Appendix I. Feature Restrictions
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## Appendix I. Feature Restrictions

The discussion here describes restrictions that apply to the use of MySQL features such as subqueries or views.

## I.1. Restrictions on Stored Routines and Triggers

Some of the restrictions noted here apply to all stored routines; that is, both to stored procedures and stored functions. Some of restrictions apply only to stored functions, and not to stored procedures.

All of the restrictions for stored functions also apply to triggers. In addition, triggers currently are not activated by foreign key actions.

Stored routines cannot contain arbitrary SQL statements. The following statements are disallowed:

- The table-maintenance statements `CHECK TABLES` and `OPTIMIZE TABLES`. Note: This restriction is lifted beginning with MySQL 5.0.17.

- The locking statements `LOCK TABLES`, `UNLOCK TABLES`.

- `LOAD DATA` and `LOAD TABLE`.

- SQL prepared statements (`PREPARE`, `EXECUTE`, `DEALLOCATE PREPARE`). Implication: You cannot use dynamic SQL within stored routines (where you construct dynamically statements as strings and then execute them). This restriction is lifted as of MySQL 5.0.13 for stored procedures; it still applies to stored functions and triggers.

For stored functions (but not stored procedures), the following additional statements or operations are disallowed:

- Statements that do explicit or implicit commit or rollback.

- Statements that return a result set. This includes `SELECT` statements that do not have an `INTO `var_list`` clause and `SHOW` statements. A function can process a result set either with `SELECT ... INTO `var_list`` or by using a cursor and `FETCH` statements. See Section 17.2.7.3, “`SELECT ... INTO` Statement”.

- `FLUSH` statements.

- Note: Before MySQL 5.0.10, stored functions created with `CREATE FUNCTION` must not contain references to tables, with limited exceptions. They may include some `SET` statements that contain table references, for example `SET a:= (SELECT MAX(id) FROM t)`, and `SELECT` statements that fetch values directly into variables, for example `SELECT i INTO var1 FROM t`.

- Recursive statements. That is, stored functions cannot be used recursively.

- Within a stored function or trigger, it is not allowable to modify a table that is already being used (for reading or writing) by the statement that invoked the function or trigger.

Note that although some restrictions normally apply to stored functions and triggers but not to stored procedures, those restrictions do apply to stored procedures if they are invoked from within a stored function or trigger. For example, although you can use `FLUSH` in a stored procedure, such a stored procedure cannot be called from a stored function or trigger.

It is possible for the same identifier to be used for a routine parameter, a local variable, and a table column. Also, the same local variable name can be used in nested blocks. For example:

    CREATE PROCEDURE p (i INT)
    BEGIN
      DECLARE i INT DEFAULT 0;
      SELECT i FROM t;
      BEGIN
        DECLARE i INT DEFAULT 1;
        SELECT i FROM t;
      END;
    END;

In such cases the identifier is ambiguous and the following precedence rules apply:

- A local variable takes precedence over a routine parameter or table column

- A routine parameter takes precedence over a table column

- A local variable in an inner block takes precedence over a local variable in an outer block

The behavior that table columns do not take precedence over variables is non-standard.

Use of stored routines can cause replication problems. This issue is discussed further in Section 17.4, “Binary Logging of Stored Routines and Triggers”.

`INFORMATION_SCHEMA` does not yet have a `PARAMETERS` table, so applications that need to acquire routine parameter information at runtime must use workarounds such as parsing the output of `SHOW CREATE` statements.

There are no stored routine debugging facilities.

`CALL` statements cannot be prepared. This true both for server-side prepared statements and for SQL prepared statements.

`UNDO` handlers are not supported.

`FOR` loops are not supported.

To prevent problems of interaction between server threads, when a client issues a statement, the server uses a snapshot of routines and triggers available for execution of the statement. That is, the server calculates a list of procedures, functions, and triggers that may be used during execution of the statement, loads them, and then proceeds to execute the statement. This means that while the statement executes, it will not see changes to routines performed by other threads.

The `RETURN` statement is disallowed in triggers, which cannot return a value. To exit a trigger immediately, use the `LEAVE` statement.

## I.2. Restrictions on Server-Side Cursors

Server-side cursors are implemented beginning with the C API in MySQL 5.0.2 via the `mysql_stmt_attr_set()` function. A server-side cursor allows a result set to be generated on the server side, but not transferred to the client except for those rows that the client requests. For example, if a client executes a query but is only interested in the first row, the remaining rows are not transferred.

