Tutorials
Practical T-SQL
Practical T-SQL
  • Practical T-SQL Pocket Guide For Beginners
  • Preface
    • Section I. A Note From The Author
    • Section II. Tutorial Overview
    • Section III. Running The Examples
    • Section IV. How To Report An Issue
    • Section V. Join The MSU Community On Discord
    • Section VI. Supplementary Material
  • Language Basics
    • Lesson 1. Obligatory Hello World
    • Lesson 2. Code Comments With T-SQL
    • Lesson 3. Basic Syntax
    • Lesson 4. Your First Query
    • Lesson 5. Filtering Data
    • Lesson 6. Sorting Data
    • Lesson 7. Complex Data Filtering
    • Lesson 8. Aliases
    • Lesson 9. String Functions
    • Lesson 10. Creating New Columns From Existing Data (Calculated Fields)
    • Lesson 11. Displaying Data Based On Conditions (Case Statement)
    • Lesson 12. Aggregate Functions
    • Lesson 13. Grouping And Summarizing Data
    • Lesson 14. Querying More Than One Table
    • Lesson 15. Combining Queries
    • Lesson 16. Subqueries
    • Lesson 17. Creating Data
    • Lesson 18. Updating Data
    • Lesson 19. Deleting Data
    • Lesson 20. Common Table Expressions (CTEs)
    • Lesson 21. Derived Tables
    • Lesson 22. Putting It All Together
  • Advanced Topics
    • Lesson 23. Selecting Unique Values
    • Lesson 24. Updating Data With A Join
    • Lesson 25. Data Types
    • Lesson 26. Casting Data Types
    • Lesson 27. Creating Tables
    • Lesson 28. Altering Tables
    • Lesson 29. Dropping Tables
    • Lesson 30. Variables
    • Lesson 31. Controlling Flow
    • Lesson 32. Looping
    • Lesson 33. Error Processing
    • Lesson 34. Temporary Tables
    • Lesson 35. Views
    • Lesson 36. Indexed Views
    • Lesson 37. User Defined Functions
    • Lesson 38. Stored Procedures
    • Lesson 39. BULK INSERT
    • Lesson 40. Loading Tables With MERGE
    • Lesson 41. Partitioning A Dataset
    • Lesson 42. Pivoting Data
    • Lesson 43. Dynamic SQL
    • Lesson 44. Cursors
  • Solutions To Real World Problems
    • Lesson 45. Listing All Tables In A SQL Server Database
    • Lesson 46. Listing All Columns In A SQL Server Database
    • Lesson 47. Pull Records From A Table At Random
    • Lesson 48. A Better Alternative To WITH (NOLOCK)
    • Lesson 49. Boost Performance When Calling A Stored Proc From SSIS
    • Lesson 50. Setting Up Queries For Ablation Testing
    • Lesson 51. Reduce Code And Save Time With Default Column Values
    • Lesson 52. Finding Duplicate Records In A Table
    • Lesson 53. Why You Cannot Have More Than One Clustered Index On A Table
    • Lesson 54. Converting Dates To YYYYMMDD
    • Lesson 55. Sending Notification Emails With T-SQL Without Using Hardcoded Email Addresses
    • Lesson 56. Troubleshooting Long Running Queries
    • Lesson 57. Loading Large CSVs Into Data Warehouse Staging Tables
    • Lesson 58. The Only Bloody Good Reason To Use Cursors
    • Lesson 59. Loading A Type II Slowly Changing Dimension With SQL Merge
    • Lesson 60. A Clearer Explanation Of The Parameters Of The Numeric Data Type
    • Lesson 61. Why You Cannot Join On Null Values
    • Lesson 62. A Deep Dive On How The Where Clause Functions
    • Lesson 63. Using HASHBYTES() To Compare Character Strings
    • Lesson 64. Using Pipe To Hash Multiple Columns For Matching
    • Lesson 65. Why People That Indent Code Drive Me Nuts
    • Lesson 66. How To Rapidly Stand Up A Data Warehouse From Scratch
    • Lesson 67. How To Pivot Data With T-SQL When Columns Are Not Predefined
    • Lesson 68. Prepopulating A Junk Dimension
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  1. Advanced Topics

Lesson 40. Loading Tables With MERGE

PreviousLesson 39. BULK INSERTNextLesson 41. Partitioning A Dataset

Last updated 3 years ago

The MERGE clause is the most powerful SQL clause known to man. With MERGE, you can take data from one table and load it into another table. Unlike INSERT INTO SELECT, MERGE gives you way more power in how you go about doing that.

With great power comes great complexity and a full explanation of SQL MERGE is FAR outside the scope of this tutorial.

The most common use case I have for MERGE is loading Type II slowly changing dimensions in data warehouses. I talk about this extensively in the section titled .

The process of using MERGE works like this.

  1. Identify the table you will load data into.

  2. Identify the table that you will use as the source of your data.

  3. Identify how records in those two tables are connected.

  4. Give instructions on what to do when records do not match.

  5. Give instructions on what to do when records do match.

Examples

A Basic MERGE Example

In [ ]:

USE demo

DROP TABLE IF EXISTS Person
DROP TABLE IF EXISTS PersonStageTable

CREATE TABLE Person(
PersonID BIGINT NOT NULL,
FirstName NVARCHAR(50) NULL,
LastName NVARCHAR(50) NULL,
SourceSystemKey NVARCHAR(50) NULL,
)

CREATE TABLE PersonStageTable(
PersonID BIGINT NOT NULL,
FirstName NVARCHAR(50) NULL,
LastName NVARCHAR(50) NULL,
SourceSystemKey NVARCHAR(50) NULL,
)

INSERT INTO Person(PersonID, FirstName, LastName, SourceSystemKey)
SELECT 1, 'Bob', 'Wakefield',1

INSERT INTO PersonStageTable(PersonID, FirstName, LastName, SourceSystemKey)
SELECT 1,'Bob','Johnson',1
UNION 
SELECT 2,'Sally','Ride',2

SELECT * FROM Person

SELECT * FROM PersonStageTable


--*****Merge example beings here.*****

MERGE Person AS target
USING (
SELECT
PersonID,
FirstName,
LastName,
SourceSystemKey
FROM PersonStageTable
) AS source
ON (target.SourceSystemKey = source.SourceSystemKey)

WHEN NOT MATCHED THEN
INSERT (
PersonID,
FirstName,
LastName,
SourceSystemKey
)
VALUES (
PersonID,
FirstName,
LastName,
SourceSystemKey
)

WHEN MATCHED THEN
UPDATE
SET
target.PersonID = source.PersonID,
target.FirstName = source.FirstName,
target.LastName = source.LastName,
target.SourceSystemKey = source.SourceSystemKey
;

SELECT * FROM Person

DROP TABLE Person
DROP TABLE PersonStageTable
Loading A Type II Slowly Changing Dimension With SQL Merge