How can I recreate a blocking process which uses FETCH API_CURSOR? - sql

My organization has recently had trouble with some SQL Server blocking processes. dbWarden has successfully reported blocking to us, but we often have the blocking SQL text reported as 'FETCH API_CURSOR'.
So, we're looking to alter the blocking alerts trigger in dbWarden to use sys.dm_exec_cursors and sys.dm_exec_sql_text to retrieve the text in the case where we find 'FETCH API_CURSOR' reported.
Trouble is, I cannot seem to come up with a way to recreate/simulate a blocking situation on our development server that will report as 'FETCH API_CURSOR'. I've started from the VB script here on SQL Authority to recreate the open cursor, but I cannot for the life of me figure out how to make it blocking.
I've seen many methods for recreating blocking transactions (open a transaction in one window, but do not commit/close, then try an update on same table in another), but not that would utilize FETCH API_CURSOR in a way that would allow us to successfully test. I'm somewhat at a loss here.
Has anyone had success in simulating blocking cursors in the past and can offer suggestions?

I'd suggest you to use Profiler tool to capture actual code that creates and fetches cursor. In this case, you'd see exactly what's going on in an application. It is not so difficult to reproduce similar blocking on a development server.
Let's say, one thread fetches rows from a cursor and another thread try to UPDATE same rows. See what's going on under the hood. Reading thread creates cursor to fetch result of SELECT back to an application. This technology is ancient and extremely slow and nowaday only some old (mostly) Java application use cursors for this purpose. Rows get fetched one-by-one, client is handling this process, so it takes time. During this time, reading thread holds shared locks on data it reads. It is by design, SQL Server is locker, it does use locks to function properly. If another thread tries to update a row that has been locked with shared lock, it get blocked. Because updating thread uses shared locks when searching rows for update, and tries to upgrade it to something more serious, but can't. For example, you can't upgrade your shared lock to U lock if another thread owns S lock on the same row. So I'd try to create a cursor, fetch several rows and tried to update in another tab. If you see difficulties, try to increase reading transaction serialization level.
But, seriously, I don't think you have to reproduce this or similar scenario on a development server. Stop use cursors for recordset fetching! Reads will be much faster and blocking issues will be reduced a lot. It's been a while since 1989 when cursors seen their great times. Client DB-access libraries evolved a lot, it is worth trying to pick up fruits of progress. Even in Java, it is a configuration option, use or not use them.
I apologize if cursor does get used on purpose, in this case. It is very unprobably but possible. I haven't seen such 'proper' cursor usage for ages! I'll be delighted to run into one more proper case.

Related

IBM i SQL - dump plan cache

I run heavy query on IBM i. First time it takes a long time, Subsequent times are much faster. It seems to be creating temporary index. How can I remove this index, so I can re-test like the first time?
Use the Visual Explain (VE) tool in the Run SQL Scripts component of ACS to see the differences between runs.
If indeed the issue is a system maintained temporary index (MTI), you can track it down via the schema's tooling in ACS and delete it if you so desire.
However, an MTI only gets deleted by the system when the system reboots (IPL).
So if you seeing differences without rebooting the server, I suspect the differences are caused by psuedo-closing. By default, once the DB see's the same query a few times (3 is the default), instead of hard closing it's cursors, it will psuedo-close them.
Again, VE will show "hard opens" and "pseudo opens".
To get the pseduo closed cursors to hard close, simply disconnect and reconnect.

How are transactions partitioned/isolated in SQLite?

