A number of limitations exist in MySQL Cluster with regard to the handling of transactions. These include the following:
Transaction isolation level. The
NDBCLUSTERstorage engine supports only the
READ COMMITTEDtransaction isolation level. (
InnoDB, for example, supports
REPEATABLE READ, and
SERIALIZABLE.) You should keep in mind that
READ COMMITTEDon a per-row basis; when a read request arrives at the data node storing the row, what is returned is the last committed version of the row at that time.
Uncommitted data is never returned, but when a transaction modifying a number of rows commits concurrently with a transaction reading the same rows, the transaction performing the read can observe “before” values, “after” values, or both, for different rows among these, due to the fact that a given row read request can be processed either before or after the commit of the other transaction.
To ensure that a given transaction reads only before or after values, you can impose row locks using
SELECT ... LOCK IN SHARE MODE. In such cases, the lock is held until the owning transaction is committed. Using row locks can also cause the following issues:
Increased frequency of lock wait timeout errors, and reduced concurrency
Increased transaction processing overhead due to reads requiring a commit phase
Possibility of exhausting the available number of concurrent locks, which is limited by
READ COMMITTEDfor all reads unless a modifier such as
LOCK IN SHARE MODEor
FOR UPDATEis used.
LOCK IN SHARE MODEcauses shared row locks to be used;
FOR UPDATEcauses exclusive row locks to be used. Unique key reads have their locks upgraded automatically by
NDBto ensure a self-consistent read;
BLOBreads also employ extra locking for consistency.
See Section 188.8.131.52, “MySQL Cluster Backup Troubleshooting”, for information on how MySQL Cluster's implementation of transaction isolation level can affect backup and restoration of
Transactions and BLOB or TEXT columns.
NDBCLUSTERstores only part of a column value that uses any of MySQL's
TEXTdata types in the table visible to MySQL; the remainder of the
TEXTis stored in a separate internal table that is not accessible to MySQL. This gives rise to two related issues of which you should be aware whenever executing
SELECTstatements on tables that contain columns of these types:
SELECTfrom a MySQL Cluster table: If the
READ COMMITTEDtransaction isolation level is converted to a read with read lock. This is done to guarantee consistency.
SELECTwhich uses a unique key lookup to retrieve any columns that use any of the
TEXTdata types and that is executed within a transaction, a shared read lock is held on the table for the duration of the transaction—that is, until the transaction is either committed or aborted.
For example, consider the table
tdefined by the following
CREATE TABLE t ( a INT NOT NULL AUTO_INCREMENT PRIMARY KEY, b INT NOT NULL, c INT NOT NULL, d TEXT, INDEX i(b), UNIQUE KEY u(c) ) ENGINE = NDB,
Either of the following queries on
tcauses a shared read lock, because the first query uses a primary key lookup and the second uses a unique key lookup:
SELECT * FROM t WHERE a = 1; SELECT * FROM t WHERE c = 1;
However, none of the four queries shown here causes a shared read lock:
SELECT * FROM t WHERE b = 1; SELECT * FROM t WHERE d = '1'; SELECT * FROM t; SELECT b,c WHERE a = 1;
This is because, of these four queries, the first uses an index scan, the second and third use table scans, and the fourth, while using a primary key lookup, does not retrieve the value of any
You can help minimize issues with shared read locks by avoiding queries that use unique key lookups that retrieve
TEXTcolumns, or, in cases where such queries are not avoidable, by committing transactions as soon as possible afterward.
Rollbacks. There are no partial transactions, and no partial rollbacks of transactions. A duplicate key or similar error causes the entire transaction to be rolled back.
This behavior differs from that of other transactional storage engines such as
InnoDBthat may roll back individual statements.
Transactions and memory usage. As noted elsewhere in this chapter, MySQL Cluster does not handle large transactions well; it is better to perform a number of small transactions with a few operations each than to attempt a single large transaction containing a great many operations. Among other considerations, large transactions require very large amounts of memory. Because of this, the transactional behavior of a number of MySQL statements is effected as described in the following list:
DELETE FROM(even with no
WHEREclause) is transactional. For tables containing a great many rows, you may find that performance is improved by using several
DELETE FROM ... LIMIT ...statements to “chunk” the delete operation. If your objective is to empty the table, then you may wish to use
Transactions and the COUNT() function. When using MySQL Cluster Replication, it is not possible to guarantee the transactional consistency of the
COUNT()function on the slave. In other words, when performing on the master a series of statements (
DELETE, or both) that changes the number of rows in a table within a single transaction, executing
SELECT COUNT(*) FROMqueries on the slave may yield intermediate results. This is due to the fact that
SELECT COUNT(...)may perform dirty reads, and is not a bug in the