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MySQL Advanced MySQL Replication MySQL Cluster MySQL Partitioning
António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 1 1
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MySQL Advanced MySQL Replication
António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 2 2
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MySQL Replication Concepts
MySQL replication tracks updates performed in a MySQL master logs and updates one or more slave servers. The mechanism involved in MySQL replication requires binary logging to be active. -Asynchronous replication, a slave doesn't need to be always active. -MySQL replication can be used to scale-out queries among different servers. -MySQL replication is a good solution for performing live backups. - Long distance data distribution. António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 3 3
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MySQL Replication Architecture MySQL replication architecture:
- Each update performed in a database is replicated from the master to the slaves. - Only slaves keep track of their replication status. - One may set at what point the replication begins. António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 4 4
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MySQL Replication setup MySQL Master
Turn on binary log and set the server id restart mysql server: server-id =1 log_bin =/var/log/mysql/mysql-bin.log binlog_do_db = gaia_test Create a user for replication: GRANT REPLICATION SLAVE ON *.* TO IDENTIFIED BY 'password'; MySQL slave Set the master properties in /etc/mysql/my.cnf: server-id=2 master-host = master_ip master-user = rep_slave master-password = password replicate-do-db={db_name} António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 5 5
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MySQL Replication setup MySQL Master Show master log position:
mysql > show master status \G; File: mysql-bin Position: 784 Binlog_Do_DB: gaia_test MySQL slave Change log position: CHANGE MASTER TO MASTER_HOST=server_IP, MASTER_LOG_FILE=mysql- bin, MASTER_LOG_POS=784; Start Slave: mysql > slave start; See slave status and notice the SLAVE_* variables for errors (No = bad) : Show slave status\G; António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 6 6
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MySQL Advanced MySQL Cluster
António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 7 7
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MySQL Cluster MySQL cluster is designed to provide near perfect availability through a shared nothing architecture, in turn this means that all the nodes in a MySQL cluster can be replicated for failover. MySQL cluster is a in memory database, which means that all data must be located in RAM, since version a mechanism is available to store data on disk although Indexes must still fit in ram. All data in MySQL is horizontally partitioned, across different storage nodes, which means that all table data is split across the storage nodes. António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 8 8
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MySQL Cluster MySQL cluster architecture consists of three types nodes: Storage nodes: All data is stored in this nodes. SQL nodes: Standard MySQL nodes, used for connection. Management nodes: Used to change the setup of the cluster. António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 9 9
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MySQL Cluster Setup (Debian)
To setup a 3 node (API + engine + management) MySQL Cluster you must update 2 files: Edit /etc/mysql/my.cnf and add: [mysqld] ndbcluster [MYSQL_CLUSTER] ndb-connectstring= António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 10 10
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MySQL Cluster Setup (debian)
Create a new configuration file in /etc/mysql/ndb_mgmd.cnf: [ndbd default] NoOfReplicas=1 DataMemory=80M IndexMemory=18M [ndb_mgmd] Id=1 hostname=localhost datadir=/var/lib/mysql-cluster [mysqld] António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 11 11
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MySQL Cluster Startup order: #1 Management nodes:
invoke-rc.d mysql-ndb-mgm start (start-initial) #2 Data nodes invoke-rc.d mysql-ndb start #3 SQL nodes invoke-rc.d mysql start António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 12 12
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MySQL Cluster Testing the installation: bash$ ndb-mgm -e show
Connected to Management Server at: :1186 Cluster Configuration [ndbd(NDB)] node(s) id=2 @ (Version: , Nodegroup: 0, Master) [ndb_mgmd(MGM)] 1 node(s) id=1 @ (Version: ) [mysqld(API)] 1 node(s) id=3 @ (Version: ) António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 13 13
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MySQL Cluster Testing the installation:
mysql> create table person (id int, name varchar(32)) engine = ndb; Query OK, 0 rows affected (2,34 sec) mysql> insert into person (id, name ) values ('11','carlos'); Query OK, 1 row affected (0,00 sec) mysql> select * from person; | id | name | | 11 | carlos | 1 row in set (0,00 sec) António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 14 14
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MySQL Advanced MySQL Partitioning
António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 15 15
