JPA Optimisitic locking versus Pessimistic locking
By: Peter Schuler, 14 January 2010
As promised in my previous post I will blog some more about JPA and how to use it. In this post I will go into the locking features of JPA 2.0 including the new pessimistic lock options.
This post will:
- introduce the new locking features of the JPA;
- introduce both pessimistic locking and optimitic locking concepts;
- give a quick recap about JPA versioning;
- talk about the connection between locking and design;
- and finally compare both locking strategies.
JPA 2.0 now supports Pessimistic Locking:
A great omission of JPA 1.0 was the lack of pessimistic locking. Therefore it was necessary to fall back on the support of the underlying implementation to use the JPA is situation where pessimistic locking was required. This can happen when JPA shares a database with another process which does not know or supports versioning based optimistic locking.
JPA 2.0 now supports the following locking modes:
- OPTIMISTIC (==READ in JPA 1.0)
- OPTIMISTIC_FORCE_INCREMENT (==WRITE in JPA 1.0)
- PESSIMISTIC_READ
- PESSIMISTIC_WRITE
- PESSIMISTIC_FORCE_INCREMENT (A hybrid of both strategies)
- READ (kept around for backward compatibility)
- WRITE (kept around for compatibility)
Object can be locked by using the find() or refresh() operation of the EntityManager. For example:
Order order = entityManager.find(Order.class, 10, LockModeType.PESSIMISTIC_READ); SELECT ID, PRODUCT, AANTAL, VERSION, orderId FROM ORDER_TABLE WHERE (orderId = ?) FOR UPDATE.
As you can see the FOR UPDATE is added to the select query telling the database to get an exclusive lock on this selected row.
You can also use the lock() method on the entityManager and specify a Lock Mode on Queries (JPQL / Named and Criteria).
Now that we know how to unleash the power of pessimistic locking we need to learn how to use it well.
Locking Strategies: a quick recap….
Locking is a means to prevent data form becoming corrupted because two different processes are editing the same data. If we use locking correctly no two processes can edit (or if required) access the same data. Thus data can never be inconsistent.
As already mentioned there are two locking strategies: optimistic locking and pessimistic locking. I will describe both strategies and give an overview of their pro’s and con’s.
Pessimistic locking
This strategy is the standard locking provided by the database. It will protect data by limiting access to a single process. This is achieved by keeping track of all the currently active locks. If another process wants to access locked data it will have to wait until the other process releases the lock. Of course this introduces a whole range of potential errors like lock timeouts and deadlocks.
This locking strategy is called pessimistic because of the assumption that locking is always necessary to avoid corruption. Based on that assumption it introduces significant overhead in order to keep track of which process is assessing which data. Compare pessimistic locking to a traffic light. It will only allow vehicles to pass when it knows for sure that no one will be in the way.
Using pessimistic locking has some pro’s:
- The database is in charge and protects your data. Independent from application logic.
- A process or thread can only proceed if it has the right locks. Thus it is guaranteed that there will be no conflicts once the lock is acquired.
- Processes are put on hold until they can acquire the lock. (This blessing can also be a curse because a process can overwrite data the moment the lock is released. This feels like a missing update but is technically the correct behaviour. But as long as you read and write in the same transction you’re data is never stale.)
No pro’s without con’s:
- Keeping track of all those locks introduces significant overhead. Even if there is no data being accessed simultaneous the database still locks.
- The locking can lead to deadlocks and lock time out. These errors are hard to recover from and take a long time before the calling process is informed.
- Must be supported by the database.
So pessimistic locking depends on the database restricting access to data. But this comes at high overhead and hard-to-recover errors.
Optimistic locking
As pessimistic locking is embedded in the DBMS, optimistic locking is a strategy that by-passes the database. It will detect conflicts only when they occur. This is done introducing a version number to every table you want to protect. If you read data you will get the version number. If you alter the data you first check the version number again, and when holding the previous read value, update the record and increment the version number. If some one has “changed the data right from under you” you will see a different version number and know that there is a conflict. I will refer to the optimistic lock procedure as check&update.
This strategy is called optimistic because it never bothers to lock. It assumes that process will not bother each other until they do.
Using optimistic locking has some big pro’s:
- There is no (at least very little) overhead involved in locking.
- Optimistic locking is fast and easy to use, especially because it works implicitly. If you specify a @Version the upate&check will be performed automatically.
- It’s very efficient.
- It is database independent. No special features are required.
