We are planning to use hibernate framework for an application which is something like an e-commerce application.
We have a requirement in which, if an user checks out an item and proceeds to the gateway, we will lock the item for 7 minutes, after which the item is released.
How can we design the above requirement? Ideas are appreciated.
You probably don't want to use a database level lock for this. Most databases and database configurations are not built around the concept of long-held locks.
The most generic approach I can think of is to build some kind of locking service in your application. The locking service has synchronized methods like tryObtainLock which will obtain the lock and return true if the lock is available or return false if the lock was not available (at which point you probably send an error to the user informing them the item is locked).
The locking service can then store in its own table a list of locks, who asked for them, and when they were obtained. Every so often you can check to see if any locks have been held for over 7 minutes and if so, release them and notify the person who obtained the lock that they no longer have it.
Related
Right now, I am thinking of implementing multi-threading to take tasks corresponding to records in the DB tables. The tasks will be ordered by created date. Now, I am stuck to handle the case that when one task (record) being taken, other tasks should skip this one and chase the next one.
Is there any way to do this? Many thanks in advance.
One solution is to make a synchronized pickATask() method and free threads can only pick a task by this method.
this will force the other free threads to wait for their order.
synchronized public NeedTask pickATask(){
return task;
}
According to how big is your data insertion you can either use global vectorized variables or use a table in the database itself to record values like (string TASK, boolean Taken, boolean finished, int Owner_PID).
By using the database to check the status you tend to accomplish a faster code in large scale, but if do not have too many threads or this code will run just once the (Synchronized) global variable approach may be a better solution.
In my opinion if you create multiple thread to read from db and every thread involve in I/O operation and some kind of serialization while reading row from same table.In my mind this is not scallable and also some performance impact.
My solution will be one thread will be producer which will read the row in batch and create task and submit the task to execution (will be thread pool of worker to do the actual task.)Now we have two module which can be scallable independently.In producer side if required we can create multiple thread and every thread will read some partition data.For an example Thread 1 will read 0-100 and thread 2 read 101-200.
It depends on how you manage your communication between java and DB. Are you using direct jdbc calls, Hibernate, Spring Data or any other ORM framework. In case you use just JDBC you can manage this whole issue on your DB level. you will need to configure your DB to lock your record upon writing. I.e. once a record was selected for update no-one can read it until the update is finished.
In case that you use some ORM framework (Such as Hibernate for example) the framework allows you to manage concurrency issues. See about Optimistic and Pessimistic locking. Pessimistic locking does approximately what is described above - Once the record is being updated no-one can read it until the update is finished. Optimistic one uses versioning mechanism, and then multiple threads can try to update the record but only the first one succeeds and the rest will get an exception saying that they are now working with stale data and they should read the record again. The versioning mechanism is to add a version column that is usually a number or sometimes timestamp. Each thread reads the record and upon update it checks if the version in DB still the same. If so it means no-ne else updated the record and upon update the version is changed (incremented or current timestamp is set). If the version changed then someone else already updated the record since it was read and so this thread has stale record and should not be allowed to update it. Optimistic locking shows better performance in environment where reading heavily outnumbers writing
For example, we have a table (login, hash). We have no unique constraint on login column, but we should keep it unique (just for example).
When a new user registers, we check if entered login is free.
If it's a java web app deployed to Tomcat, that has thread pool, then those checks might be processed parallel, right? How to ensure uniqueness then?
You can use pessimist lock in the table, that will lock the table and you can check if has and save, so other thread won't be able to change that table for this time being. But I think that is a really bad way to do things, why not use DB constraints ?
In short, you can't have a good solution without database constraints here.
Without a constraint in a multi-threaded environment you'll need some common resource to synchronize your threads on. A thread would acquire the mutex, check if login is free (using a SELECT) and then INSERT a new record if it was free. No other thread should be able to do this at the same time - this is why you need synchronization here.
This will work iff all your threads have access to this mutex and if it is guaranteed that noone else can access the database at the same time.
The first problem appears if you have, for instance several machines which access the same database. Threads running on different machines will not have access to the same mutex so they will happily insert in your table in parallel.
The other problem that if someone logs in to database and creates records in that table directly, such inserts may happen exactly between SELECT and INSERT executed from your code. So synchronization in code won't help here.
A further option is locking the whole table, but that's even worse. You'll need to very reliably release the lock otherwise you're risking stalling the whole system.
In my Java webapp, each instance is checking on startup if the database is up-to-date via a JDBC connection. If the DB is not up-to-date, it performs an update routine by executing SQL scripts.
I can't control when instances get startet. Therefore, I need to ensure that only a single instance is performing a database update at the same time. Ideally, I would need to lock the complete database, but according to
http://www.postgresql.org/docs/8.4/static/explicit-locking.html
and
http://wiki.postgresql.org/wiki/Lock_database
PostgreSQL doesn't support it (I'm still using version 8.4).
What other options do I have?
If you control the code for all the instances, then you can create a table in the database where each instance that starts, looks in this table for a record with a timestamp. Lets call it your "lock" record.
If a process finds that the lock record does not exist, then it inserts the record and processes the data you require.
If a process finds that the lock record does exist then you can assume that another process has created it and do nothing, busy wait, or what ever.
