It is often desirable to maintain multiple copies of a Xapian database, having a “master” database which modifications are made on, and a set of secondary (read-only, “slave”) databases which these modifications propagate to. For example, to support a high query load there may be many search servers, each with a local copy of the database, and a single indexing server. In order to allow scaling to a large number of search servers, with large databases and frequent updates, we need an database replication implementation to have the following characteristics:
- Data transfer is (at most) proportional to the size of the updates, rather than the size of the database, to allow frequent small updates to large databases to be replicated efficiently.
- Searching (on the slave databases) and indexing (on the master database) can continue during synchronisation.
- Data cached (in memory) on the slave databases is not discarded (unless it’s actually out of date) as updates arrive, to ensure that searches continue to be performed quickly during and after updates.
- Synchronising each slave database involves low overhead (both IO and CPU) on the server holding the master database, so that many slaves can be updated from a single master without overloading it.
- Database synchronisation can be recovered after network outages or server failures without manual intervention and without excessive data transfer.
The database replication protocol is intended to support replicating a single writable database to multiple (read-only) search servers, while satisfying all of the above properties. It is not intended to support replication of multiple writable databases - there must always be a single master database to which all modifications are made.
Replication is supported by the chert and glass database backends, and can cleanly handle the master switching database type (a full copy is sent in this situation). It doesn’t make a lot of sense to support replication for the remote backend. Replication of inmemory databases isn’t currently available.
Setting up replicated databases¶
To replicate a database efficiently from one master machine to other machines, there is one configuration step to be performed on the master machine, and two servers to run.
Firstly, on the master machine, the indexer must be run with the environment variable XAPIAN_MAX_CHANGESETS set to a non-zero value, which will cause changeset files to be created whenever a transaction is committed. A changeset file allows the transaction to be replayed efficiently on a replica of the database.
The value which XAPIAN_MAX_CHANGESETS is set to determines the maximum number of changeset files which will be kept. The best number to keep depends on how frequently you run replication and how big your transactions are - if not all the changeset files needed to update a replica are present, a full copy of the database will be sent, but at some point this becomes more efficient anyway. 10 is probably a good value to start with.
Secondly, also on the master machine, run the xapian-replicate-server server to serve the databases which are to be replicated. This takes various parameters to control the directory that databases are found in, and the network interface to serve on. The –help option will cause usage information to be displayed. For example, if /var/search/dbs contains a set of Xapian databases to be replicated:
xapian-replicate-server /var/search/dbs -p 7010
would run a server allowing access to these databases, on port 7010.
Finally, on the client machine, run the xapian-replicate server to keep an individual database up-to-date. This will contact the server on the specified host and port, and copy the database with the name (on the master) specified in the -m option to the client. One non-option argument is required - this is the name that the database should be stored in on the slave machine. For example, contacting the above server from the same machine:
xapian-replicate -h 127.0.0.1 -p 7010 -m foo foo2
would produce a database “foo2” containing a replica of the database “/var/search/dbs/foo”. Note that the first time you run this, this command will create the foo2 directory and populate it with appropriate files; you should not create this directory yourself.
As of 1.2.5, if you don’t specify the master name, the same name is used remotely and locally, so this will replicate remote database “foo2” to local database “foo2”:
xapian-replicate -h 127.0.0.1 -p 7010 foo2
Both the server and client can be run in “one-shot” mode, by passing -o. This may be particularly useful for the client, to allow a shell script to be used to cycle through a set of databases, updating each in turn (and then probably sleeping for a period).
It is possible to confuse the replication system in some cases, such that an invalid database will be produced on the client. However, this is easy to avoid in practice.
To confuse the replication system, the following needs to happen:
- Start with two databases, A and B.
- Start a replication of database A.
- While the replication is in progress, swap B in place of A (ie, by moving the files around, such that B is now at the path of A).
- While the replication is still in progress, swap A back in place of B.
If this happens, the replication process will not detect the change in database, and you are likely to end up with a database on the client which contains parts of A and B mixed together. You will need to delete the damaged database on the client, and re-run the replication.
To avoid this, simply avoid swapping a database back in place of another one. Or at least, if you must do this, wait until any replications in progress when you were using the original database have finished.
xapian.Database.reopen() is usually an efficient way to ensure that a
database is up-to-date with the latest changes. Unfortunately, it does not
currently work as you might expect with databases which are being updated by the
replication client. The workaround is simple; don’t use the
reopen() method on such databases: instead, you should
close the database and open it again from scratch.
Briefly, the issue is that the databases created by the replication client are
created in a subdirectory of the target path supplied to the client, rather
than at that path. A “stub database” file is then created in that directory,
pointing to the database. This allows the database which readers open to be
switched atomically after a database copy has occurred. The
reopen() method doesn’t re-read the stub database file in
this situation, so ends up attempting to read the old database which has been
We intend to fix this issue in the future by eliminating this hidden use of a stub database file.
Without using the database replication protocol, there are various ways in which the “single master, multiple slaves” setup could be implemented.
- Copy database from master to all slaves after each update, then swap the new database for the old.
- Synchronise databases from the master to the slaves using rsync.
- Keep copy of database on master from before each update, and use a binary diff algorithm (e.g., xdelta) to calculate the changes, and then apply these same changes to the databases on each slave.
