Preliminary:
I have an application which maintains a thread pool of about 100 threads. Each thread can last about 1-30 seconds before a new task replaces it. When a thread ends, that thread will almost always will result in inserting 1-3 records into a table, this table is used by all of the threads. Right now, no transactional support exists, but I am trying to add that now. Also, the table in question is InnoDB. So...
Goal
I want to implement a transaction for this. The rules for whether or not this transaction commits or rollback reside in the main thread. Basically there is a simple function that will return a boolean.
Can I implement a transaction across multiple connections?
If not, can multiple threads share the same connection? (Note: there are a LOT of inserts going on here, and that is a requirement).
1) No, a transaction is limited to a single DB connection.
2) Yes, a connection (and transaction) can be shared across multiple threads.
Well, as stated in a different answer you can't create a transaction across multiple connections. And you can share the single connection across threads. However you need to be very careful with that. You need to make sure that only one thread is writing to the connection at the same time. You can't just have multiple threads talking across the same connection without synchronizing their activities in some way. Bad things will likely happen if you allow two threads to talk at once (memory corruptions in the client library, etc). Using a mutex or critical section to protect the connection conversations is probably the way to go.
-Don
Sharing connections between lots of threads is usually implemented by using a connection pool. Every thread can request a connection from the pool, use it for its purposes (one or more transactions, committed or rolled back) and hand it back to the pool once the task is finished.
This is what application servers offer you. They will take care of transactions, too, i. e. when the method that requested the transaction finishes normally, changes are committed, if it throws an exception, the database transaction is rolled back.
I suggest you have a look at Java EE 5 or 6 - it is very easy to use and can even be employed in embedded systems. For easy start, have a look at Netbeans and the Glassfish application server. However the general concepts apply to all application servers alike.
As for InnoDB, it will not have any problems handling lots of transactions. Under the supervision of the app server you can concentrate on the business logic and do not have to worry about half-written updates or anyone seeing updates/inserts before the transaction they originate from has been committed.
InnoDB uses MVCC (multi version concurrency control), effectively presenting each transaction with a snapshot of the whole database as of the time when it was started. You can read more about MVCC here in a related question: Question 812512
Related
Recently we've added a functionality in our RoR application which allows users to open a particular record, let's say in their own individual tabs. Doing so, we've started seeing frequent ActiveRecord::StaleObject errors. On investigating the issue I found that rails is indeed trying to update the session store first whenever a resource is opened in a tab and the exception is raised.
We've lock_version in our active record session store, so Rails is taking it as optimistic locking by default. Is there any way we could solve this issue without introducing much complexity, as the application is already live on the client's machine and without affecting any sessions' data we've stored in our session store DB.
Any suggestions would be much appreciated. Thanks
It sounds like you're using optimistic locking on a db session record and updating the session record when you process an update to other records. Not sure what you'd need to update in the session, but if you're worried about possibly conflicting updates to the session object (and need the locking) then these errors might be desired.
If you don't - you can refresh the session object before saving the session (or disable it's optimistic locking) to avoid this error for these session updates.
You also might look into what about the session is being updated and whether it's strictly necessary. If you're updating something like "last_active_on" then you might be better off sending off a background job to do this and/or using the update_column method which bypasses the rather heavyweight activerecord save callback chain.
--- UPDATE ---
Pattern: Putting side-effects in background jobs
There are several common Rails patterns that start to break down as your app usage grows. One of the most common that I've run into is when a controller endpoint for a specific record also updates a common/shared record (for example, if creating a 'message' also updates the messages_count for a user using counter cache, or updates a last_active_at on a session). These patterns create bottlenecks in your application as multiple different types of requests across your application will compete for write locks on the same database rows unnecessarily.
These tend to creep into your app over time and become hard to refactor later. I'd recommend always handling side-effects of a request in an asynchronous job (using something like Sidekiq). Something like:
class Message < ActiveRecord::Base
after_commit :enqueue_update_messages_count_job
def enqueue_update_messages_count_job
Jobs::UpdateUserMessageCountJob.enqueue(self.id)
end
end
While this may seem like overkill at first, it creates an architecture that is significantly more scalable. If counting the messages becomes slow... that will make the job slower but not impact the usability of the product. In addition, if certain activities create lots of objects with the same side-effects (lets say you have a "signup" controller that creates a bunch of objects for a user that all trigger an update of user.updated_at) it becomes easy to throw out duplicate jobs and prevent updating the same field 20 times.
