But it only guarantees, that if the transactions execute, their observable effects will be as if they both executed sequentially i.e. It is very easy to make wrong assumption, that SERIALIZABLE level guarantees that our SQL code will be executed sequentially. This is very simple scenario from the application point of view: to read some data, update the data, do some things and have all of this wrapped with a transaction. I am writing about this for the following reasons: The lock is not taken in this place with READ COMMITED which is the default level. The problem is caused by the lock taken witch SELECT instruction having SERIALIZABLE isolation level set. This is deadlock which fortunately is detected by the engine. Conversely, the second’s tab UPDATE waits for the lock taken by the SELECT in the first tab. This is because when the first tab reaches its UPDATE it needs to take writer lock, but it is locked by the SELECT in the second tab. We observe the first tab waits more than 10 seconds. Now when the first session passes waitfor and comes to UPDATE it needs to take a writer lock and waits (I am purposely using generic vocabulary instead of SQL Server specific one - these locks inside database engine all have their names). When we execute the code again in another session we have one more reader lock taken on the table. What happens here is that SQL Server takes a reader lock on the table after executing the SELECT. In real application the execution flow is much more `polluted` with an ORM calls, but my simplified code from above just tries to model common scenario of reads followed by writes. I would advise having a closer look at the instructions wrapped in transaction. By setting SERIALIZABLE level we do not automatically switch the behavior of the code wrapped with transaction to the behavior of lock statement known from C# (technically lock is a monitor). For application developer it is very easy to be tricked into thinking that having set SERIALIZABLE isolation level we magically make sequential execution of our SQL code. This situation occurred in a web application where concurrent execution of methods is pretty common. Process and has been chosen as the deadlock victim. Transaction (Process ID 54) was deadlocked on lock resources with another After waiting more than 10 seconds, which is the delay in code, we will observe an error message on the first tab: Let’s put the code in both tabs and then execute one tab and the second tab. But the point is that the transaction does both SELECT and UPDATE on the same table having those time consuming things in between. These are emulated with WAITFOR instruction. The following code tries to resemble application level function which does a bunch of possibly time consuming things. Then execute the following statement to increase isolation level in both tabs: Please consider, that each tab has its own connection. Now let’s open SSMS (BTW, since version 2016 there is an installer decoupled from SQL Server available here) with two separate tabs. We can replay this condition with the simplest table possible: This provides all the information we need to identify the root cause of the deadlock and take necessary steps to resolve the issue.Today I am demonstrating a deadlock condition which I came across after I had accidentally increased isolation level to serializable. You can save the Deadlock xml as xdl to view the Deadlock Diagram. SELECT CAST(event_data AS XML) AS įROM sys.fn_xe_telemetry_blob_target_read_file('dl', These queries identifies the deadlock event time as well as the deadlock event details. Next logical question is, what caused this deadlock. So we have identified Deadlock happened in the database through our Application Insights. | communication buffer resources with another process and has been chosen as the deadlock victim. Transaction (Process ID 166) was deadlocked on lock Customize the degree of parallelism, or set it to 1 to execute in sequence. Log App Concurrency Control Behaviorįor each loops execute in parallel by default. The solution we implemented to alleviate this problem is to run this process in Sequence instead of parallel threads. That’s the root cause of the problem and we didn’t want to remove the explicit Transaction. Our process high percentage of shared data and we wanted to ensure the consistency, so we had Explicit Transactions in our Stored procedure calls. In Ideal world, Database should be able to handle numerous concurrent functions without deadlocks. The problem was Azure Functions invoked Database Calls which caused Deadlocks. So Logic App invoked several concurrent threads which in turn invoked several Azure Functions. Recently we were working with Azure Logic Apps to invoke Azure Functions.īy Default, Logic App runs parallel threads and we didn’t explicitly control the concurrency and left the default values.
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