better way, as shown below:

View the code print 1 SELECT * FROM table WHERE id BETWEEN 1000000 AND 1000010;
Compared with the above solutions, the speed will be much faster.

I also share two tips on query:

(1) If the id to be queried is not a consecutive segment, the best practice is to first find the id and then use in to query:

View the code print 1 SELECT * FROM table WHERE id IN (10000,100 000, 1000000 ...);
(2) When you query a long string of a field, you must add a field to the field during table design. For example, if you want to query this field, do not directly query a string, which is inefficient. Check the crc32 or md5 value of the string.

How to optimize Mysql's 10 million-level quick paging: The following is an excerpt and online record for your reference.

How high is MySql performance? I have been using php for more than half a year. I think this problem from the day before yesterday. Have been suffering, have been desperate, and are full of confidence now! MySql is definitely suitable for dba-level Masters. Generally, you can write 11 thousand pieces of news in a small system, and you can achieve rapid development using the xx framework. However, if the data volume reaches 0.1 million or tens of millions, can the performance be so high? A small mistake may cause the whole system to be rewritten, or even the system cannot run normally! Okay, not that much nonsense. Let's talk about the facts and look at the example:

The data table collect (id, title, info, vtype) has these four fields, where title is fixed length, info is text, id is gradual, vtype is tinyint, and vtype is index. This is a simple model of a basic news system. Now fill in the data and 0.1 million news articles. Finally, collect contains 0.1 million records, and the database table occupies 1.6 GB of hard disk space. OK. Check the following SQL statement:

Select id, title from collect limit 0.01, 10; very fast; basically seconds on OK, then look at the following

Select id, title from collect limit 90 thousand, 10; pagination starts from. What is the result?

8-9 seconds. What's wrong with my god? In fact, we need to optimize this data and find the answer online. Let's look at the following statement:

Select id from collect order by id limit 90000,10;

Soon, 0.04 seconds is OK. Why? Because it is faster to use the id Primary Key for indexing. The online modification method is:

Select id, title from collect where id >=( select id from collect order by id limit 90000,1) limit 10;

This is the result of indexing with id. But the problem is a little complicated, and it's all done. See the following statement.

Select id from collect where vtype = 1 order by id limit 90000,10; very slow, 8-9 seconds!

At this point, I believe many people will feel the same as me! What if the vtype has been indexed? How can it be slow? Vtype is good for indexing. You can directly

Select id from collect where vtype = 1 limit 1000,10;

It is very fast, basically 0.05 seconds, but it is increased by 90 times. From 90 thousand, it is the speed of 0.05*90 = 4.5 seconds. And the test result is 8-9 seconds to an order of magnitude. Some people have put forward the idea of table sharding from here. This is the same idea as that of the dis # cuz forum. The idea is as follows:

Create an index table: t (id, title, vtype) and set it to a fixed length. Then, perform pagination, and retrieve the results by page in collect. Is it feasible? The experiment is complete.

0.1 million records are recorded in t (id, title, vtype), and the data table size is about 20 mb. Use

Select id from t where vtype = 1 order by id limit 90000,10;

Soon. It can basically be completed in 0.1-0.2 seconds. Why? I guess it is because there is too much collect data, so paging takes a long time. Limit is completely related to the size of the data table. In fact, this is still a full table scan, only because the data volume is small and only 0.1 million is fast. OK. Here is a crazy experiment, which adds 1 million entries to test the performance. After adding 10 times of data, the t table will reach more than 200 MB and the length is fixed. Or the query statement just now. The time is 0.1-0.2 seconds! Is table sharding performance okay? Error! Because our limit is still 90 thousand, so fast. Big, starting from 0.9 million

Select id from t where vtype = 1 order by id limit 900000,10;

Check the result. The time is 1-2 seconds! Why?

The table sharding time is still so long and depressing! Some people say that the fixed length will improve the performance of limit. At first I thought that because the length of a record is fixed, mysql should be able to calculate the 0.9 million position? However, we overestimated the intelligence of mysql. It is not a business database. It turns out that fixed length and non-fixed length have little impact on limit? No wonder some people say that discuz will be slow when it reaches 1 million records. I believe this is true. This is related to database design!

Can't MySQL exceed the 1 million limit ??? When the page size reaches 1 million, the limit is reached?

The answer is: Why can't NO exceed 1 million because mysql is not designed. Next we will introduce the non-Table sharding Method for a crazy test! How to quickly split a table with 1 million records and 10 Gb databases!
 
Now, our test goes back to the collect table and the test conclusion is:

0.3 million data. It is feasible to use the table sharding method. If it exceeds 0.3 million, it will slow down and you cannot bear it! Of course, if you use the sub-table + me method, it is absolutely perfect. However, after using this method, it can be perfectly solved without table sharding!
 
The answer is: Composite Index! When I designed a mysql index, I accidentally found that the index name can be any one, and several fields can be selected. What is the purpose? Start

Select id from collect order by id limit 90000,10;

This is because the index is adopted, but if the where clause is added, the index is not taken. I tried to add an index like search (vtype, id. Then test

Select id from collect where vtype = 1 limit 90000,10; very fast! Finished in 0.04 seconds!

Test again: select id, title from collect where vtype = 1 limit 90000,10; very sorry, 8-9 seconds, did not go to the search index!

Test again: search (id, vtype) or select id statement, also very sorry, 0.5 seconds.

To sum up, if you want to reference limit with the where condition, you must design an index and place where first. The primary key used by limit is placed at 2nd bits, and only the select primary key can be used!

Solved the paging problem perfectly. If you can quickly return the id, there is hope to optimize the limit. According to this logic, millions of limit can be completed in seconds. It seems that mysql statement optimization and indexing are very important!
 
Now, back to the original question, how can we quickly apply the above research to development? If a composite query is used, my Lightweight Framework will be useless. You have to write the paging string by yourself. How much trouble is that? Let's look at another example. The idea is coming out:

Select * from collect where id in (9000,12, 50,7000); you can check it in 0 seconds!

Mygod and mysql indexes are equally valid for in statements! It seems that it is wrong to say that in cannot use indexes on the Internet!

With this conclusion, we can easily apply it to a lightweight framework:

Through simple transformation, the idea is actually very simple:

(1) Optimize the index, find the id, and splice it into a string like "12000.

(2) 2nd queries to find the results. With a small index and a few changes, mysql can support efficient paging with millions or even tens of millions of pages!

Through the example here, I have reflected on one point: for large systems, PHP cannot use frameworks, especially those that cannot even be seen by SQL statements! At first, I almost collapsed my Lightweight Framework! It is only suitable for rapid development of small applications. For ERP, OA, and large websites, the data layer, including the logic layer, cannot use frameworks. If programmers lose control over SQL statements, the risk of the project will increase exponentially! Especially when using mysql, mysql must be a professional dba to achieve its best performance. A single index may result in a performance difference of thousands of times!

Copyright Disclaimer: you are welcome to reprint it. I hope to add the original article address at the same time. Thank you for your cooperation and learning!