I have been reading the SQLite documentation and also referencing code I have written previously but I don't seem to be able to find a definitive answer to what I imagine to be a rather simple question.
I would like to execute many (separate) compiled statements within a transaction, but child threads may also be creating transactions or just executing statements at the same time and I would not want them included in this particular transaction. Currently, I have a single database handle that I share between all threads.
So, my question is,
1) .. is it generally better to have some kind of semaphore around transactions to ensure they will not clash/collect with other statements being executed against a database handle. I already marshal writes to prevent problems with multithreaded issues with SQLite (although with WAL now it's very hard to unsettle it at all).
2) .. or are you expected to open multiple database connections and start/commit the transactions one per database connection if they will be concurrent?
Changes made in one database connection are invisible to all other database connections prior to commit.
So it seems a hybrid approach of having several connections open to the database provides adequate concurrency guarantees, trading off the expense of opening a new connection with the benefit of allowing multi-threaded write transactions.
A query sees all changes that are completed on the same database connection prior to the start of the query, regardless of whether or not those changes have been committed.
If changes occur on the same database connection after a query starts running but before the query completes, then it is undefined whether or not the query will see those changes.
If changes occur on the same database connection after a query starts running but before the query completes, then the query might return a changed row more than once, or it might return a row that was previously deleted.
For the purposes of the previous four items, two database connections that use the same shared cache and which enable PRAGMA read_uncommitted are considered to be the same database connection, not separate database connections.
Here is the SQLite information on isolation. Which is exceptionally useful to read and understand for this problem.

SQLite concurrent connections issue

I am working on a VB.NET application.
As per the nature of the application, One module has to monitor database (SQLite DB) each second. This Monitoring is done by simple select statement which run to check data against some condition.
Other Modules performs a select,Insert and Update statements on same SQLite DB.
on SQLite concurrent select statements are working fine, but I'm having hard time here to find out, why it is not allowing Inset and Update.
I understand it's a file based lock, but is there anyway to get it done?
each module, in fact statement opens and close the connection to DB.
I've restricted user to run single statement at a time by GUI design.
any Help will be appreciated.
If your database file is not on a network, you could allow a certain amount of read/write concurrency by enabling WAL mode.
But perhaps you should use only a single connection and do your own synchronization for all DB accesses.
You can use some locking mechanism to make sure the database works in a multithreading situation. Since your application is a read intensive one according to what you said, you can consider using a ReaderWriterLock or ReaderWriterLockSlim. (refer to here and here for more details)
If you have only one database, then creating just one instance of the lock is OK; if you have more than one database, each of them can be assigned a lock. Every time you do some read or write, enter the lock (by EnterReadLock() for ReaderWriterLockSlim, or by AcquireReaderLock() for ReaderWriterLock) before you do something, and after you're done exit the lock. Note that you can place the exit of the lock in a finally clause lest you forget to release it.
The strategy above is being used in our production applications. It's not so good as to use a single thread in your case because you have to take performance into account.

Run a SQL command in the event my connection is broken? (SQL Server)

Here's the sequence of events my hypothetical program makes...
Open a connection to server.
Run an UPDATE command.
Go off and do something that might take a significant amount of time.
Run another UPDATE that reverses the change in step 2.
Close connection.
But oh-no! During step 3, the machine running this program literally exploded. Other machines querying the same database will now think that the exploded machine is still working and doing something.
What I'd like to do, is just as the connection is opened, but before any changes have been made, tell the server that should this connection close for whatever reason, to run some SQL. That way, I can be sure that if something goes wrong, the closing update will run.
(To pre-empt the answer, I'm not looking for table/record locks or transactions. I'm not doing resource claims here.)
Many thanks, billpg.
I'm not sure there's anything built in, so I think you'll have to do some bespoke stuff...
This is totally hypothetical and straight off the top of my head, but:
Take the SPID of the connection you
opened and store it in some temp
table, with the text of the reversal
update.
Use an a background process (either
SSIS or something else) to monitor
the temp table and check that the
SPID is still present as an open connection.
If the connection dies then the background process can execute the stored revert command
If the connection completes properly then the SPID can be removed from the temp table so that the background process no longer reverts it when the connection closes.
Comments or improvements welcome!
I'll expand on my comment. In general, I think you should reconsider your approach. All database access code should open a connection, execute a query then close the connection where you rely on connection pooling to mitigate the expense of opening lots of database connections.
If it is the case that we are talking about a single SQL command whose rows on which it operates should not change, that is a problem that should be handled by the transaction isolation level. For that you might investigate the Snapshot isolation level in SQL Server 2005+.
If we are talking about a series of queries that are part of a long running transaction, that is more complicated and can be handled via storage of a transaction state which other connections read in order to determine whether they can proceed. Going down this road, you need to provide users with tools where they can cancel a long running transaction that might no longer be applicable.
Assuming it's even possible... this will only help you if the client machine explodes during the transaction. Also, there's a risk of false positives - the connection might get dropped for a few seconds due to network noise.
The approach that I'd take is to start a process on another machine that periodically pings the first one to check if it's still on-line, then takes action if it becomes unreachable.

