Apéndice H. Restricciones en características de MySQL
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## Apéndice H. Restricciones en características de MySQL

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

## H.1. Restricciones en procedimientos almacenados y disparadores

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.

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

- `CHECK TABLES`

- `LOCK TABLES`, `UNLOCK TABLES`

- `FLUSH`

- `LOAD DATA`, `LOAD TABLE`

- SQL prepared statements (`PREPARE`, `EXECUTE`, `DEALLOCATE`). Implication: You cannot use dynamic SQL within stored routines (where you construct dynamically statements as strings and then execute them).

For stored functions (but not stored procedures), the following additional statements 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` clause and `SHOW` statements. A function can process a result set either with `SELECT … INTO` or by using a cursor and `FETCH` statements.

Use of stored routines can cause replication problems. This issue is discussed further in Sección 19.3, “Registro binario de procedimientos almacenados y disparadores”.

`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.

Stored routines use materialized cursors, not native cursors. (The result set is generated and cached on the server side, and then returned row by row as the client fetches it.)

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

## H.2. Restricciones en cursores el lado del servidor

Server-side cursors are implemented beginning with MySQL 5.0.2 via the `mysql_stmt_attr_set()` C API 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.

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`.

## H.3. Restricciones en subconsultas

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`.

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` was 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 ...

Subquery optimization for `IN` is not as effective as for `=`.

A typical case for poor `IN` 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.

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.

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.

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 doesn't 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 can 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:

1. 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`.

2. 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`.

## H.4. Restricciones en vistas

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 Sección H.3, “Restricciones en subconsultas”.

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 aren't 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` keyword 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 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 in order 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.

Ésta es una traducción del manual de referencia de MySQL, que puede encontrarse en dev.mysql.com. El manual de referencia original de MySQL está escrito en inglés, y esta traducción no necesariamente está tan actualizada como la versión original. Para cualquier sugerencia sobre la traducción y para señalar errores de cualquier tipo, no dude en dirigirse a mysql-es@vespito.com.

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