Alternative for UPDATE with JOIN

Translation specification for UPDATE statement with WHERE and JOIN clauses

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Description

The pattern UPDATE FROM is used to update data based on data from other tables. This SQLServer documentation provides a simple sample.

Review the following SQL Server syntax from the documentation.

SQL Server Syntax

UPDATE [table_name] 
SET column_name = expression [, ...]
[FROM <table_source> [, ...]]
[WHERE <search_condition>]
[OPTION (query_hint)]

table_name: The table or view you are updating.
SET: Specifies the columns and their new values. The SET clause assigns a new value (or expression) to one or more columns.
FROM: Used to specify one or more source tables (like a join). It helps define where the data comes from to perform the update.
WHERE: Specifies which rows should be updated based on the condition(s). Without this clause, all rows in the table would be updated.
OPTION (query_hint): Specifies hints for query optimization.

Snowflake syntax

The Snowflake syntax can also be reviewed in the Snowflake documentation.

Snowflake does not support JOINs in UPDATE clause.

UPDATE <target_table>
       SET <col_name> = <value> [ , <col_name> = <value> , ... ]
        [ FROM <additional_tables> ]
        [ WHERE <condition> ]

Required parameters

target_table:Specifies the table to update.
col_name:Specifies the name of a column in target_table. Do not include the table name. E.g., UPDATE t1 SET t1.col = 1 is invalid.
value:Specifies the new value to set in col_name.

Optional parameters

FROM`` additional_tables: Specifies one or more tables to use for selecting rows to update or for setting new values. Note that repeating the target table results in a self-join.
WHERE`` condition:The expression that specifies the rows in the target table to update. Default: No value (all rows of the target table are updated)

Translation Summary

SQL Server JOIN type

Snowflake Best Alternative

Single INNER JOIN

Use the target table in the FROM clause to emulate an INNER JOIN.

Multiple INNER JOIN

Use the target table in the FROM clause to emulate an INNER JOIN.

Multiple INNER JOIN + Agregate condition

Use subquery + IN Operation

Single LEFT JOIN

Use subquery + IN Operation

Multiple LEFT JOIN

Use Snowflake UPDATE reordering the statements as needed. UPDATE [target_table_name]

SET [all_set_statements]

FROM [all_left_join_tables_separated_by_comma]

WHERE [all_clauses_into_the_ON_part]

Multiple RIGHT JOIN

Use Snowflake UPDATE reordering the statements as needed. UPDATE [target_table_name]

SET [all_set_statements]

FROM [all_right_join_tables_separated_by_comma]

WHERE [all_clauses_into_the_ON_part]

Single RIGHT JOIN

Use the table in the FROM clause and add filters in the WHERE clause as needed.

Note-1: Simple JOIN may use the table in the FROM clause and add filters in the WHERE clause as needed.

Note-2: Other approaches may include (+) operand to define the JOINs.

Sample Source Patterns

Setup data

CREATE TABLE Orders (
    OrderID INT PRIMARY KEY,
    CustomerID INT,
    ProductID INT,
    Quantity INT,
    OrderDate DATE
);

CREATE TABLE Customers (
    CustomerID INT PRIMARY KEY,
    CustomerName VARCHAR(100)
);

CREATE TABLE Products (
    ProductID INT PRIMARY KEY,
    ProductName VARCHAR(100),
    Price DECIMAL(10, 2)
);

CREATE OR REPLACE TABLE Orders (
    OrderID INT PRIMARY KEY,
    CustomerID INT,
    ProductID INT,
    Quantity INT,
    OrderDate DATE
)
COMMENT = '{ "origin": "sf_sc", "name": "snowconvert", "version": {  "major": 0,  "minor": 0,  "patch": "0" }, "attributes": {  "component": "transact",  "convertedOn": "11/12/2024",  "domain": "test" }}'
;

CREATE OR REPLACE TABLE Customers (
    CustomerID INT PRIMARY KEY,
    CustomerName VARCHAR(100)
)
COMMENT = '{ "origin": "sf_sc", "name": "snowconvert", "version": {  "major": 0,  "minor": 0,  "patch": "0" }, "attributes": {  "component": "transact",  "convertedOn": "11/12/2024",  "domain": "test" }}'
;

CREATE OR REPLACE TABLE Products (
    ProductID INT PRIMARY KEY,
    ProductName VARCHAR(100),
    Price DECIMAL(10, 2)
)
COMMENT = '{ "origin": "sf_sc", "name": "snowconvert", "version": {  "major": 0,  "minor": 0,  "patch": "0" }, "attributes": {  "component": "transact",  "convertedOn": "11/12/2024",  "domain": "test" }}'
;