In MySQL, a server-side cursor is materialized into a temporary table. Initially, this is a `MEMORY` table, but is converted to a `MyISAM` table if its size reaches the value of the `max_heap_table_size` system variable. (Beginning with MySQL 5.0.14, the same temporary-table implementation also is used for cursors in stored routines.) One limitation of the implementation is that for a large result set, retrieving its rows through a cursor might be slow.

Cursors are read-only; you cannot use a cursor to update rows.

`UPDATE WHERE CURRENT OF` and `DELETE WHERE CURRENT OF` are not implemented, because updatable cursors are not supported.

Cursors are non-holdable (not held open after a commit).

Cursors are asensitive.

Cursors are non-scrollable.

Cursors are not named. The statement handler acts as the cursor ID.

You can have open only a single cursor per prepared statement. If you need several cursors, you must prepare several statements.

You cannot use a cursor for a statement that generates a result set if the statement is not supported in prepared mode. This includes statements such as `CHECK TABLES`, `HANDLER READ`, and `SHOW BINLOG EVENTS`.

## I.3. Restrictions on Subqueries

- Known bug to be fixed later: If you compare a `NULL` value to a subquery using `ALL`, `ANY`, or `SOME`, and the subquery returns an empty result, the comparison might evaluate to the non-standard result of `NULL` rather than to `TRUE` or `FALSE`.

- A subquery's outer statement can be any one of: `SELECT`, `INSERT`, `UPDATE`, `DELETE`, `SET`, or `DO`.

- Subquery optimization for `IN` is not as effective as for the `=` operator or for `IN(`value_list`)` constructs.

  A typical case for poor `IN` subquery performance is when the subquery returns a small number of rows but the outer query returns a large number of rows to be compared to the subquery result.

  The problem is that, for a statement that uses an `IN` subquery, the optimizer rewrites it as a correlated subquery. Consider the following statement that uses an uncorrelated subquery:

      SELECT ... FROM t1 WHERE t1.a IN (SELECT b FROM t2);

  The optimizer rewrites the statement to a correlated subquery:

      SELECT ... FROM t1 WHERE EXISTS (SELECT 1 FROM t2 WHERE t2.b = t1.a);

  If the inner and outer queries return `M` and `N` rows, respectively, the execution time becomes on the order of `O(`M`×`N`)`, rather than `O(`M`+`N`)` as it would be for an uncorrelated subquery.

  An implication is that an `IN` subquery can be much slower than a query written using an `IN(`value_list`)` construct that lists the same values that the subquery would return.

- In general, you cannot modify a table and select from the same table in a subquery. For example, this limitation applies to statements of the following forms:

      DELETE FROM t WHERE ... (SELECT ... FROM t ...);
      UPDATE t ... WHERE col = (SELECT ... FROM t ...);
      {INSERT|REPLACE} INTO t (SELECT ... FROM t ...);

  Exception: The preceding prohibition does not apply if you are using a subquery for the modified table in the `FROM` clause. Example:

      UPDATE t ... WHERE col = (SELECT (SELECT ... FROM t...) AS _t ...);

  Here the prohibition does not apply because a subquery in the `FROM` clause is materialized as a temporary table, so the relevant rows in `t` have already been selected by the time the update to `t` takes place.

- Row comparison operations are only partially supported:

  - For ``expr` IN (`subquery`)`, `expr` can be an `n`-tuple (specified via row constructor syntax) and the subquery can return rows of `n`-tuples.

  - For ``expr` `op` {ALL|ANY|SOME} (`subquery`)`, `expr` must be a scalar value and the subquery must be a column subquery; it cannot return multiple-column rows.

  In other words, for a subquery that returns rows of `n`-tuples, this is supported:

      (val_1, ..., val_n) IN (subquery)

  But this is not supported:

      (val_1, ..., val_n) op {ALL|ANY|SOME} (subquery)

  The reason for supporting row comparisons for `IN` but not for the others is that `IN` is implemented by rewriting it as a sequence of `=` comparisons and `AND` operations. This approach cannot be used for `ALL`, `ANY`, or `SOME`.