There are also some drawbacks:
- It will only detect conflicts, not prevent them. When it occurs it’s the application that must resolve the conflict. For example by showing the user a diff or an option to override the current version in the database.
- If a conflict occurs only one process is allowed to proceed. The others have their database transaction rolled back. This is far more expensive than waiting until you get the database lock.
- It will only work if everyone accessing the database plays by the versioning rules. The database does not enforce it.
- It can be considered ‘unfair’ as the process that writes the data first wins, opposed to the process that first acquired the lock.
- Sometimes optimistic locking is not sufficient. Locking a complete table to protect against insert for example.
So optimistic locking depends on the calling processes to respect the versioning rules. This makes it possible to detect conflicts and eliminates the need to keep of all the locks and gives Optimistic locking a huge advantage.
However when conflicts occurs it is up to the application to patch things up.
JPA support for optimistic locking
JPA supports optimistic locking based on versioning right from the first release. All you need to do is declare an attribute of your class with a @Version annotation.
For example:
@Entity public class Order { @id @GeneratedValue private Integer id; @Version private Integer version; }
The above code will result in a Order table with a primary key and version column. JPA will check and update the version after every change to Order.
More on JPA versioning can be found here.
Lock scope.
At first glance versioning seems to be the preferred strategy. It’s easy to use and with little overhead. However there is one more aspect to take into account when dealing with locking. That is what I call ‘the lock scope’.
Versioning will only lock (check&update) records that were changed. Databases will only lock records you tell it to lock by doing a SELECT … FOR UPDATE. Both procedures prevent processes from corrupting the database. But it will not prevent breaking business rules!
Let’s look at the following example:
This is a typical Order->OrderLine example. Order has a set of OrderLines which keep a price and quantity for every single item in Order. Let’s assume that there is a business rule that the total amount of money of an Order must stay below $10.000. This is easily achieved by adding a check on order to make sure that every addition/alteration of OrderLines will not break this rule.
A problem occurs when another process comes in and adds OrderLines to an Order at the same time. No single process knows all OrderLines. To make the check work in a concurrent environment you need to make the OrderLine updates in a serial order. In other words: the Order needs to be locked before any additions can be made to OrderLines. This ensures that the business rule can be enforced.
The JPA can achieve this by using one of the two lock levels: OPTIMISTC_FORCE_INCREMENT or PESSIMITC_WRITE. Both will give you a exclusive lock to make sure no other process can edit the same data.
This example illustrates that there are situations in which you need to think ahead about locking. Both versioning and database locks won’t help you out-of-the-box . You need to determine the right lock scope. Determining the lock scope is a business question and needs to be defined based on the functional design and then translated to technical requirements.
Choosing a locking Strategy.
Ok .. now you know about the pro’s and con’s of both locking strategies. You know how to use them technically and you know you need to think about the lock scope. So which strategy is for winners?
As you probably have guessed there is no straightforward answer.
Optimistic locking has little overhead and is easy to use, especially because it works implicitly in JPA. But you need to make sure that everyone using the database uses the same versioning approach. It’s also more expensive in terms of conflict resolving.
Optimistic locking is the preferred strategy if:
- You’re application has a private database.
- All the applications using the database know and use versioning.
- It is unlikely that there will be a lot of conflicts. (eg. Users editing the same data.)
Pessimistic locking will protect data on the database level. It will prevent conflicts by putting the process in a queue to wait for the lock. If there are a lot of collisions this gives a better change of more processes making it through. However having to keep a large lock administration involves a lot of overhead even if there a no conflicts.
So pessimistic locking it the preferred strategy if:
- Other non-versionized processes will edit the data you need to lock.
- You predict / see that there will be a lot of colissions.
For those among us unable to choose, JPA offers a hybrid solution. If you use the lock option PESSIMISTIC_FORCE_INCREMENT both Pessimitic and Optimisic locks are acquired at the same time. Offcourse you’re cutting of both your hands when using this option for every database call…. “Just to be sure .. “. You’ll end up with the bad from both locking strategies. But this hybird option can be a life saver when a particular table or operation must be protected at a database level and still has to participate in versionized transactions.
More information on locking
- JPA 2.0 Concurrency and locking – Shows transcipts of most lokcing possibilities.
- Explanation of Optimistic Concurrency Checking – Talks some more about optimisitic locking.
And don’t forget to think about the lock scope!
This is the second installment of my blogs about the JPA. Next time we’ll go into the new Criteria API of JPA 2.0.
- Special thanks to Martijn Blankestijn for the Order example and Jouke Stoel for test reading.