MySQL databases come in all shapes and sizes, but most often are deployed behind Web sites. As sites grow, the companies behind them often become concerned about uptime and want to move to a high-availability model. Unfortunately, by this point, options often are limited based on the data and database engines previously chosen.
The first decision to make when moving to a high-availability model is actually whether to do it. This may seem obvious, but it often is assumed that high availability always is a good option. Opting to move in this direction, also means adds significant complexity to the system as a whole. When deploying a clustered solution, the number of boxes increase. Thus, the number of individual failures will increase, even though the downtime of the clustered application decreases overall. In addition, as availability increases, cost increases. Adding a second box for failover doubles the cost of the server, and adding failover clusters in alternative geographies can double (or more) the operational cost of the entire data center. In addition to this, moving to an NDB cluster adds additional hardware itself.
Before considering the level of availability you need, consider the cost of downtime compared to the operational costs of running failover facilities. Very few facilities need to continue running if there is a global extinction event, and planning for that situation would require the budget of a large government. Planning for failure as a result of a multinational economic disaster is more reasonable, but it still requires the budget of a large multinational corporation. When planning for national and localized disasters, the cost becomes more reasonable for most companies to handle. Based on this end-of-the-world thought experiment and the needs of most users, concentration on the development of high availability for MySQL mostly focuses on the single geography cluster.
Although you can build clusters in many ways, using combinations of block replication and SAN storage, the official MySQL solutions are replication and NDB (Network DataBase) clusters. Each has pros and cons, and your choice is not based on newer or older developments within MySQL, but on what is right for your application. In addition to choosing a type of replication, the version of MySQL is also critical. Because of continuing software development, at least version 5.1 is required for many of the features described here. If your current database has a lower version, strongly consider upgrading the database software before implementing these solutions. Active development on version 5.0 ended in December 2009, and active development on version 5.1 will end in December 2010.
MySQL replication establishes a master-slave or master-master relationship between a pair of servers. These servers can be chained to build a circular set of many servers, or one master can be used for many slaves, but the relationship itself exists between only two. A single MySQL server can have only a single master. Replication is more flexible than NDB in terms of what types of engines and features can be used. Although NDB clusters are limited to NDB tables, replication can be used with almost any of the standard MySQL table types, including MyIASM and InnoDB.
Multimaster replication examples usually are set up with only two servers, but they can be done with any number in a circular set. To set up a circular set with three servers, the [mysqld] section of the my.cnf configuration file should include the following:
server-id=1 # This must be unique per server. auto_increment_offset=1 # Must be unique per server but less # than the auto_increment_increment # value below. auto_increment_increment=3 # Set to at least the maximum # number of servers in the circle
The auto_increment_offset value determines the starting point for auto_increment columns and must be unique per server but less than the auto_increment_increment value. The auto_increment_increment value determines the interval between auto_increment values on a particular server. To prevent conflicts, set it to at least the maximum number of servers in the circle.
Now, to determine the next value in an auto_increment column, the server multiplies the next value expected in counting order by the auto_increment_increment value, plus the auto_increment_offset value. If N is the next expected value in a sequence (for example, 1, 2, 3, 4, 5 and so on), the next value for an auto_increment column becomes:
N x auto_increment_increment + auto_increment_offset
In addition, add the following values:
log_slave_updates: this tells the server to log updates from its master into its own log, so that the machine can act as both a master and a slave.
slave_exec_mode=IDEMPOTENT: this feature is strictly optional. It allows the slave to skip errors. Although it can be useful to make sure that slave replication does not stop due to an error, it can be dangerous, as it can cause the slave to desynchronize from the master, resulting in a different data set on each server. Use of InnoDB tables and transactions and rollbacks can help limit this possibility.
