If you want to get rid of these phantom records, you have to use the Isolation Level Serializable, which is the most restrictive one. In every discussed Isolation Level so far, you are also always able to get so-called Phantom Records – records that can appear and disappear in your result set. Means nobody else can make changes to your read data, and you are getting Repeatable Reads for your transaction. In Repeatable Read SQL Server holds the S locks until you end your transaction with a COMMIT or ROLLBACK. If you want to avoid Non Repeatable Reads, you can use the Isolation Level Repeatable Read. In Read Committed you can have so-called Non Repeatable Reads, because someone else can change the data, when you are reading the data twice in your transaction. And as you will see later, even NOLOCK can block… But that’s not the preferred way to handle blocking. I’m seeing a lot of cases during my consulting engagements where people are using Read Uncommitted or the NOLOCK query hint to get rid of blocking situations in SQL Server. Just think about, what happens if the uncommitted transaction is aborded after you have read the data: you have data in your hand that doesn’t even logically existed in your database. ![]() ![]() It’s blazingly fast (no one else can block you), but on the other hand it’s very dangerous, because it’s uncommitted data. Read Uncommitted just means you are able to read dirty data – data that isn’t yet committed. When you don’t want that readers are acquiring S locks (which isn’t really recommended), you can use the Isolation Level Read Uncommitted. When you are reading row by row, you are acquiring and releasing the needed S locks row by row. By default SQL Server uses the Isolation Level Read Committed, which means SQL Server acquires a S lock, when you read a record, and and when the record was read, the S lock is released. Writers will always acquire X locks, and you can’t influence them. With the Transaction Isolation Level you can control now, how long a reader will hold its S locks. And both locks are incompatible to each other, means readers are blocking writers, and writers are blocking readers. Everytime when you change data, SQL Server has to acquire Exclusive Locks (X). Every time when you are reading data, SQL Server has to acquire Shared Locks (S). When we are looking on a high level view onto SQL Server, you have transactions that are reading data (SELECT queries), and you have transactions that are changing data (INSERT, UPDATE, DELETE, MERGE). I don’t want to go into the deep internals about every Transaction Isolation Level, but I want to give you a brief overview what every Isolation Level is doing internally, because we need that information for the subsequent sections of this blog posting. ![]() In the old pessimistic concurrency model, SQL Server supports 4 different Transaction Isolation Levels: Today I want to concentrate on the “old” one. SQL Server supports 2 kinds of concurrency models: the “old” pessimistic one, and the “new” optimistic one that was introduced with SQL Server 2005 – almost 9 years ago… When we are talking about locking & blocking in any relational database, we also have to talk about the various Transaction Isolation Levels that the DBMS supports (in our case – SQL Server). Have you ever tried starting a new transaction (without ever committing it) that acquires an exclusive lock the main table of your production database? Trust me: the performance and the throughput of your database will just die – in front of your eyes!!! So my Pro Tip to you: don’t try it □ When you have one bad query (maybe you are missing a very important index), the performance of your whole database can go down. Transaction Isolation Levels – What?Įverytime when I’m on customer side, and troubleshooting crazy SQL Server problems (or performing SQL Server Health Checks), the root cause sometimes lies in the locking/blocking behavior of the database. So let’s get started by first laying out the foundation about Transaction Isolation Levels in SQL Server. Key Range Locks are specific to Serializable!?. ![]() I mainly want to talk about the following topics: In todays blog posting I want to talk about myths & misconceptions about the various Transaction Isolation Levels that exists in SQL Server.
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