Question
Answer and Explanation
In SQL, CROSS APPLY is an operator that allows you to invoke a table-valued function (TVF) for each row of an outer table expression. It's a powerful tool that can significantly enhance the flexibility and capabilities of your SQL queries. Unlike a regular JOIN, CROSS APPLY executes the table-valued function for each row processed from the outer table, providing a row-by-row evaluation context. This means that the inner table expression (the result of the TVF) can depend on values of the current outer table row.
Here’s a breakdown of its key characteristics and uses:
1. Row-by-Row Processing: CROSS APPLY processes the table-valued function for each row in the outer table. For each row, it applies the TVF and returns the result, making it ideal for processing data on a per-record basis.
2. Table-Valued Function Requirement: CROSS APPLY works exclusively with table-valued functions (TVFs). TVFs are user-defined functions that return a table as their output. This result set is then joined to the outer table row.
3. Dependency on Outer Table: The TVF can reference columns from the outer table. This dependency makes CROSS APPLY suitable for scenarios where the result of the inner table expression varies based on data in the outer table's current row.
4. Syntax: The basic syntax for CROSS APPLY is as follows:
SELECT outer_table.column1, inner_table.column2
FROM outer_table
CROSS APPLY table_valued_function(outer_table.column1);
Here, outer_table is the outer table expression, and table_valued_function is the function being invoked. The columns used within the function like outer_table.column1 are passed from the outer table. The returned result set is aliased as inner_table
5. When to Use CROSS APPLY:
- String manipulation: When you need to split a string field into multiple rows, or when you need to extract parts of a text based on criteria. - Hierarchical data: When traversing data that has a hierarchical structure, or data that contains nested arrays. - Complex logic: When your query involves complex processing or filtering that is difficult to achieve using regular join conditions. - JSON parsing: When dealing with JSON data structures where you need to extract specific values and create a relational table.
6. Difference from JOIN: Unlike a JOIN, which joins tables based on a condition, CROSS APPLY invokes a function for each row. A regular JOIN might not handle per-row logic as efficiently as CROSS APPLY.
7. Difference from OUTER APPLY: OUTER APPLY is similar to CROSS APPLY, except that it includes rows from the outer table even when the table-valued function returns no rows. This is analogous to a LEFT JOIN, while CROSS APPLY is analogous to an INNER JOIN.
Example Scenario:
Suppose you have a table named Customers with a column Orders storing comma-separated order IDs, and a function SplitOrderIds to split them:
CREATE FUNCTION SplitOrderIds (@orderIds VARCHAR(MAX))
RETURNS TABLE
AS
RETURN
(
SELECT value AS OrderId
FROM STRING_SPLIT(@orderIds, ',')
);
Then you can get each customer with their corresponding order id with a cross apply:
SELECT C.CustomerId, O.OrderId
FROM Customers C
CROSS APPLY SplitOrderIds(C.Orders) O;
In summary, CROSS APPLY is a powerful tool that provides a way to perform per-row processing using table-valued functions, making it a valuable operator for complex queries that involve conditional logic and data transformations within SQL.