Table JOIN - SQL Server to Aurora MySQL Migration Playbook
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Table JOIN

Feature compatibility Amazon SCT / Amazon DMS automation level Amazon SCT action code index Key differences


                              Four star feature compatibility


                              Four star automation level

Table Joins

Basic syntax compatible. FULL OUTER, APPLY, and ANSI SQL 89 outer joins will need to be rewritten.

SQL Server Usage

SQL Server supports the standard ANSI join types:

  • <Set A> CROSS JOIN <Set B> — Results in a Cartesian product of the two sets. Every JOIN starts as a Cartesian product.

  • <Set A> INNER JOIN <Set B> ON <Join Condition> — Filters the cartesian product to only the rows where the join predicate evaluates to TRUE.

  • <Set A> LEFT OUTER JOIN <Set B> ON <Join Condition> — Adds to the INNER JOIN all the rows from the reserved left set with NULL for all the columns that come from the right set.

  • <Set A> RIGHT OUTER JOIN <Set B> ON <Join Condition> — Adds to the INNER JOIN all the rows from the reserved right set with NULL for all the columns that come from the left set.

  • <Set A> FULL OUTER JOIN <Set B> ON <Join Condition> — Designates both sets as reserved and adds non matching rows from both, similar to a LEFT OUTER JOIN and a RIGHT OUTER JOIN.

APPLY

SQL Server also supports the APPLY operator, which is somewhat similar to a join. However, APPLY operators enable the creation of a correlation between <Set A> and <Set B> such as that <Set B> may consist of a subquery, a VALUES row value constructor, or a table valued function that is evaluated for each row of <Set A> where the <Set B> query can reference columns from the current row in <Set A>. This functionality isn’t possible with any type of standard JOIN operator.

There are two APPLY types:

  • <Set A> CROSS APPLY <Set B> — Similar to a CROSS JOIN in the sense that every row from <Set A> is matched with every row from <Set B>.

  • <Set A> OUTER APPLY <Set B> — Similar to a LEFT OUTER JOIN in the sense that rows from <Set A> are returned even if the sub query for <Set B> produces an empty set. In that case, NULL is assigned to all columns of <Set B>.

ANSI SQL 89 JOIN Syntax

Up until SQL Server version 2008 R2, SQL Server also supported the old style JOIN syntax including LEFT and` RIGHT OUTER JOIN`.

The ANSI syntax for a CROSS JOIN operator was to list the sets in the FROM clause using commas as separators. Consider the following example:

SELECT *
FROM Table1,
    Table2,
    Table3...

To perform an INNER JOIN, you only needed to add the JOIN predicate as part of the WHERE clause. Consider the following example:

SELECT *
FROM Table1,
    Table2
WHERE Table1.Column1 = Table2.Column1

Although the ANSI standard didn’t specify outer joins at the time, most RDBMS supported them in one way or another. T-SQL supported outer joins by adding an asterisk to the left or the right of equality sign of the join predicate to designate the reserved table. Consider the following example:

SELECT *
FROM Table1,
    Table2
WHERE Table1.Column1 *= Table2.Column1

To perform a FULL OUTER JOIN, asterisks were placed on both sides of the equality sign of the join predicate.

As of SQL Server 2008R2, outer joins using this syntax have been deprecated. For more information, see Deprecated Database Engine Features in SQL Server 2008 R2 in the SQL Server documentation.

Note

Even though inner joins using the ANSI SQL 89 syntax are still supported, they are highly discouraged due to being notorious for introducing hard to catch programming bugs.

Syntax

CROSS JOIN

FROM <Table Source 1>
    CROSS JOIN
    <Table Source 2>
-- ANSI 89
FROM <Table Source 1>,
    <Table Source 2>

INNER / OUTER JOIN

FROM <Table Source 1>
    [ { INNER | { { LEFT | RIGHT | FULL } [ OUTER ] } }] JOIN
    <Table Source 2>
    ON <JOIN Predicate>
-- ANSI 89
FROM <Table Source 1>,
    <Table Source 2>
WHERE <Join Predicate>
<Join Predicate>:: <Table Source 1 Expression> | = | *= | =* | *=* <Table Source 2 Expression>

APPLY

FROM <Table Source 1>
    { CROSS | OUTER } APPLY
    <Table Source 2>
<Table Source 2>:: <SELECT sub-query> | <Table Valued UDF> | <VALUES clause>

Examples

Create the Orders and Items tables.

