Why Does My SQL Server 2012 Identity Column Skip Values?

SQL Server 2012 Identity Column Gaps: Troubleshooting and Solutions

SQL Server 2012's auto-incrementing identity columns sometimes exhibit unexpected behavior, skipping values—for instance, jumping from 6 directly to 1000 on the seventh insertion. This article explores the root causes and provides effective solutions.

Understanding the Issue

The irregular increment behavior stems from SQL Server 2012's introduction of sequences for identity value generation. This change affects how identity keys are assigned:

• Internal Value Caching: Sequences employ caching for performance optimization, pre-allocating a range of values.
• Bulk Inserts: Inserting multiple rows simultaneously can lead to gaps. The sequence allocates a block of numbers; unused values within that block create skips if not all are immediately consumed.

Resolving the Problem

Several approaches can address this issue and ensure sequential identity column increments:

Method 1: Deactivating Caching

To restore the pre-2012 behavior, disable caching using these commands:

<code class="language-sql">ALTER DATABASE [YourDatabase] SET SINGLE_USER WITH ROLLBACK IMMEDIATE;
GO
ALTER TABLE [TableWithIdentity] ADD PRIMARY KEY ([ColumnName]) WITH (IDENTITY(1, 1));
GO
ALTER DATABASE [YourDatabase] SET MULTI_USER;</code>

Method 2: Utilizing Trace Flag 272

Enable trace flag 272 to monitor each generated identity value. This detailed logging can pinpoint problems with the sequence caching mechanism.

Method 3: Employing a NO CACHE Sequence

Create a sequence generator explicitly configured without caching (NO CACHE). This guarantees strictly sequential increments, preventing gaps.

<code class="language-sql">CREATE SEQUENCE [YourSequenceName] AS INT
START WITH 1 INCREMENT BY 1 NO CACHE;
ALTER TABLE [TableWithIdentity] ADD PRIMARY KEY ([ColumnName]) WITH (IDENTITY(1, 1));
GO</code>

By implementing these solutions, you can maintain the expected behavior of your SQL Server 2012 identity columns, preventing data inconsistencies and gaps.

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