Once the my.cnf file is set up, each server needs to have the replication user granted access for replication and set to point at the master database:
server A mysql> GRANT REPLICATION CLIENT, REPLICATION SLAVE, SELECT, FILE, PROCESS, SUPER RELOAD ON *.* TO 'replication'@'%s' identified by 'replpass'; server A mysql> flush privileges; server A mysql> change master to MASTER_HOST="serverB.example.com", MASTER_USER="replication", MASTER_PASSWORD='replpass'; server A mysql> start slave; server B mysql> GRANT REPLICATION CLIENT ... ; (as above) server B mysql> flush privileges; server B mysql> change master to MASTER_HOST="serverC.example.com", MASTER_USER="replication", MASTER_PASSWORD='replpass'; server B mysql> start slave; server C mysql> GRANT REPLICATION CLIENT ... ; (as above) server C mysql> flush privileges; server C mysql> change master to MASTER_HOST="serverA.example.com", MASTER_USER="replication", MASTER_PASSWORD='replpass'; server C mysql> start slave;
In this scenario, server A gets data from server B, which gets data from server C, which gets data circularly from server A. Data can be inserted into any of the three servers and will be replicated to the other two. This doesn't speed up writes (except possibly for additional drive spindles), but it can add additional speed for reads if the application rotates between servers in the cluster. In addition, if there is hardware failure, the highly available nature of the cluster contains copies of data. Removing a dead slave can be as simple as using the “change master” statement to point at the grandfather server or replacing the dead server and simply copying a snapshot of the data.
In contrast to the loosely bound multimaster replication, NDB clusters can be viewed as a single entity. In fact, they're so tightly coupled, an NDB cluster entity can be used as a single server in a multimaster replication scenario. Although NDB is a huge advantage in terms of cluster synchronicity and management, the NDB engine does not support all the features of other MySQL engines, and the NDB engine is the only one that can be used in an NDB cluster. The NDB engine does not support savepoints within MySQL and, thus, cannot support transactions and rollbacks. As a result of this, when an ALTER TABLE or CREATE TABLE command is issued, the table being altered should not be accessed. Although it locks the table on the current node, this is a local lock only and may cause data integrity problems or even crashes if the table is accessed on another node.
Before setting up software for an NDB cluster, hardware is a concern. Because the clusters can act as a synchronous unit and there is no encryption built in to the package, a private network or VLAN is a best practice to employ. If the idea is to use NDB in a Web application, the inter-database links should be separated from the links that are used to execute queries.
Networking in an NDB cluster can be set up in a number of different ways, but most users prefer standard TCP-over-Gigabit or higher-speed networks. 100Mbit networks will work, but they will be far less efficient for larger systems. 10Mbit networks are not supported. Although the replication configuration requires only the MySQL servers to be part of the setup, NDB requires management nodes and data nodes in addition to the MySQL servers. All of these should demonstrate the lowest latency possible. Jumbo frames also are a good idea on Gigabit networks, because fitting as much data into the packet as possible decreases the possibility of any kind of errors interrupting the synchronous transfer of data between NDB nodes.
In addition to networks, increased RAM is a necessity as caching becomes more of a priority to decrease network traffic. The best way to increase IO to disk is to increase spindles. Adding more, smaller disks will increase the IO throughput of any given node, but this is especially important on the data nodes, because these are the ones that have the actual data on disk. Increasing the number of data nodes also will increase the read speed of the cluster as a whole, but it will not increase the write speed significantly. If the database is behind a Web server, the read-to-write ratio is usually so high, this is exactly the kind of performance that is good for the application. If most of the application's queries are for writing data, focusing on the speed of single nodes is the best strategy.
Before setting up the configuration for an NDB cluster, be sure that it is available in your distribution on MySQL. The show engines command should include an engine type of NDBCLUSTER with the Support column set to Yes. If this is not available, check your distribution for an external package, or install or compile the community package from www.mysql.com.
The NDB configuration has three types of servers. The management server does configuration and monitoring of the cluster via the ndb_mgmd dæmon. The data nodes store the data running the ndbd dæmon, and the SQL nodes run the mysqld server itself. Although it is possible to run multiple types of dæmons on the same physical servers, it is not recommended in a production environment. The best practice is to separate all of them onto their own pieces of hardware.
NDB clusters consist of two configuration files. The first file, my.cnf, is the standard configuration file for MySQL. The second file, config.ini, is read only by the management server. The config.ini file includes configuration for the data nodes and is passed to them by the management server.
The additions to the my.cnf file are fairly straightforward:
[ndb_mgm] ndb-connectstring=manage.example.com:1186 # The management server [ndb_mgmd] config-file=/etc/config.ini [ndbd] ndb-connectstring=manage.example.com:1186 # The management server [mysqld] ndbcluster # This turns the cluster on ndb-force-send=1 # Sends buffers immediately ndb-index-stat-enable=1 # Optimizes queries with NDB # index statistics engine-condition-pushdown=1 [mysql_cluster] ndb-connectstring=manage.example.com:1186 # The management server
The engine-condition-pushdown option forces MySQL to send the query directly to the storage engine instead of evaluating it in the mysql dæmon. In an NDB cluster, this allows the NDB engine to spread queries across multiple data nodes.
