[Zodb-checkins] CVS: ZODB3/Doc - BDBStorage.txt:1.1
Barry Warsaw
barry@wooz.org
Tue, 7 Jan 2003 15:35:46 -0500
Update of /cvs-repository/ZODB3/Doc
In directory cvs.zope.org:/tmp/cvs-serv3219
Added Files:
BDBStorage.txt
Log Message:
Readme for BDBStorages
=== Added File ZODB3/Doc/BDBStorage.txt ===
BerkeleyDB Storages for ZODB
============================
Introduction
------------
The BDBStorage package contains two types of ZODB storages based on
Sleepycat Software's BerkeleyDB library, and the PyBSDDB3 Python
wrapper module. These storages save ZODB data to a number of
BerkeleyDB tables, relying on BerkeleyDB's transaction machinery to
provide reliability and recoverability.
Note that the BerkeleyDB based storages are not "set and forget". The
underlying Berkeley database technology requires maintenance, careful
system resource planning, and tuning for performance. You should have
a good working familiarity with BerkeleyDB in general before trying to
use these storages in a production environment. It's a good idea to
read Sleepycat's own documentation, available at
http://www.sleepycat.com
See also our operating notes below.
Contents
--------
Inside the BDBStorage package, there are two storage implementations:
- BDBFullStorage.py is a complete storage implementation, supporting
transactional undo, versions, application level conflict resolution,
packing, and automatic reference counting garbage collection. You
must pack this storage in order to get rid of old object revisions,
but there is also a new "autopack" strategy which packs the storage
in a separate thread and can eliminate the need for an explicit
manual pack operation.
- BDBMinimalStorage.py is an implementation of an undo-less,
version-less storage, which implements a reference counting garbage
collection strategy to remove unused objects. It is still possible
for garbage objects to persist in the face of object cycles,
but this storage too implements an autopack strategy.
Compatibility
-------------
As of this writing (07-Jan-2003), these storages have been tested with
Python 2.1.3, Python 2.2.2, and Python 2.3a1. When used with Python
2.1 or 2.2, you must use the distutils PyBSDDB package (see below),
however with Python 2.3, these storages use the standard Python bsddb
package (which is essentially a port of the PyBSDDB package).
Some testing has been conducted with Zopes as far back as 2.4.3 and as
far forward as Zope 3 alpha 1. These storages have primarily been
tested on Linux.
It is recommended that you use BerkeleyDB 4.1.25, and if you are using
Python 2.1 or 2.2, PyBSDDB 3.4.1 or later. BDBStorage will not work
with any BerkeleyDB version before 3.3.11 so be careful if your Python
or PyBSDDB is linking against earlier BerkeleyDB 3.x versions. If you
are using BerkeleyDB 4.0.14, it is highly recommended that you apply
the patch for 4.0.14 in the file
db-4014-patch.txt
We've seen corrupt databases that couldn't be recovered without this
patch. Sleepycat claims the patch fixes this problem and we've not
seen a repeat of it since applying the patch (note though that this
bug was hard to reproduce in the first place).
Requirements
------------
You must install Sleepycat BerkeleyDB and perhaps PyBSDDB separately.
To obtain the BerkeleyDB 4.1.25, see the Sleepycat download page::
http://www.sleepycat.com/download.html
If you're using a version of Python before 2.3, you'll need the latest
release of PyBSDDB, which you can get from::
http://pybsddb.sourceforge.net
You do not need this if you are using Python 2.3.
Install both BerkeleyDB and PyBSDDB as per the instructions that come
with those packages. For BerkeleyDB, it's generally wise to accept
the default configure options and do a "make install" as root. This
will install BerkeleyDB in /usr/local/BerkeleyDB.4.1
Note that because Berkeley installs itself in a non-standard location,
the dynamic linker ld.so may not be able to find it. This could
result in link errors during application startup. For systems that
support ldconfig, it is highly recommended that you add
/usr/local/BerkeleyDB.4.1/lib to /etc/ld.so.conf and run ldconfig.
PyBSDDB comes with a standard distutils-based setup script which will
do the right thing.
If you've extended your ld.so.conf file as above, you can build
PyBSDDB like so::
% python setup.py install
You may want to run the PyBSDDB test suite too. See its documentation
for details.
Using BDBStorage with Zope2
---------------------------
By default, Zope uses a FileStorage as its backend storage. To tell
Zope to use an alternate storage, you need to set up a custom_zodb.py
file.
There is a sample bdbstorage_custom_zodb.py file in the Docs/
subdirectory, shipped with this release. The easiest way to get
started with one of the BerkeleyDB storages is to copy
bdbstorage_custom_zodb.py to SOFTWARE_HOME/custom_zodb.py directory
(your main Zope dir) and edit its contents to specify which storage
you want to use. If you use an INSTANCE_HOME setup, you'll want to
copy the file to the INSTANCE_HOME directory instead and do the same.
If you choose to edit the contents of the custom_zodb.py file, you can
change the envpath variable to point to a different environment
directory for BerkeleyDB. BerkeleyDB will store its support tables
and log files in this directory. The contents of this directory can
become quite large, even if your data needs are relatively modest (see
"BerkeleyDB Log Files" below).
You can also set up some tuning paramaters in the custom_zodb.py file.
See the comments below and the BerkeleyBase.py file for details. For
better performance, you should consider at least setting the
config.logdir to point to a directory on a different disk than the one
your tables are stored on.
