Cross Apply vs. Inner Join: When Does Cross Apply Offer Superior Efficiency for Large Datasets?

Cross Apply vs. Inner Join: Performance Optimization for Large Datasets

Cross apply proves particularly useful when dealing with intricate table relationships or operations not easily achievable with inner joins. It generates rows from the right-hand table for every row in the left-hand table.

Although both cross apply and inner join can yield similar results, cross apply often demonstrates superior efficiency, particularly when processing extensive datasets and employing partitioning or paging.

A key advantage of cross apply is its ability to function without a user-defined function (UDF) as the right-hand table, offering flexibility in various situations.

To highlight the performance disparity, let's examine a scenario with a "master" table containing 20 million records. An inner join query retrieving the last three rows for each record in a smaller "t" table takes approximately 30 seconds:

<code class="language-sql">WITH q AS
        (
        SELECT  *, ROW_NUMBER() OVER (ORDER BY id) AS rn
        FROM    master
        ),
        t AS 
        (
        SELECT  1 AS id
        UNION ALL
        SELECT  2
        )
SELECT  *
FROM    t
JOIN    q
ON      q.rn <= t.id</code>

However, an equivalent cross apply query completes almost instantly:

<code class="language-sql">WITH    t AS 
        (
        SELECT  1 AS id
        UNION ALL
        SELECT  2
        )
SELECT  *
FROM    t
CROSS APPLY
        (
        SELECT  TOP (t.id) m.*
        FROM    master m
        ORDER BY
                id
        ) q</code>

This dramatic performance difference underscores the efficiency benefits of cross apply when handling complex data manipulations within large datasets.

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