A basic config.ini file also is fairly easy to write. It must be placed in the location specified by the config-file line in the my.cnf file:
# Management Node [ndb_mgmd default] DataDir=/var/lib/mysql-cluster # This is where the management # server keeps data [ndb_mgmd] HostName=manage.example.com # The machine's hostname [ndbd default] NoOfReplicas=2 # There are 2 data nodes [ndbd] HostName=datanode.example.com # The machine's hostname [mysqld] HostName=datanode.example.com # The machine's hostname DataDir=/var/lib/mysql # This is where the data # node keeps data
In this scenario, there are three servers, one of each type: a management server, a data node and an SQL node. Queries are sent to the SQL server, which then interoperates with the data nodes. Because the SQL servers can talk to multiple data nodes as necessary with the optimizer inside the NDB engine (set via the engine-condition-push variable above), this type of replication can operate on some SELECT queries far faster than the multimaster replication setup discussed above. On the other hand, NDB uses synchronous replication, so queries that write data, such as INSERTs and UPDATEs, can take longer, because the data must be written to each node on the cluster.
The problem of extending systems across various locations is well known in the industry. With Web servers and static content, this is a fairly simple situation. With cacheable content, this can be done using various caching services.
Dealing with MySQL across multiple geographies is complex at best. It is not reasonable to set up an NDB cluster with nodes in separate data centers. Even if there is dedicated bandwidth between the boxes in the cluster, the latency across the link will cause large delays in issuing write commands to the system.
The accepted way to set up a multi-geography NDB cluster is to have two separate NDB clusters, one per data center, and set up an asynchronous multimaster (or master-slave for failover only) replication system between the two. To do this, set up NDB clusters normally, add the auto_increment statements to the my.cnf file, add replication user permissions, and issue the “change master” statement at the MySQL prompt.
This asynchronous relationship between geographies will create a great way to distribute your load across the systems, but it is still asynchronous. There can be cases where queries will return different results from the different locations where the data has not yet completed replication. If the application is a Web site showing photographs, this is generally not a problem. If the application is a bank, this inconsistency could result in large problems.
Building a MySQL cluster, either using replication or NDB clusters, is a difficult task to get right the first time. Doing it in a hurry or with existing data in the system makes it even harder. Setting up a few systems as a test lab is a necessity. Although virtual machines are a good platform for setting up the configuration of the system, testing end-to-end performance also is a necessity in order to verify that the application will not suffer from poor database performance. This requires time on the actual hardware with the actual data and, if possible, a file full of actual queries run on the system. Multi-geography setups are even more difficult with a small budget, and it is good practice to think hard about the operational expense of running a second location compared to the cost of downtime. Finally, as good as your replications and clusters are, they are not a substitute for backups. Save early; save often.
Michael Nugent has spent a good deal of his time designing large-scale solutions to fit into tiny budgets, leveraging Linux to fulfill the roles that typically would be filled by large commercial appliances. Recently, Michael has been working to design large multi-geography database solutions for growing startups in the Silicon Valley area. When not building systems, he likes sailing, MIG welding and hanging out with his cat, MIDI. Michael can be reached at firstname.lastname@example.org.
Fast/Flexible Linux OS Recovery
On Demand Now
In this live one-hour webinar, learn how to enhance your existing backup strategies for complete disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible full-system recovery solution for UNIX and Linux systems.
Join Linux Journal's Shawn Powers and David Huffman, President/CEO, Storix, Inc.
Free to Linux Journal readers.Register Now!
- Download "Linux Management with Red Hat Satellite: Measuring Business Impact and ROI"
- Profiles and RC Files
- Astronomy for KDE
- Understanding Ceph and Its Place in the Market
- Maru OS Brings Debian to Your Phone
- Git 2.9 Released
- OpenSwitch Finds a New Home
- SoftMaker FreeOffice
- What's Our Next Fight?
- The Giant Zero, Part 0.x
With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide