How to Fix “Violation of PRIMARY KEY Constraint” in SQL Server (Error 2627)

Tutorialsrack 26/01/2025 SQL Server

Introduction

When working with SQL Server, encountering the error “Violation of PRIMARY KEY constraint” (Error 2627) is a common issue. This error occurs when you try to insert a duplicate value into a column defined as a PRIMARY KEY, which must contain unique values. Resolving this error is crucial to maintaining data integrity and ensuring your database operates efficiently.

This guide will explore the causes of this error and provide actionable solutions, written in a clear, beginner-friendly tone to help you troubleshoot and resolve the issue effectively.

Possible Reasons for the Problem

Below are the key reasons why this error occurs:

1. Duplicate Data in the Source

When inserting data from a source table or file, the source may already contain duplicate records that violate the PRIMARY KEY constraint.

2. Application Logic Issues

Errors in application logic, such as re-attempting failed transactions or generating duplicate identifiers, can result in duplicate entries.

3. Lack of Proper Indexing or Constraints

Tables without sufficient constraints or proper indexing may inadvertently allow duplicate entries to be attempted during inserts or merges.

4. Manual Data Entry Errors

Human errors during manual data entry can lead to attempts to insert duplicate values.

5. Issues with Auto-Increment Columns

If the PRIMARY KEY is auto-incremented, inconsistencies in the identity seed values may cause duplicate key violations during inserts.

Possible Solutions with Explanations

Here are actionable solutions to resolve the error, tailored to address the root causes:

1. Check and Remove Duplicates from the Source Data

Action: Before inserting data, ensure the source data is clean and free from duplicates by running a query to identify duplicates:

SELECT PRIMARY_KEY_COLUMN, COUNT(*)
FROM SOURCE_TABLE
GROUP BY PRIMARY_KEY_COLUMN
HAVING COUNT(*) > 1;

Explanation: This query identifies duplicate records in the source table. Removing duplicates prevents violations during insertion.

Example:

DELETE FROM SOURCE_TABLE
WHERE PRIMARY_KEY_COLUMN IN (
    SELECT PRIMARY_KEY_COLUMN
    FROM (
        SELECT PRIMARY_KEY_COLUMN, ROW_NUMBER() OVER(PARTITION BY PRIMARY_KEY_COLUMN ORDER BY PRIMARY_KEY_COLUMN) AS RN
        FROM SOURCE_TABLE
    ) AS TEMP
    WHERE TEMP.RN > 1
);

2. Update Application Logic

Action: Review and revise application logic to ensure unique identifiers are generated for each record.

Explanation: Using GUIDs or sequences instead of manually generated keys ensures that duplicate keys are not created.

Example:

-- Using a Sequence
CREATE SEQUENCE seq_example
    START WITH 1
    INCREMENT BY 1;

INSERT INTO TARGET_TABLE (PRIMARY_KEY_COLUMN, OTHER_COLUMNS)
VALUES (NEXT VALUE FOR seq_example, 'value');

3. Add Constraints and Indexes to the Table

Action: Define UNIQUE constraints and indexes on the relevant columns to prevent duplicates:

ALTER TABLE TARGET_TABLE
ADD CONSTRAINT UNIQUE_KEY_CONSTRAINT UNIQUE (COLUMN_NAME);

Explanation: Constraints enforce data integrity at the database level, preventing duplicate entries during data operations.

4. Fix Identity Seed Value Issues

Action: If auto-increment columns are causing the issue, reseed the identity value:

DBCC CHECKIDENT ('TABLE_NAME', RESEED, NEW_SEED_VALUE);

Explanation: This ensures the next value for the identity column does not conflict with existing entries.

5. Use MERGE Instead of INSERT

Action: When inserting data from another table, use the MERGE statement to handle duplicates:

MERGE INTO TARGET_TABLE AS TARGET
USING SOURCE_TABLE AS SOURCE
ON TARGET.PRIMARY_KEY_COLUMN = SOURCE.PRIMARY_KEY_COLUMN
WHEN NOT MATCHED THEN
    INSERT (PRIMARY_KEY_COLUMN, OTHER_COLUMNS)
    VALUES (SOURCE.PRIMARY_KEY_COLUMN, SOURCE.OTHER_COLUMNS);

Explanation: The MERGE statement ensures that only non-duplicate rows are inserted.

Conclusion

The “Violation of PRIMARY KEY constraint” error (Error 2627) in SQL Server can be resolved by identifying its root cause and implementing the appropriate solution. From cleaning source data and fixing application logic to reseeding identity columns and adding constraints, each solution addresses specific scenarios. By proactively applying these methods, you can maintain data integrity and ensure seamless database operations.

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