Database Replication with Slony-I
Database management systems have been a crucial component of infrastructures for many years now. PostgreSQL is an advanced, object-relational database management system that is frequently used to provide such services. Although this database management system has proven to be stable for many years, the two available open-source replication solutions, rserv and ERServer, had serious limitations and needed replacement.
Fortunately, such a replacement recently became available. Slony-I is a trigger-based master to multiple slaves replication system for PostgreSQL being developed by Jan Wieck. This enterprise-level replication solution works asynchronously and offers all key features required by data centers. Among the key Slony-I usage scenarios are:
Database replication from the head office to various branches to reduce bandwidth usage or speed up database requests.
Database replication to offer load balancing in all instances. This can be particularly useful for report generators or dynamic Web sites.
Database replication to offer high availability of database services.
Hot backup using a standby server or upgrades to a new release of PostgreSQL.
This article walks you through the steps required to install Slony-I and replicate a simple database located on the same machine. It also describes how Slony-I can be combined with high-availability solutions to provide automatic failover.
To install Slony-I and replicate a simple database, first install PostgreSQL from source. Slony-I supports PostgreSQL 7.3.2 or higher; 7.4.x and 8.0 need the location of the PostgreSQL source tree when being compiled. If you prefer using PostgreSQL packages from your favorite distribution, simply rebuild them from the package sources and keep the package build location intact so it can be used when compiling Slony-I. That said, obtain the latest Slony-I release, which is 1.0.5, compile and install it. To do so, proceed with the following commands:
% tar -zxvf slony1-1.0.5.tar.gz % cd slony1-1.0.5 % ./configure \ --with-pgsourcetree=/usr/src/redhat/BUILD/postgresql-7.4.5 % make install
In this example, we tell the Slony-I's configure script to look in /usr/src/redhat/BUILD/postgresql-7.4.5/ for the location of the PostgreSQL sources, the directory used when building the PostgreSQL 7.4.5 RPMs on Red Hat Enterprise Linux. The last command compiles Slony-I and installs the following files:
$postgresql_bindir/slonik: the administration and configuration script utility of Slony-I. slonik is a simple tool, usually embedded in shell scripts, used to modify Slony-I replication systems. It supports its own format-free command language described in detail in the Slonik Command Summary document.
$postgresql_bindir/slon: the main replication engine. This multithreaded engine makes use of information from the replication schema to communicate with other engines, creating the distributed replication system.
$postgresql_libdir/slony1_funcs.so: the C functions and triggers.
$postgresql_libdir/xxid.so: additional datatype to store transaction IDs safely.
$postgresql_datadir/slony1_base.sql: replication schema.
$postgresql_datadir/slony1_funcs.sql: replication functions.
$postgresql_datadir/xxid.v73.sql: a script used to load the additional datatype previously defined.
Generally, $postgresql_bindir points to /usr/bin/, $postgresql_libdir to /usr/lib/pgsql/ and $postgresql_datadir to /usr/share/pgsql/. Use the pg_config --configure command to display the parameters used when PostgreSQL was built to find the various locations for your own installation. Those files are all that is needed to offer a complete replication engine for PostgreSQL.
As you can see in Figure 1, Slony-I's main replication engine, slon, makes use of many threads. The synchronization thread verifies at a configurable interval if there has been replicable database activity, generating SYNC events if such activity happens. The local listen thread listens for new configuration events and modifies the cluster configuration and the in-memory configuration of the slon process accordingly.
As its name implies, the cleanup thread performs maintenance on the Slony-I schema, like removing old events or vacuuming the tables. The remote listen thread connects to the remote node's database to receive events from its event provider. When it receives events or confirmations, it selects the corresponding information and feeds the internal message queue of the remote workers thread. The replication data is combined into groups of transactions. The remote workers thread, one per remote node, does the actual data replication, events storing and generation of confirmations. At any moment, the slave knows exactly what groups of transactions it has consumed.
|Speed Up Your Web Site with Varnish||Jun 19, 2013|
|Non-Linux FOSS: libnotify, OS X Style||Jun 18, 2013|
|Containers—Not Virtual Machines—Are the Future Cloud||Jun 17, 2013|
|Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer||Jun 12, 2013|
|Weechat, Irssi's Little Brother||Jun 11, 2013|
|One Tail Just Isn't Enough||Jun 07, 2013|
- Speed Up Your Web Site with Varnish
- Containers—Not Virtual Machines—Are the Future Cloud
- Linux Systems Administrator
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Non-Linux FOSS: libnotify, OS X Style
- Senior Perl Developer
- Technical Support Rep
- UX Designer
- RSS Feeds
- Reply to comment | Linux Journal
1 hour 49 min ago
- Yeah, user namespaces are
3 hours 6 min ago
- Cari Uang
6 hours 37 min ago
- user namespaces
9 hours 30 min ago
9 hours 56 min ago
- One advantage with VMs
12 hours 25 min ago
- about info
12 hours 58 min ago
12 hours 59 min ago
13 hours 14 sec ago
13 hours 2 min ago
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?