- Row constructors are not well optimized. The following two expressions are equivalent, but only the second can be optimized:

      (col1, col2, ...) = (val1, val2, ...)
      col1 = val1 AND col2 = val2 AND ...

- Subqueries in the `FROM` clause cannot be correlated subqueries. They are materialized (executed to produce a result set) before evaluating the outer query, so they cannot be evaluated per row of the outer query.

- The optimizer is more mature for joins than for subqueries, so in many cases a statement that uses a subquery can be executed more efficiently if you rewrite it as a join.

  An exception occurs for the case where an `IN` subquery can be rewritten as a `SELECT DISTINCT` join. Example:

      SELECT col FROM t1 WHERE id_col IN (SELECT id_col2 FROM t2 WHERE condition);

  That statement can be rewritten as follows:

      SELECT DISTINCT col FROM t1, t2 WHERE t1.id_col = t2.id_col AND condition;

  But in this case, the join requires an extra `DISTINCT` operation and is not more efficient than the subquery.

- Possible future optimization: MySQL does not rewrite the join order for subquery evaluation. In some cases, a subquery could be executed more efficiently if MySQL rewrote it as a join. This would give the optimizer a chance to choose between more execution plans. For example, it could decide whether to read one table or the other first.

  Example:

      SELECT a FROM outer_table AS ot
      WHERE a IN (SELECT a FROM inner_table AS it WHERE ot.b = it.b);

  For that query, MySQL always scans `outer_table` first and then executes the subquery on `inner_table` for each row. If `outer_table` has a lot of rows and `inner_table` has few rows, the query probably will not be as fast as it could be.

  The preceding query could be rewritten like this:

      SELECT a FROM outer_table AS ot, inner_table AS it
      WHERE ot.a = it.a AND ot.b = it.b;

  In this case, we can scan the small table (`inner_table`) and look up rows in `outer_table`, which will be fast if there is an index on `(ot.a,ot.b)`.

- Possible future optimization: A correlated subquery is evaluated for each row of the outer query. A better approach is that if the outer row values do not change from the previous row, do not evaluate the subquery again. Instead, use its previous result.

- Possible future optimization: A subquery in the `FROM` clause is evaluated by materializing the result into a temporary table, and this table does not use indexes. This does not allow the use of indexes in comparison with other tables in the query, although that might be useful.

- Possible future optimization: If a subquery in the `FROM` clause resembles a view to which the merge algorithm can be applied, rewrite the query and apply the merge algorithm so that indexes can be used. The following statement contains such a subquery:

      SELECT * FROM (SELECT * FROM t1 WHERE t1.t1_col) AS _t1, t2 WHERE t2.t2_col;

  The statement can be rewritten as a join like this:

      SELECT * FROM t1, t2 WHERE t1.t1_col AND t2.t2_col;

  This type of rewriting would provide two benefits:

  - It avoids the use of a temporary table for which no indexes can be used. In the rewritten query, the optimizer can use indexes on `t1`.

  - It gives the optimizer more freedom to choose between different execution plans. For example, rewriting the query as a join allows the optimizer to use `t1` or `t2` first.

- Possible future optimization: For `IN`, `= ANY`, `<> ANY`, `= ALL`, and `<> ALL` with non-correlated subqueries, use an in-memory hash for a result result or a temporary table with an index for larger results. Example:

      SELECT a FROM big_table AS bt
      WHERE non_key_field IN (SELECT non_key_field FROM table WHERE condition)

  In this case, we could create a temporary table:

      CREATE TABLE t (key (non_key_field))
      (SELECT non_key_field FROM table WHERE condition)

  Then, for each row in `big_table`, do a key lookup in `t` based on `bt.non_key_field`.

## I.4. Restrictions on Views

View processing is not optimized:

- It is not possible to create an index on a view.

- Indexes can be used for views processed using the merge algorithm. However, a view that is processed with the temptable algorithm is unable to take advantage of indexes on its underlying tables (although indexes can be used during generation of the temporary tables).

Subqueries cannot be used in the `FROM` clause of a view. This limitation will be lifted in the future.

There is a general principle that you cannot modify a table and select from the same table in a subquery. See Section I.3, “Restrictions on Subqueries”.