CREATE TABLE Items
(
Item VARCHAR(20) NOT NULL
    PRIMARY KEY
Category VARCHAR(20) NOT NULL,
Material VARCHAR(20) NOT NULL
);
INSERT INTO Items (Item, Category, Material)
VALUES
('M8 Bolt', 'Metric Bolts', 'Stainless Steel'),
('M8 Nut', 'Metric Nuts', 'Stainless Steel'),
('M8 Washer', 'Metric Washers', 'Stainless Steel'),
('3/8" Bolt', 'Imperial Bolts', 'Brass')
CREATE TABLE OrderItems
(
    OrderID INT NOT NULL,
    Item VARCHAR(20) NOT NULL
    REFERENCES Items(Item),
    Quantity SMALLINT NOT NULL,
    PRIMARY KEY(OrderID, Item)
);
INSERT INTO OrderItems (OrderID, Item, Quantity)
VALUES
(1, 'M8 Bolt', 100),
(2, 'M8 Nut', 100),
(3, 'M8 Washer', 200)

INNER JOIN

SELECT *
FROM Items AS I
    INNER JOIN
    OrderItems AS OI
    ON I.Item = OI.Item;

-- ANSI SQL 89
SELECT *
FROM Items AS I,
    OrderItems AS OI
WHERE I.Item = OI.Item;

LEFT OUTER JOIN

Find Items that were never ordered.

SELECT Item
FROM Items AS I
    LEFT OUTER JOIN
    OrderItems AS OI
    ON I.Item = OI.Item
WHERE OI.OrderID IS NULL;

-- ANSI SQL 89
SELECT Item
FROM
(
    SELECT I.Item, O.OrderID
    FROM Items AS I,
        OrderItems AS OI
    WHERE I.Item *= OI.Item
) AS LeftJoined
WHERE LeftJoined.OrderID IS NULL;

FULL OUTER JOIN

CREATE TABLE T1(Col1 INT, COl2 CHAR(2));
CREATE TABLE T2(Col1 INT, COl2 CHAR(2));

INSERT INTO T1 (Col1, Col2)
VALUES (1, 'A'), (2,'B');

INSERT INTO T2 (Col1, Col2)
VALUES (2,'BB'), (3,'CC');

SELECT *
FROM T1
    FULL OUTER JOIN
    T2
    ON T1.Col1 = T2.Col1;
Result:
Col1  COl2  Col1  COl2
1     A     NULL  NULL
2     B     2     BB
NULL NULL 3 CC

For more information, see FROM clause plus JOIN, APPLY, PIVOT (Transact-SQL) in the SQL Server documentation.

MySQL Usage

Amazon Aurora MySQL-Compatible Edition (Aurora MySQL) supports the following types of joins in the same way as SQL Server, except for FULL OUTER JOIN:

  • <Set A> CROSS JOIN <Set B> — Results in a Cartesian product of the two sets. Every JOIN starts as a Cartesian product.

  • <Set A> INNER JOIN <Set B> ON <Join Condition> — Filters the Cartesian product to only the rows where the join predicate evaluates to TRUE.

  • <Set A> LEFT OUTER JOIN <Set B> ON <Join Condition> — Adds to the INNER JOIN all the rows from the reserved left set with NULL for all the columns that come from the right set.

  • <Set A> RIGHT OUTER JOIN <Set B> ON <Join Condition> — Adds to the INNER JOIN all the rows from the reserved right set with NULL for all the columns that come from the left set.

In addition, Aurora MySQL supports the following join types not supported by SQL Server:

  • <Set A> NATURAL [INNER | LEFT OUTER | RIGHT OUTER ] JOIN <Set B> — Implicitly assumes that the join predicate consists of all columns with the same name from <Set A> and <Set B>.

  • <Set A> STRAIGHT_JOIN <Set B> — Forces <Set A> to be read before <Set B> and is used as an optimizer hint.

Aurora MySQL also supports the USING clause as an alternative to the ON clause. The USING clause consists of a list of comma separated columns that must appear in both tables. The join predicate is the equivalent of an AND logical operator for equality predicates of each column. For example, the following two joins are equivalent:

FROM Table1
    INNER JOIN
    Table2
    ON Table1.Column1 = Table2.column1;
FROM Table1
    INNER JOIN
    Table2
    USING (Column1);

If Column1 is the only column with a common name between Table1 and Table2, the following statement is also equivalent:

FROM Table1
    NATURAL JOIN
    Table2
Note

Aurora MySQL supports the ANSI SQL 89 syntax for joins using commas in the FROM clause, but only for inner joins.