Pattern: Skipping the activerecord callback chain
Calling save on an ActiveRecord object runs validations and all the before and after callbacks. These can be slow and (at times) unnecessary. For example, updating a message_count cached value doesn't necessarily care about whether the user's email address is valid (or any other validations) and you may not care about other callbacks running. Similar if you're just updating a user's updated_at value to clear a cache. You can bypass the activerecord callback chain by calling user.update_attribute(:message_count, ..) to write that field directly to the database. In theory this shouldn't be necessary for a well designed application but in practice some larger/legacy codebases may make significant use of the activerecord callback chain to handle business logic that you may not want to invoke.
--- Update #2 ---
On Deadlocks
One reason to avoid updating (or generally locking) a common/shared object from a concurrent request is that it can introduce Deadlock errors.
Generally speaking a "Deadlock" in a database is when there are two processes that both need a lock the other one has. Neither thread can continue so it must error instead. In practice, detecting this is hard, so some databases (like postgres) just throw a "Deadlock" error after a thread waits for an exclusive/write lock for x amount of time. While contention for locks is common (e.g. two updates that are both updating a 'session' object), a true deadlock is often rare (where thread A has a lock on the session that thread B needs, but thread B has a lock on a different object that thread A needs), so you may be able to partially address the problem by looking at / extending your deadlock timeout. While this may reduce the errors, it doesn't fix the issue that the threads may be waiting for up to the deadlock timeout. An alternative approach is to have a short deadlock timeout and rescue/retry a few times.
I'm building my first single-producer/single-consumer app in which the consumer takes items off the queue and stores them in a MySQL database.
Previously, when it was a single thread app, I would open a connection to the DB, send the query, close the connection, and repeat every time new info came in.
With a producer-consumer setup, what is the better way to handle the DB connection? Should I open it once before starting the consumer loop (I can't see a problem with this, but I'm sure that one of you fine folks will point it out if there is one)? Or should I open and close the DB connection on each iteration of the loop (seems like a waste of time and resources)?
This software runs on approximately 30 small linux computers and all of them talk to the same database. I don't see 30 simultaneous connections being an issue, but I'd love to hear your thoughts.
Apologies if this has been covered, I couldn't find it anywhere. If it has, a link would be fantastic. Thanks!
EDIT FOR CLARITY
My main focus here is the speed of the consumer thread. The whole reason for switching from single- to multi-threaded was because the single-threaded version was missing incoming information because it was busy trying to connect to the database. Given that the producer thread is expected to start dumping info into the buffer at quite a high rate, and given that the buffer will be limited in size, it is very important that the consumer work through the buffer as quickly as possible while remaining stable.
Your MySQL shouldn't have any problems handling connections in the hundreds, if not thousands.
On each of your consumers you should set up a connection pool use that from your consumer. If you consume the messages in a single thread (per application) the pool only needs to use one connection but it's also fine to consume and start parallel threads that all use one connection.
The reason for using a connection pool is that it will handle re connection and keep alive for you. Just ask it for one connection and have it promise that it will work (it does this by running a small query against the database). If you don't use a connection for a while and it get's terminated the pool will just create a new one.
Would it add overhead to put a DB transactions around every single service method in our application?
We currently only use DB transactions where it's an explicit/obvious necessity. I have recently suggested transactions around all service methods, but some other developers asked the prudent question: will this add overhead?
My feeling is not - auto commit is the same as a transaction from the DB perspective. But is this accurate?
DB: MySQL
You are right, with autocommit every statement is wrapped in transaction. If your service methods are executing multiple sql statements, it would be good to wrap them into a transaction. Take a look at this answer for more details, and here is a nice blog post on the subject.
And to answer your question, yes, transactions do add performance overhead, but in your specific case, you will not notice the difference since you already have autocommit enabled, unless you have long running statements in service methods, which will cause longer locks on tables participating in transactions. If you just wrap your multiple statements inside a transaction, you will get one transaction (instead of transaction for every individual statement), as pointed here ("A session that has autocommit enabled can perform a multiple-statement transaction by starting it with an explicit START TRANSACTION or BEGIN statement and ending it with a COMMIT or ROLLBACK statement") and you will achieve atomicity on a service method level...
At the end, I would go with your solution, if that makes sense from the perspective of achieving atomicity on a service method level (which I think that you want to achieve), but there are + and - effects on performance, depending on your queries, requests/s etc...
Yes, they can add overhead. The extra "bookkeeping" required to isolate transactions from each other can become significant, especially if the transactions are held open for a long time.