- Serve database from master to slaves over NFS (or other remote file system).
- Use the “remote database backend” facility of Xapian to allow slave servers to search the database directly on the master.
All of these could be made to work but have various drawbacks, and fail to satisfy all the desired characteristics. Let’s examine them in detail:
Copying database after each update¶
Databases could be pushed to the slaves after each update simply by copying the entire database from the master (using scp, ftp, http or one of the many other transfer options). After the copy is completed, the new database would be made live by indirecting access through a stub database and switching what it points to.
After a sufficient interval to allow searches in progress on the old database to complete, the old database would be removed. (On UNIX filesystems, the old database could be unlinked immediately, and the resources used by it would be automatically freed as soon as the current searches using it complete.)
This approach has the advantage of simplicity, and also ensures that the databases can be correctly re-synchronised after network outages or hardware failure.
However, this approach would involve copying a large amount of data for each update, however small the update was. Also, because the search server would have to switch to access new files each time an update was pushed, the search server will be likely to experience poor performance due to commonly accessed pages falling out of the disk cache during the update. In particular, although some of the newly pushed data would be likely to be in the cache immediately after the update, if the combination of the old and new database sizes exceeds the size of the memory available on the search servers for caching, either some of the live database will be dropped from the cache resulting in poor performance during the update, or some of the new database will not initially be present in the cache after update.
Synchronise database using rsync¶
Rsync works by calculating hashes for the content on the client and the server, sending the hashes from the client to the server, and then calculating (on the server) which pieces of the file need to be sent to update the client. This results in a fairly low amount of network traffic, but puts a fairly high CPU load on the server. This would result in a large load being placed on the master server if a large number of slaves tried to synchronise with it.
Also, rsync will not reliably update the database in a manner which allows the database on a slave to be searched while being updated - therefore, a copy or snapshot of the database would need to be taken first to allow searches to continue (accessing the copy) while the database is being synchronised.
If a copy is used, the caching problems discussed in the previous section would apply again. If a snapshotting filesystem is used, it may be possible to take a read-only snapshot copy cheaply (and without encountering poor caching behaviour), but filesystems with support for this are not always available, and may require considerable effort to set up even if they are available.
Use a binary diff algorithm¶
If a copy of the database on the master before the update was kept, a binary diff algorithm (such as “xdelta”) could be used to compare the old and new versions of the database. This would produce a patch file which could be transferred to the slaves, and then applied - avoiding the need for specific calculations to be performed for each slave.
However, this requires a copy or snapshot to be taken on the master - which has the same problems as previously discussed. A copy or snapshot would also need to be taken on the slave, since a patch from xdelta couldn’t safely be applied to a live database.
Serve database from master to slaves over NFS¶
NFS allows a section of a filesystem to be exported to a remote host. Xapian is quite capable of searching a database which is exported in such a manner, and thus NFS can be used to quickly and easily share a database from the master to multiple slaves.
A reasonable setup might be to use a powerful machine with a fast disk as the master, and use that same machine as an NFS server. Then, multiple slaves can connect to that NFS server for searching the database. This setup is quite convenient, because it separates the indexing workload from the search workload to a reasonable extent, but may lead to performance problems.
There are two main problems which are likely to be encountered. Firstly, in order to work efficiently, NFS clients (or the OS filesystem layer above NFS) cache information read from the remote file system in memory. If there is insufficient memory available to cache the whole database in memory, searches will occasionally need to access parts of the database which are held only on the master server. Such searches will take a long time to complete, because the round-trip time for an access to a disk block on the master is typically a lot slower than the round-trip time for access to a local disk. Additionally, if the local network experiences problems, or the master server fails (or gets overloaded due to all the search requests), the searches will be unable to be completed.
Also, when a file is modified, the NFS protocol has no way of indicating that only a small set of blocks in the file have been modified. The caching is all implemented by NFS clients, which can do little other than check the file modification time periodically, and invalidate all cached blocks for the file if the modification time has changed. For the Linux client, the time between checks can be configured by setting the acregmin and acregmax mount options, but whatever these are set to, the whole file will be dropped from the cache when any modification is found.
This means that, after every update to the database on the master, searches on the slaves will have to fetch all the blocks required for their search across the network, which will likely result in extremely slow search times until the cache on the slaves gets populated properly again.
Use the “remote database backend” facility¶
Xapian has supported a “remote” database backend since the very early days of the project. This allows a search to be run against a database on a remote machine, which may seem to be exactly what we want. However, the “remote” database backend works by performing most of the work for a search on the remote end - in the situation we’re concerned with, this would mean that most of the work was performed on the master, while slaves remain largely idle.
The “remote” database backend is intended to allow a large database to be split, at the document level, between multiple hosts. This allows systems to be built which search a very large database with some degree of parallelism (and thus provide faster individual searches than a system searching a single database locally). In contrast, the database replication protocol is intended to allow a database to be copied to multiple machines to support a high concurrent search load (and thus to allow a higher throughput of searches).
In some cases (i.e., a very large database and a high concurrent search load) it may be perfectly reasonable to use both the database replication protocol in conjunction with the “remote” database backend to get both of these advantages - the two systems solve different problems.