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MySQL Partitioning concepts
Typical SQL doesn't provide guidance to underling physical storage layer, Partitioning allows you to split a table across multiple files, through the usage of a special partitioning rule called partitioning function. Partitioning can only take place in engines that support partitioning, engines like MyISAM or InnoDB and not like CSV or BlackHole. The big performance boost in database partition is that partitions that do not satisfy a certain rule are not scanned, this is called partition pruning. António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 16 16
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MySQL Partitioning Partition types
RANGE partitioning: Assigns rows to partitions based on column values falling within a given range. • LIST partitioning: Similar to partitioning by range, except that the partition is selected based on columns matching one of a Partitioning set of discrete values. • HASH partitioning: A partition is selected based on the value returned by a user-defined expression that operates on column values in rows to be inserted into the table. The function may consist of any expression valid in MySQL that yields a non- negative integer value. • KEY partitioning: Similar to partitioning by hash, except that only one or more columns to be evaluated are supplied, and the MySQL server provides its own hashing function. António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 17 17
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MySQL Partitioning examples
Range partition: CREATE TABLE t1 ( r_name VARCHAR(50) NOT NULL, region_code TINYINT UNSIGNED NOT NULL ) PARTITION BY RANGE( region_code ) ( PARTITION p0 VALUES LESS THAN (64), PARTITION p1 VALUES LESS THAN (128), PARTITION p3 VALUES LESS THAN MAXVALUE ); António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 18 18
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MySQL Partitioning examples
List Partition: CREATE TABLE employees ( id INT NOT NULL, fname VARCHAR(30), lname VARCHAR(30), hired DATE NOT NULL DEFAULT ' ', separated DATE NOT NULL DEFAULT ' ', job_code INT, store_id INT ) PARTITION BY LIST(store_id) ( PARTITION pNorth VALUES IN (16,15,3,5,6,9,17), PARTITION pEast VALUES IN (1,2,8,10,11,19,20), PARTITION pWest VALUES IN (7, 4,12,13,14,18) ); António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 19 19
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MySQL Partitioning examples
Hash Partition: CREATE TABLE employees ( id INT NOT NULL, fname VARCHAR(30), lname VARCHAR(30), hired DATE NOT NULL DEFAULT ' ', separated DATE NOT NULL DEFAULT ' ', job_code INT, store_id INT ) PARTITION BY HASH(store_id) PARTITIONS 5; António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 20 20
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MySQL Partitioning examples
Key Partition: CREATE TABLE k1 ( id INT NOT NULL PRIMARY KEY, name VARCHAR(20)) PARTITION BY KEY() PARTITIONS 4; id INT NOT NULL, name VARCHAR(20), UNIQUE KEY (id) ) António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 21 21
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Q&A For more information: More on MySQL-cluster and other studies: SIM Studies at the GAIA WIKI The technical note: GAIA-C1-TN-SIM-CDJ pdf GAIA-C1-TN-SIM-AAB pdf António Amorim, Carlos Jesus. CU1 - First Database Testing Meeting, 20/Nov/08 22 22
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MySQL Benchmarks MySQL Single server MySQL Cluster Oracle
António Amorim, Carlos Jesus. CU1 - DBWorkshop /Feb/09 23 23
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Network load(400K objects)
Test objectives Past studies evaluated the architecture and performance of MySQL Cluster and PostgreSQL solutions for the Gaia Databases. MySQL Cluster: MySQL-Cluster Poor performance Redundancy benefits PostgreSQL Sends 2x more data than MySQL Poor Bytea performance Network load(400K objects) PostgreSQL: 2072M MYSQL: Mb ORACLE-XE: 520 Mb António Amorim, Carlos Jesus. CU1 - First Database Testing Meeting, 20/Nov/08 24 24
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Single MySQL Server In order to pinpoint bottlenecks associated with MySQL, a series of basic tests were performed, these new tests made use of the available MDBExtractorIngestor package. Control and Monitor: Available at the local infrastructure was the SMS (Supervisor Monitor Scheduler) batch system, we deployed in one node the database and in another the Ingestor. At the local infrastructure was available the SMS (Supervisor Monitor Scheduler) batch system. The tests basic 2 node client server model the nodes where as following: Hardware setup António Amorim, Carlos Jesus. CU1 - First Database Testing Meeting, 20/Nov/08 25 25
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MDBExtractorIngestor
Tests For MDBExtractorIngestor JdbcObjectUpdater.java MySQL Ingestor, Old and new JdbcObjectUpdater, 4.5Gb of data. António Amorim, Carlos Jesus. CU1 - First Database Testing Meeting, 20/Nov/08 26 26
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Tests For DbBenchmark JdbcObjectUpdater.java MySQL Ingestor, Old and new JdbcObjectUpdater, 1Gb of data. Oracle datapump (local), 1Gb of data. António Amorim, Carlos Jesus. CU1 - First Database Testing Meeting, 20/Nov/08 27 27
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