ORM Support for Handling Deadlocks

Do you know of any ORM tool that offers deadlock recovery? I know deadlocks are a bad thing but sometimes any system will suffer from it given the right amount of load. In Sql Server, the deadlock message says "Rerun the transaction" so I would suspect that rerunning a deadlock statement is a desirable feature on ORM's.
I don't know of any special ORM tool support for automatically rerunning transactions that failed because of deadlocks. However I don't think that a ORM makes dealing with locking/deadlocking issues very different. Firstly, you should analyze the root cause for your deadlocks, then redesign your transactions and queries in a way that deadlocks are avoided or at least reduced. There are lots of options for improvement, like choosing the right isolation level for (parts) of your transactions, using lock hints etc. This depends much more on your database system then on your ORM. Of course it helps if your ORM allows you to use stored procedures for some fine-tuned command etc.
If this doesn't help to avoid deadlocks completely, or you don't have the time to implement and test the real fix now, of course you could simply place a try/catch around your save/commit/persist or whatever call, check catched exceptions if they indicate that the failed transaction is a "deadlock victim", and then simply recall save/commit/persist after a few seconds sleeping. Waiting a few seconds is a good idea since deadlocks are often an indication that there is a temporary peak of transactions competing for the same resources, and rerunning the same transaction quickly again and again would probably make things even worse.
For the same reason you probably would wont to make sure that you only try once to rerun the same transaction.
In a real world scenario we once implemented this kind of workaround, and about 80% of the "deadlock victims" succeeded on the second go. But I strongly recommend to digg deeper to fix the actual reason for the deadlocking, because these problems usually increase exponentially with the number of users. Hope that helps.
Deadlocks are to be expected, and SQL Server seems to be worse off in this front than other database servers. First, you should try to minimize your deadlocks. Try using the SQL Server Profiler to figure out why its happening and what you can do about it. Next, configure your ORM to not read after making an update in the same transaction, if possible. Finally, after you've done that, if you happen to use Spring and Hibernate together, you can put in an interceptor to watch for this situation. Extend MethodInterceptor and place it in your Spring bean under interceptorNames. When the interceptor is run, use invocation.proceed() to execute the transaction. Catch any exceptions, and define a number of times you want to retry.
An o/r mapper can't detect this, as the deadlock is always occuring inside the DBMS, which could be caused by locks set by other threads or other apps even.
To be sure a piece of code doesn't create a deadlock, always use these rules:
- do fetching outside the transaction. So first fetch, then perform processing then perform DML statements like insert, delete and update
- every action inside a method or series of methods which contain / work with a transaction have to use the same connection to the database. This is required because for example write locks are ignored by statements executed over the same connection (as that same connection set the locks ;)).
Often, deadlocks occur because either code fetches data inside a transaction which causes a NEW connection to be opened (which has to wait for locks) or uses different connections for the statements in a transaction.
I had a quick look (no doubt you have too) and couldn't find anything suggesting that hibernate at least offers this. This is probably because ORMs consider this outside of the scope of the problem they are trying to solve.
If you are having issues with deadlocks certainly follow some of the suggestions posted here to try and resolve them. After that you just need to make sure all your database access code gets wrapped with something which can detect a deadlock and retry the transaction.
One system I worked on was based on “commands” that were then committed to the database when the user pressed save, it worked like this:
While(true)
start a database transaction
Foreach command to process
read data the command need into objects
update the object by calling the command.run method
EndForeach
Save the objects to the database
If not deadlock
commit the database transaction
we are done
Else
abort the database transaction
log deadlock and try again
EndIf
EndWhile
You may be able to do something like with any ORM; we used an in house data access system, as ORM were too new at the time.
We run the commands outside of a transaction while the user was interacting with the system. Then rerun them as above (when you use did a "save") to cope with changes other people have made. As we already had a good ideal of the rows the command would change, we could even use locking hints or “select for update” to take out all the write locks we needed at the start of the transaction. (We shorted the set of rows to be updated to reduce the number of deadlocks even more)