Data Insertion for samples


-- Insert Customer Data
INSERT INTO Customers (CustomerID, CustomerName) VALUES (1, 'John Doe');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (2, 'Jane Smith');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (3, 'Alice Johnson');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (4, 'Bob Lee');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (5, 'Charlie Brown');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (6, 'David White');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (7, 'Eve Black');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (8, 'Grace Green');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (9, 'Hank Blue');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (10, 'Ivy Red');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (11, 'Jack Grey');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (12, 'Kim Yellow');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (13, 'Leo Purple');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (14, 'Mona Pink');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (15, 'Nathan Orange');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (16, 'Olivia Cyan');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (17, 'Paul Violet');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (18, 'Quincy Brown');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (19, 'Rita Silver');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (20, 'Sam Green');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (21, 'Tina Blue');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (22, 'Ursula Red');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (23, 'Vince Yellow');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (24, 'Wendy Black');
INSERT INTO Customers (CustomerID, CustomerName) VALUES (25, 'Xander White');

-- Insert Product Data
INSERT INTO Products (ProductID, ProductName, Price) VALUES (1, 'Laptop', 999.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (2, 'Smartphone', 499.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (3, 'Tablet', 299.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (4, 'Headphones', 149.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (5, 'Monitor', 199.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (6, 'Keyboard', 49.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (7, 'Mouse', 29.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (8, 'Camera', 599.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (9, 'Printer', 99.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (10, 'Speaker', 129.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (11, 'Charger', 29.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (12, 'TV', 699.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (13, 'Smartwatch', 199.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (14, 'Projector', 499.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (15, 'Game Console', 399.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (16, 'Speaker System', 299.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (17, 'Earphones', 89.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (18, 'USB Drive', 15.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (19, 'External Hard Drive', 79.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (20, 'Router', 89.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (21, 'Printer Ink', 49.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (22, 'Flash Drive', 9.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (23, 'Gamepad', 34.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (24, 'Webcam', 49.99);
INSERT INTO Products (ProductID, ProductName, Price) VALUES (25, 'Docking Station', 129.99);

-- Insert Orders Data
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (1, 1, 1, 2, '2024-11-01');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (2, 2, 2, 1, '2024-11-02');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (3, 3, 3, 5, '2024-11-03');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (4, 4, 4, 3, '2024-11-04');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (5, NULL, 5, 7, '2024-11-05');  -- NULL Customer
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (6, 6, 6, 2, '2024-11-06');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (7, 7, NULL, 4, '2024-11-07');  -- NULL Product
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (8, 8, 8, 1, '2024-11-08');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (9, 9, 9, 3, '2024-11-09');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (10, 10, 10, 2, '2024-11-10');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (11, 11, 11, 5, '2024-11-11');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (12, 12, 12, 2, '2024-11-12');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (13, NULL, 13, 8, '2024-11-13');  -- NULL Customer
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (14, 14, NULL, 4, '2024-11-14');  -- NULL Product
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (15, 15, 15, 3, '2024-11-15');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (16, 16, 16, 2, '2024-11-16');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (17, 17, 17, 1, '2024-11-17');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (18, 18, 18, 4, '2024-11-18');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (19, 19, 19, 3, '2024-11-19');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (20, 20, 20, 6, '2024-11-20');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (21, 21, 21, 3, '2024-11-21');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (22, 22, 22, 5, '2024-11-22');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (23, 23, 23, 2, '2024-11-23');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (24, 24, 24, 4, '2024-11-24');
INSERT INTO Orders (OrderID, CustomerID, ProductID, Quantity, OrderDate) VALUES (25, 25, 25, 3, '2024-11-25');

Case 1: Single `INNER JOIN` Update

For INNER JOIN, if the table is used inside the FROM statements, it automatically turns into INNER JOIN. Notice that there are several approaches to support JOINs in UPDATE statements in Snowflake. This is one of the simplest patterns to ensure readability.

SQL Server

UPDATE Orders
SET Quantity = 10
FROM Orders O
INNER JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE C.CustomerName = 'John Doe';

-- Select the changes
SELECT Orders.CustomerID, Orders.Quantity, Customers.CustomerName
FROM Orders, Customers
WHERE Orders.CustomerID = Customers.CustomerID
AND Customers.CustomerName = 'John Doe';

Snowflake

UPDATE Orders O
SET O.Quantity = 10
FROM 
  Customers C
WHERE 
  C.CustomerName = 'John Doe'
  AND O.CustomerID = C.CustomerID;


-- Select the changes
SELECT Orders.CustomerID, Orders.Quantity, Customers.CustomerName
FROM Orders, Customers
WHERE Orders.CustomerID = Customers.CustomerID
AND Customers.CustomerName = 'John Doe';

Other approaches:

MERGE INTO

MERGE INTO Orders O
USING Customers C
ON O.CustomerID = C.CustomerID
WHEN MATCHED AND C.CustomerName = 'John Doe' THEN
  UPDATE SET O.Quantity = 10;