The short answer is that it depends on your table type. If you're using MyISAM, the default, there are no transactions really, so there should be no effect on performance.
But you should use them anyway. Without transactions, there is no demarcation of work. If you upgrade to InnoDB or a real database like PostgreSQL, you'll want to add these transactions to your service methods anyway, so you may as well make it a habit now while it isn't costing you anything.
Besides, you should already be using a transactional store. How do you clean up if a service method fails currently? If you write some information to the database and then your service method throws an exception, how do you clean out that incomplete or erroneous information? If you were using transactions, you wouldn't have to—the database would throw away rolled back data for you. Or what do you do if I'm halfway through a method and another request comes in and finds my half-written data? Is it going to blow up when it goes looking for the other half that isn't there yet? A transactional data store would handle this for you: your transactions would be isolated from each other, so nobody else could see a partially written transaction.
Like everything with databases, the only definitive answer will come from testing with realistic data and realistic loads. I recommend that you do this always, no matter what you suspect, because when it comes to databases very different code paths get activated when the data are large versus when they are not. But I strongly suspect the cost of using transactions even with InnoDB is not great. After all, these systems are heavily used constantly, every day, by organizations large and small that depend on transactions performing well. MVCC adds very little overhead. The benefits are vast, the costs are low—use them!
I am developing some websites that need to interact with a database. I will not bring here a complicated example. My question actually comes down to: Is a MySQL procedure thread safe? If one client on my site triggers a procedure, can I assume it is atomic, or could it interfere with another request from another user?
Depends on if you're using SQL transactions. Its possible, without the appropriate use of transactions and the actual serialization level, that a procedure can expose some data in a write call, for instance, that is visible to other queries / procedures before the complete procedure has completed.
in short: a given procedure will only be atomic if you use the appropriate transaction level
The database will handle concurrency for you. This is normally done via transactions - any set of statements within a transaction is considered atomic and isolated from other processes. In some databases, a stored procedure will be in an implicit transaction (so you don't need to declare one) - read the documentation for your RDBMS.
Sometimes this will mean that records are locked while another process tries to use them.
You will need to write your application so it can detect such occurrences and retry.
It really depends on how your server is configured to use transactions. There are tradeoff to consider depending on how your data is used and whether or not dirty, non-repeatable, or phantom reads are acceptable for your application.
Yes.
It's the DB's job to ensure thread safety among its worker threads, and it's your job to ensure thread safety among your application threads. Since there's a separation between the DB server, and your application, you don't need to worry about thread safety in this case. MySQL's data locking mechanisms will prevent you from corrupting the data in the DB due to simultaneous access from multiple threads in your own app.
Thread safety is more about modifying data in-memory, that is also shared among multiple threads within your app. Since the DB server is its own, separate application, it basically protects you from the scenario you've outlined above.
i am using a toplink with struts 2 and toplink for a high usage app, the app always access a single table with multiple read and writes per second. This causes a lock_wait_timeout error and the transaction rolls back, causing the data just entered to disappear from the front end. (Mysql's autocommit has been set to one). The exception has been caught and sent to an error page in the app but still a rollback occurs (it has to be a toplink exception as mysql does not have the rollback feature turned on). The raw data files, ibdata01 show the entry in it when opened in an editor. As this happend infreqeuntly have not been able to replicate in test conditions.
Can anyone be kind enough to provide some sort of way out of this dilemma? What sort of approach should such a high access (constant read and writes from the same table all the time)? Any help would be greatly appreciated.
What is the nature of your concurrent reads/updates? Are you updating the same rows constantly from different sessions? What do you expect to happen when two sessions update the same row at the same time?
If it is just reads conflicting with updates, consider reducing your transaction isolation on your database.
If you have multiple write conflicting, then you may consider using pessimistic locking to ensure each transaction succeeds. But either way, you will have lot of contention, so may reconsider your data model or application's usage of the data.
See,
http://en.wikibooks.org/wiki/Java_Persistence/Locking
lock_wait_timeouts are a fact of life for transactional databases. the normal response should usually be to trap the error and attempt to re-run the transaction. not many developers seem to understand this, so it bears repeating: if you get a lock_wait_timeout error and you still want to commit the transaction, then run it again.
other things to look out for are:
persistent connections and not
explicitly COMMIT'ing your
transactions leads to long-running
transactions that result in
unnecessary locks.
since you
have auto-commit off, if you log in
from the mysql CLI (or any other
interactive query tool) and start
running queries you stand a
significant chance of locking rows
and not releasing them in a timely
manner.