In this case, Peter needs to wait until John finishes his work and releases the exclusive lock. This row already has an exclusive lock for John. It tries to take a shared lock to read the row.It acquires an intent shared (IS) lock on the customer table and the page that contains the record as per the where clause.It prevents any other user from modifying the row data until process A releases its lock. It further takes an exclusive (X) lock on the row that John wants to update.It takes an intent exclusive (IX) lock on the customer table and page that contains the record.In this case, SQL Server uses the following locks for both John and Peter. At the same time, Peter wants to retrieve the value for the customer having 1.John wants to update the records for the customer having 1.Suppose you have two users, John and Peter who are connected to the customer database. These locks can be acquired on the key, table, row, page and database level. Various lock types include: exclusive lock(X), shared lock(S), update lock (U), intent lock (I), schema lock (SCH) and bulk update lock (BU). To follow the ACID properties, SQL Server uses locking mechanisms, constraints and write-ahead logging. The image below describes the ACID properties in a relational database. In this case, your database should follow the Atomicity, Consistency, Isolation, Durability (ACID) properties in order to be consistent, reliable and protect data integrity. Multiple users are likely performing the same activity at the same time. For example, suppose you are supporting the database for an online shopping portal where you receive new orders from customers around the clock. SQL Server is a highly transactional database. In this article, we’ll explore SQL Server deadlocks and the best ways to avoid them. For DBAs just starting out, this might come as a shock. Suppose you updated a transaction and SQL Server reported the following deadlock message. Database professionals are routinely confronted with database performance issues like improper indexing and poorly written code in production SQL instances.
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