The same principle also applies if you select from a view that selects from the table, if the view selects from the table in a subquery and the view is evaluated using the merge algorithm. Example:

    CREATE VIEW v1 AS
    SELECT * FROM t2 WHERE EXISTS (SELECT 1 FROM t1 WHERE t1.a = t2.a);

    UPDATE t1, v2 SET t1.a = 1 WHERE t1.b = v2.b;

If the view is evaluated using a temporary table, you can select from the table in the view subquery and still modify that table in the outer query. In this case the view will be materialized and thus you are not really selecting from the table in a subquery and modifying it “at the same time.” (This is another reason you might wish to force MySQL to use the temptable algorithm by specifying `ALGORITHM = TEMPTABLE` in the view definition.)

You can use `DROP TABLE` or `ALTER TABLE` to drop or alter a table that is used in a view definition (which invalidates the view) and no warning results from the drop or alter operation. An error occurs later when the view is used.

A view definition is “frozen” by certain statements:

- If a statement prepared by `PREPARE` refers to a view, the view contents seen each time the statement is executed later will be the contents of the view at the time it was prepared. This is true even if the view definition is changed after the statement is prepared and before it is executed. Example:

      CREATE VIEW v AS SELECT 1;
      PREPARE s FROM 'SELECT * FROM v';
      ALTER VIEW v AS SELECT 2;
      EXECUTE s;

  The result returned by the `EXECUTE` statement is 1, not 2.

- If a statement in a stored routine refers to a view, the view contents seen by the statement are its contents the first time that statement is executed. For example, this means that if the statement is executed in a loop, further iterations of the statement see the same view contents, even if the view definition is changed later in the loop. Example:

      CREATE VIEW v AS SELECT 1;
      delimiter //
      CREATE PROCEDURE p ()
      BEGIN
        DECLARE i INT DEFAULT 0;
        WHILE i < 5 DO
          SELECT * FROM v;
          SET i = i + 1;
          ALTER VIEW v AS SELECT 2;
        END WHILE;
      END;
      //
      delimiter ;
      CALL p();

  When the procedure `p()` is called, the `SELECT` returns 1 each time through the loop, even though the view definition is changed within the loop.

With regard to view updatability, the overall goal for views is that if any view is theoretically updatable, it should be updatable in practice. This includes views that have `UNION` in their definition. Currently, not all views that are theoretically updatable can be updated. The initial view implementation was deliberately written this way to get usable, updatable views into MySQL as quickly as possible. Many theoretically updatable views can be updated now, but limitations still exist:

- Updatable views with subqueries anywhere other than in the `WHERE` clause. Some views that have subqueries in the `SELECT` list may be updatable.

- You cannot use `UPDATE` to update more than one underlying table of a view that is defined as a join.

- You cannot use `DELETE` to update a view that is defined as a join.

## I.5. Restrictions on XA Transactions

XA transaction support is limited to the `InnoDB` storage engine.

The MySQL XA implementation is for “external XA,” where a MySQL server acts as a Resource Manager and client programs act as Transaction Managers. “Internal XA” is not implemented. This would allow individual storage engines within a MySQL server to act as RMs, and the server itself to act as a TM. Internal XA is required for handling XA transactions that involve more than one storage engine. The implementation of internal XA is incomplete because it requires that a storage engine support two-phase commit at the table handler level, and currently this is true only for `InnoDB`.

For `XA START`, the `JOIN` and `RESUME` clauses are not supported.

For `XA END`, the `SUSPEND [FOR MIGRATE]` clause is not supported.

The requirement that the `bqual` part of the `xid` value be different for each XA transaction within a global transaction is a limitation of the current MySQL XA implementation. It is not part of the XA specification.

If an XA transaction has reached the `PREPARED` state and the MySQL server is killed (for example, with kill -9 on Unix) or shuts down abnormally, the transaction can be continued after the server restarts. However, if the client reconnects and commits the transaction, the transaction will be absent from the binary log even though it has been committed. This means the data and the binary log have gone out of synchrony. An implication is that XA cannot be used safely together with replication.

It is possible that the server will roll back a pending XA transaction, even one that has reached the `PREPARED` state. This happens if a client connection terminates and the server continues to run, or if clients are connected and the server shuts down gracefully. (In the latter case, the server marks each connection to be terminated, and then rolls back the `PREPARED` XA transaction associated with it.) It should be possible to commit or roll back a `PREPARED` XA transaction, but this cannot be done without changes to the binary logging mechanism.

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