IN Operation

UPDATE Orders O
SET O.Quantity = 10
WHERE O.CustomerID IN 
  (SELECT CustomerID FROM Customers WHERE CustomerName = 'John Doe');

Case 2: Multiple `INNER JOIN` Update

SQL Server

UPDATE Orders
SET Quantity = 5
FROM Orders O
INNER JOIN Customers C ON O.CustomerID = C.CustomerID
INNER JOIN Products P ON O.ProductID = P.ProductID
WHERE C.CustomerName = 'Alice Johnson' AND P.ProductName = 'Tablet';

-- Select the changes
SELECT Orders.CustomerID, Orders.Quantity, Customers.CustomerName FROM Orders, Customers
WHERE Orders.CustomerID = Customers.CustomerID
AND Customers.CustomerName = 'Alice Johnson';

Snowflake

UPDATE Orders O
SET O.Quantity = 5
FROM Customers C, Products P
WHERE O.CustomerID = C.CustomerID
  AND C.CustomerName = 'Alice Johnson'
  AND P.ProductName = 'Tablet'
  AND O.ProductID = P.ProductID;

-- Select the changes
SELECT Orders.CustomerID, Orders.Quantity, Customers.CustomerName FROM Orders, Customers
WHERE Orders.CustomerID = Customers.CustomerID
AND Customers.CustomerName = 'Alice Johnson';

Case 3: Multiple `INNER JOIN` Update with Aggregate Condition

SQL Server

UPDATE Orders
SET Quantity = 6
FROM Orders O
INNER JOIN Customers C ON O.CustomerID = C.CustomerID
INNER JOIN Products P ON O.ProductID = P.ProductID
WHERE C.CustomerID IN (SELECT CustomerID FROM Orders WHERE Quantity > 3)
AND P.Price < 200;

SELECT C.CustomerID, C.CustomerName, O.Quantity, P.Price FROM Orders O
INNER JOIN Customers C ON O.CustomerID = C.CustomerID
INNER JOIN Products P ON O.ProductID = P.ProductID
WHERE C.CustomerID IN (SELECT CustomerID FROM Orders WHERE Quantity > 3)
AND P.Price < 200;

Snowflake

UPDATE Orders O
SET Quantity = 6
WHERE O.CustomerID IN (SELECT CustomerID FROM Orders WHERE Quantity > 3)
AND O.ProductID IN (SELECT ProductID FROM Products WHERE Price < 200);

-- Select changes
SELECT C.CustomerID, C.CustomerName, O.Quantity, P.Price FROM Orders O
INNER JOIN Customers C ON O.CustomerID = C.CustomerID
INNER JOIN Products P ON O.ProductID = P.ProductID
WHERE C.CustomerID IN (SELECT CustomerID FROM Orders WHERE Quantity > 3)
AND P.Price < 200;

Case 4: Single `LEFT JOIN` Update

SQL Server

UPDATE Orders
SET Quantity = 13
FROM Orders O
LEFT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE C.CustomerID IS NULL AND O.ProductID = 13;

-- Select the changes
SELECT * FROM orders
WHERE CustomerID IS NULL;

Snowflake

UPDATE Orders
SET Quantity = 13
WHERE OrderID IN (
  SELECT O.OrderID
  FROM Orders O
  LEFT JOIN Customers C ON O.CustomerID = C.CustomerID
  WHERE C.CustomerID IS NULL AND O.ProductID = 13
);


-- Select the changes
SELECT * FROM orders
WHERE CustomerID IS NULL;

This approach in Snowflake will not work because it does not update the necessary rows:

UPDATE Orders O SET O.Quantity = 13 FROM Customers C WHERE O.CustomerID = C.CustomerID AND C.CustomerID IS NULL AND O.ProductID = 13;

Case 5: Multiple `LEFT JOIN` and `RIGHT JOIN` Update

This is a more complex pattern. To translate multiple LEFT JOINs, please review the following pattern:

LEFT JOIN and RIGHT JOIN will depend on the order in the FROM clause.

UPDATE [target_table_name]
SET [all_set_statements]
FROM [all_left_join_tables_separated_by_comma]
WHERE [all_clauses_into_the_ON_part]

SQL Server

UPDATE Orders
SET
    Quantity = C.CustomerID
FROM Orders O
LEFT JOIN Customers C ON C.CustomerID = O.CustomerID
LEFT JOIN Products P ON P.ProductID = O.ProductID
WHERE C.CustomerName = 'Alice Johnson'
  AND P.ProductName = 'Tablet';

SELECT O.OrderID, O.CustomerID, O.ProductID, O.Quantity, O.OrderDate
FROM Orders O
LEFT JOIN Customers C ON C.CustomerID = O.CustomerID
LEFT JOIN Products P ON P.ProductID = O.ProductID
WHERE C.CustomerName = 'Alice Johnson'
  AND P.ProductName = 'Tablet';