Note

Aurora MySQL supports neither APPLY nor the equivalent LATERAL JOIN used by some other database engines.

Syntax

FROM
    <Table Source 1> CROSS JOIN <Table Source 2>
    | <Table Source 1> INNER JOIN <Table Source 2>
        ON <Join Predicate> | USING (Equality Comparison Column List)
    | <Table Source 1> {LEFT|RIGHT} [OUTER] JOIN <Table Source 2>
        ON <Join Predicate> | USING (Equality Comparison Column List)
    | <Table Source 1> NATURAL [INNER | {LEFT|RIGHT} [OUTER]] JOIN <Table Source 2>
    | <Table Source 1> STRAIGHT_JOIN <Table Source 2>
    | <Table Source 1> STRAIGHT_JOIN <Table Source 2>
        ON <Join Predicate>

Migration Considerations

For most joins, the syntax should be equivalent and no rewrites should be needed.

  • CROSS JOIN using either ANSI SQL 89 or ANSI SQL 92 syntax.

  • INNER JOIN using either ANSI SQL 89 or ANSI SQL 92 syntax.

  • OUTER JOIN using the ANSI SQL 92 syntax only.

FULL OUTER JOIN and OUTER JOIN using the pre-ANSI SQL 92 syntax aren’t supported, but they can be easily worked around.

CROSS APPLY and OUTER APPLY aren’t supported and need to be rewritten.

Examples

Create the Orders and Items tables.

CREATE TABLE Items
(
    Item VARCHAR(20) NOT NULL
    PRIMARY KEY
    Category VARCHAR(20) NOT NULL,
    Material VARCHAR(20) NOT NULL
);
INSERT INTO Items (Item, Category, Material)
VALUES
('M8 Bolt', 'Metric Bolts', 'Stainless Steel'),
('M8 Nut', 'Metric Nuts', 'Stainless Steel'),
('M8 Washer', 'Metric Washers', 'Stainless Steel'),
('3/8" Bolt', 'Imperial Bolts', 'Brass')
CREATE TABLE OrderItems
(
    OrderID INT NOT NULL,
    Item VARCHAR(20) NOT NULL
    REFERENCES Items(Item),
    Quantity SMALLINT NOT NULL,
    PRIMARY KEY(OrderID, Item)
);
INSERT INTO OrderItems (OrderID, Item, Quantity)
VALUES
(1, 'M8 Bolt', 100),
(2, 'M8 Nut', 100),
(3, 'M8 Washer', 200)

INNER JOIN and OUTER JOIN

SELECT *
FROM Items AS I
    INNER JOIN
    OrderItems AS OI
    ON I.Item = OI.Item;

-- ANSI SQL 89
SELECT *
FROM Items AS I,
    Orders AS O
WHERE I.Item = OI.Item;

LEFT OUTER JOIN

SELECT Item
FROM Items AS I
    LEFT OUTER JOIN
    OrderItems AS OI
    ON I.Item = OI.Item
WHERE OI.OrderID IS NULL;

Rewrite for FULL OUTER JOIN

CREATE TABLE T1(Col1 INT, COl2 CHAR(2));
CREATE TABLE T2(Col1 INT, COl2 CHAR(2));

INSERT INTO T1 (Col1, Col2)
VALUES (1, 'A'), (2,'B');

INSERT INTO T2 (Col1, Col2)
VALUES (2,'BB'), (3,'CC');

SELECT *
FROM T1
    LEFT OUTER JOIN
    T2
    ON T1.Col1 = T2.Col1
UNION ALL
SELECT NULL, NULL, Col1, Col2
FROM T2
WHERE Col1 NOT IN (SELECT Col1 FROM T1);
Result:
Col1  COl2  Col1  COl2
1     A     NULL  NULL
2     B     2     BB
NULL  NULL  3     CC

Summary

Table of similarities, differences, and key migration considerations.

SQL Server Aurora MySQL Comments

INNER JOIN with ON clause or commas

Supported

OUTER JOIN with ON clause

Supported

OUTER JOIN with commas

Not supported

Requires T-SQL rewrite post SQL Server 2008 R2.

CROSS JOIN or using commas

Supported

CROSS APPLY and OUTER APPLY

Not Supported

Rewrite required.

Not Supported

NATURAL JOIN

Not recommended, may cause unexpected issues if table structure changes.

Not Supported

STRAIGHT_JOIN

Not Supported

USING clause

For more information, see JOIN Clause in the MySQL documentation.