Java Open source Fresh e-commerce platform discussion and solution of concurrency problem and lock mechanism in-oms Order system (source code can be downloaded)

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Java Open source Fresh e-commerce platform discussion and solution of concurrency problem and lock mechanism in-oms Order system (source code can be downloaded)

Description: Discussion and solution of concurrency problem and lock mechanism in OMS order system of Java Open Source fresh e-commerce:

Origin of the problem

Suppose in an order system (take train ticket order system for example), user A, User B are to book a train ticket from Chengdu to Beijing, A, b in different ticket window at the same time inquires into a car sleeper, the next berth there is vacant. User A is hesitant to order Zhong Pu or lower berth, then User B decisively ordered the lower berth. When user a decides to book the lower berth, the system indicates that the lower berth has been booked, please re-select the bunk. In this system scenario, let's explore how the train ticket system handles concurrency events and how to use locking mechanisms to avoid duplicate bookings.

Scenario envisaged

Scenario 1:

In order to avoid duplicate bookings, most people will think before the booking operation, go to the database to check whether the bunk has been booked, assuming that the "bunk" database table added flag field flag (idle: 0; Booked: 1), if the value of the flag field of the query to the bunk is 1, then the reservation is unsuccessful, if the booking is 0 , and set the flag to 1. This scenario might be feasible in a system with a small volume of business. However, when the volume of business is large, especially the train ticket such business volume, there will be problems. The problem is that when user A, User B, while booking the same bunk, although the "simultaneous", but for database operations must be sequential, assuming a in the query of the berth flag, a value of 0, ready to book and set the value to 1, while B has been booked successfully, and has set flag to 1. A because there is no immediate query to the flag=1, so the booking is also successful, and flag is set to 1.

A flag=0 moment =t1 (enquiry)

B flag=0 moment =t2 (query)

B flag=1 moment =t3 (update)

A flag=1 moment =t4 (update)

This creates a duplicate booking, at the peak of the ticket purchase, the use of such a scheme, repeat booking inevitable.

Scenario 2:

We think of the use of database pessimistic lock to solve this problem, imagine if user a query to want to book tickets, User B simply can not query, only a a person to see, it is not the possibility of duplicate tickets, because no one to rob him. This scenario can be implemented as follows:

SELECT * FROM table where ... for update skip locked, the statement is to query the user to specify the conditions of the ticket information, and lock (for update), if there is a record has been locked automatically skip to the next record (skip locked), so who First query who can slowly consider the upper bunk or the lower berth. But is the train ticket system doing this? Obviously not, because this user experience is too bad, the ticket actually still many, but do not see can not buy, this obviously unreasonable.

Scenario 3:

We also think of the process to solve the concurrency problem, the simplest way is to use synchronized to deal with, but we need to know that a large-scale system is necessarily a cluster deployment, synchronized can only solve the single-node environment concurrency problem, To resolve this issue, you must rely on the global locking mechanism.

Scenario 4:

Now that we're back on the database, let's think about it. What if we use optimistic locks when querying, but what about using pessimistic locks before we make a reservation? For example, when we query:

SELECT * FROM table where ...

Both User A and User B are queried for the same ticket information (Zhong Pu and bunk), and user A or User B makes a pessimistic lock at the time of booking:

SELECT * FROM table where ... for update (pessimistic lock on reserved tickets only)

At this time the latter at the time of booking, unable to obtain the lock of the record, nature can not book, avoid the problem of duplicate booking.

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Java Open source Fresh e-commerce platform-java backend generated token architecture and design details (source can be downloaded), If you need to download, you can download under my github.

https://github.com/137071249/

Group number: 168096884

Java Open source Fresh e-commerce platform discussion and solution of concurrency problem and lock mechanism in-oms Order system (source code can be downloaded)

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