Snowflake

UPDATE Orders O
SET O.Quantity = C.CustomerID
FROM Customers C, Products P
WHERE O.CustomerID = C.CustomerID
  AND C.CustomerName = 'Alice Johnson'
  AND P.ProductName = 'Tablet'
  AND O.ProductID = P.ProductID;

  SELECT O.OrderID, O.CustomerID, O.ProductID, O.Quantity, O.OrderDate
FROM Orders O
LEFT JOIN Customers C ON C.CustomerID = O.CustomerID
LEFT JOIN Products P ON P.ProductID = O.ProductID
WHERE C.CustomerName = 'Alice Johnson'
  AND P.ProductName = 'Tablet';

Case 6: Mixed `INNER JOIN` and `LEFT JOIN` Update

SQL Server

UPDATE Orders
SET Quantity = 4
FROM Orders O
INNER JOIN Products P ON O.ProductID = P.ProductID
LEFT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE C.CustomerID IS NULL AND P.ProductName = 'Monitor';

-- Select changes
SELECT O.CustomerID, C.CustomerName, O.Quantity FROM Orders O
INNER JOIN Products P ON O.ProductID = P.ProductID
LEFT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE C.CustomerID IS NULL AND P.ProductName = 'Monitor';

Snowflake

UPDATE Orders O
SET Quantity = 4
WHERE O.ProductID IN (SELECT ProductID FROM Products WHERE ProductName = 'Monitor')
AND O.CustomerID IS NULL;

-- Select changes
SELECT O.CustomerID, C.CustomerName, O.Quantity FROM Orders O
INNER JOIN Products P ON O.ProductID = P.ProductID
LEFT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE C.CustomerID IS NULL AND P.ProductName = 'Monitor';

Case 7: Single `RIGHT JOIN` Update

SQL Server

UPDATE O
SET O.Quantity = 1000
FROM Orders O
RIGHT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE C.CustomerName = 'Alice Johnson';

-- Select changes 
SELECT
    O.OrderID,
    O.CustomerID,
    O.ProductID,
    O.Quantity,
    O.OrderDate,
    C.CustomerName
FROM
    Orders O
RIGHT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE
    C.CustomerName = 'Alice Johnson';

Snowflake

UPDATE Orders O
SET O.Quantity = 1000
FROM Customers C
WHERE O.CustomerID = C.CustomerID
  AND C.CustomerName = 'Alice Johnson';


  -- Select changes 
SELECT
    O.OrderID,
    O.CustomerID,
    O.ProductID,
    O.Quantity,
    O.OrderDate,
    C.CustomerName
FROM
    Orders O
RIGHT JOIN Customers C ON O.CustomerID = C.CustomerID
WHERE
    C.CustomerName = 'Alice Johnson';

Know Issues

Since UPDATE in Snowflake does not allow the usage of JOINs directly, there may be cases that do not match the patterns described.

Last updated 5 months ago

hashtagDescription

hashtagSQL Server Syntax

hashtagSnowflake syntax

hashtagTranslation Summary

hashtagSample Source Patterns

hashtagSetup data

hashtagCase 1: Single INNER JOIN Update

hashtagSQL Server

hashtagSnowflake

hashtagCase 2: Multiple INNER JOIN Update

hashtagSQL Server

hashtagSnowflake

hashtagCase 3: Multiple INNER JOIN Update with Aggregate Condition

hashtagSQL Server

hashtagSnowflake

hashtagCase 4: Single LEFT JOIN Update

hashtagSQL Server

hashtagSnowflake

hashtagCase 5: Multiple LEFT JOIN and RIGHT JOIN Update

hashtagSQL Server

hashtagSnowflake

hashtagCase 6: Mixed INNER JOIN and LEFT JOIN Update

hashtagSQL Server

hashtagSnowflake

hashtagCase 7: Single RIGHT JOIN Update

hashtagSQL Server

hashtagSnowflake

hashtagKnow Issues

Description

SQL Server Syntax

Snowflake syntax

Translation Summary

Sample Source Patterns

Setup data

Case 1: Single `INNER JOIN` Update

SQL Server

Snowflake

Case 2: Multiple `INNER JOIN` Update

SQL Server

Snowflake

Case 3: Multiple `INNER JOIN` Update with Aggregate Condition

SQL Server

Snowflake

Case 4: Single `LEFT JOIN` Update

SQL Server

Snowflake

Case 5: Multiple `LEFT JOIN` and `RIGHT JOIN` Update

SQL Server

Snowflake

Case 6: Mixed `INNER JOIN` and `LEFT JOIN` Update

SQL Server

Snowflake

Case 7: Single `RIGHT JOIN` Update

SQL Server

Snowflake

Know Issues