With this design you are effectively creating a "lock" in the database to synchronize your processes with. You code it, so all processes know they have to adhere to the logic of the lock record.
Once the first process that has the lock, has completed processing, it should clear the lock record so the next restart behaves correctly. You also need to think about the situation where the lock has not been cleared due to a server error, or execution erorr. Typically, if the lock is older than n minutes you can consider it to be "stale", therefore delete it, and create it again (or just update it).
When dealing with the "lock" record be sure to utilise the Serializable isolation level on your DB connection in order to guarantee atomicity.
The Service layer of your Java code can enforce with your locking strategy prior to calling your Data Access layer. It won't matter whether you use Hibernate or not, as it's just application logic.
Ideally, I would need to lock the complete database.
Does it really matter what your lock applies to, as long as you're effectively serializing access? Just acquire an exclusive lock on any table, or row for that matter.
This is a recent interview question to my friend:
How would you handle a situation where users enter some data in the screen and let's say 5 of them clicked on the Submit button *the SAME time ?*
(By same time,the interviewer insisted that they are same to the level of nanoseconds)
My answer was just to make the method that handles the request synchronized and only one request can acquire the lock on the method at a given time.
But it looks like the interviewer kept insisting there was a "better way" to handle it .
One other approach to handle locking at the database level, but I don't think it is "better".
Are there any other approaches. This seems to be a fairly common problem.
If you have only one network card, you can only have one request coming down it at once. ;)
The answer he is probably looking for is something like
Make the servlet stateless so they can be executed concurrently.
Use components which allow thread safe concurrent access like Atomic* or Concurrent*
Use locks only where you obsolutely have to.
What I prefer to do is to make the service so fast it can respond before the next resquest can come in. ;) Though I don't have the overhead of Java EE or databases to worry about.
Does it matter that they click at the same time e.g. are they both updating the same record on a database?
A synchronized method will not cut it, especially if it's a webapp distributed amongst multiple JVMs. Also the synchronized method may block, but then the other threads would just fire after the first completes and you'd have lost writes.
So locking at database level seems to be the option here i.e. if the record has been updated, report an error back to the users whose updates were serviced after the first.
You do not have to worry about this as web server launches each request in isolated thread and manages it.
But if you have some shared resource like some file for logging then you need to achieve concurrency and put thread lock on it in request and inter requests
I have a tasks thread running in two separate instances of tomcat.
The Task threads concurrently reads (using select) TASKS table on certain where condition and then does some processing.
Issue is ,sometimes both the threads pick the same task , because of which the task is executed twice.
My question is how do i make both thread not to read the same set of data from the TASKS table
It is just because your code(which is accessing data base)DAO function is not synchronized.Make it synchronized,i think your problem will be solved.
If the TASKS table you mention is a database table then I would use Transaction isolation.
As a suggestion, within a trasaction, set an attribute of the TASK table to some unique identifiable value if not set. Commit the tracaction. If all is OK then the task has be selected by the thread.
I haven't come across this usecase so treat my suggestion with catuion.
I think you need to see some information how does work with any enterprise job scheduler, for example with Quartz
For your use case there is a better tool for the job - and that's messaging. You are persisting items that need to be worked on, and then attempting to synchronise access between workers. There are a number of issues that you would need to resolve in making this work - in general updating a table and selecting from it should not be mixed (it locks), so storing state there doesn't work; neither would synchronization in your Java code, as that wouldn't survive a server restart.
Using the JMS API with a message broker like ActiveMQ, you would publish a message to a queue. This message would contain the details of the task to be executed. The message broker would persist this somewhere (either in its own message store, or a database). Worker threads would then subscribe to the queue on the message broker, and each message would only be handed off to one of them. This is quite a powerful model, as you can have hundreds of message consumers all acting on tasks so it scales nicely. You can also make this as resilient as it needs to be, so tasks can survive both Tomcat and broker restarts.
Whether the database can provide graceful management of this will depend largely on whether it is using strict two-phase locking (S2PL) or multi-version concurrency control (MVCC) techniques to manage concurrency. Under MVCC reads don't block writes, and vice versa, so it is very possible to manage this with relatively simple logic. Under S2PL you would spend too much time blocking for the database to be a good mechanism for managing this, so you would probably want to look at external mechanisms. Of course, an external mechanism can work regardless of the database, it's just not really necessary with MVCC.
Databases using MVCC are PostgreSQL, Oracle, MS SQL Server (in certain configurations), InnoDB (except at the SERIALIZABLE isolation level), and probably many others. (These are the ones I know of off-hand.)
I didn't pick up any clues in the question as to which database product you are using, but if it is PostgreSQL you might want to consider using advisory locks. http://www.postgresql.org/docs/current/interactive/explicit-locking.html#ADVISORY-LOCKS I suspect many of the other products have some similar mechanism.
I think you need have some variable (column) where you keep last modified date of rows. Your threads can read same set of data with same modified date limitation.
Edit:
I did not see "not to read"
In this case you need have another table TaskExecutor (taskId , executorId) , and when some thread runs task you put data to TaskExecutor; and when you start another thread it just checks that task is already executing or not (Select ... from RanTask where taskId = ...).
Нou also need to take care of isolation level for transaсtions.