By default, the environment path is set in custom_zodb.py to a
subdirectory of your Zope's var subdirectory. You may change this to
any path that you have write permissions on. If the environment
directory doesn't exist, it will be created when you first run Zope
with one of the storages. It is recommended that you choose an
environment directory which does not contain any other files.
Additionally, you should not use BerkeleyDB on remotely mounted
filesystems such as NFS.
Using BDBStorage with ZEO
-------------------------
The BerkeleyDB storages are compatible with ZEO. For general
information on how to use alternate storage implementations with ZEO,
see the "start.txt" file in the ZEO documentation.
Using Berkeley storage outside of Zope
--------------------------------------
ZODB applications that use the BerkeleyDB storages need to take care
to close the database gracefully, otherwise the underlying database
could be left in a corrupt, but recoverable, state.
By default, all the BerkeleyDB storages open their databases with the
DB_RECOVER flag, meaning if recovery is necessary (e.g. because you
didn't explicitly close it the last time you opened it), then recover
will be run automatically on database open. You can also manually
recover the database by running Berkeley's db_recover program.
The upshot of this is that a database which was not gracefully closed
can usually be recovered automatically, but this could greatly
increase the time it takes to open the databases. This can be
mitigated by periodically checkpointing, since recovery only needs to
take place from the time of the last checkpoint. The database is
always checkpointed when it's closed cleanly.
You can configure the BerkeleyDB storages to automatically checkpoint
the database every so often, by using the BerkeleyConfig class. The
"interval" setting determines how often, in terms of ZODB commits,
that the underlying database will be checkpointed. See the class
docstring for BerkeleyBase.BerkeleyConfig for details.
BerkeleyDB files
----------------
After Zope is started with one of the BerkeleyDB storages, you will
see a number of different types of files in your BerkeleyDB
environment directory. There will be a number of "__db*" files, a
number of "log.*" files, and several files which have the prefix
``zodb_``. The files which have the ``zodb_`` prefix are the actual
BerkeleyDB databases which hold the storage data. The "log.*" files
are write-ahead logs for BerkeleyDB transactions, and they are very
important. The "__db*" files are working files for BerkeleyDB, and
they are less important. It's wise to back up all the files in this
directory regularly. BerkeleyDB supports "hot-backup". Log files
need to be archived and cleared on a regular basis (see below).
You really want to store your database files on a file system with
large file support. See below for details.
BerkeleyDB log files
--------------------
BerkeleyDB is a transactional database system. In order to maintain
transactional integrity, BerkeleyDB writes data to log files before
the data is committed. These log files live in the BerkeleyDB
environment directory unless you take steps to configure your
BerkeleyDB environment differently. There are good reasons to put the
log files on a different disk than the data files:
- The performance win can be huge. By separating the log and data
files, Berkeley can much more efficiently write data to disk. We
have seen performance improvements from between 2.5 and 10 times for
write intensive operations. You might also want to consider using
three separate disks, one for the log files, one for the data files,
and one for the OS swap.
- The log files can be huge. It might make disk space management
easier by separating the log and data files.
The log file directory can be changed by setting the "logfile"
attribute on the config object given to the various storage
constructors. Set this to the directory where BerkeleyDB should store
your log files. Note that this directory must already exist.
For more information about BerkeleyDB log files, recoverability and
why it is advantageous to put your log files and your database files
on separate devices, see
http://www.sleepycat.com/docs/ref/transapp/reclimit.html.
You can reclaim some disk space by occasionally backing up and
removing unnecessary BerkeleyDB log files. Here's a trick that I use::
% db_archive | xargs rm
Be sure to read the db_archive manpages first!
Tuning BerkeleyDB
-----------------
BerkeleyDB has lots of knobs you can twist to tune it for your
application. Getting most of these knobs at the right setting is an
art, and will be different from system to system. You should at least
read the following Sleepycat pages::
http://www.sleepycat.com/docs/ref/am_conf/cachesize.html
http://www.sleepycat.com/docs/ref/am_misc/tune.html
http://www.sleepycat.com/docs/ref/transapp/tune.html
http://www.sleepycat.com/docs/ref/transapp/throughput.html
As you read these, it will be helpful to know that the BDBStorages
mostly use BTree access method, although there are a few Queue tables
to support packing.
One thing we can safely say is that the default BerkeleyDB cache size
of 256KB is way too low to be useful. The BerkeleyDB storages
themselves default the cache size to 128MB which seems about optimal
on a 256MB machine. Be careful setting this too high though, as
performance will degrade if you tell BerkeleyDB to consume more than
the available resources. You can change the cache size by setting the
"cachesize" attribute on the config object to the constructor.
Archival and maintenance
------------------------
Log file rotation for BerkeleyDB is closely related to database
archival.
BerkeleyDB never deletes "old" log files. Eventually, if you do not
maintain your Berkeley database by deleting "old" log files, you will
run out of disk space. It's necessary to maintain and archive your
BerkeleyDB files as per the procedures outlined in
http://www.sleepycat.com/docs/ref/transapp/archival.html
It is advantageous to automate this process, perhaps by creating a
script run by "cron" that makes use of the "db_archive" executable as
per the referenced document. One strategy might be to perform the
following sequence of operations::
- shut down the process which is using BerkeleyDB (Zope or the ZEO
storage server).
- back up the database files (the files prefixed with "zodb_").
- back up all existing BerkeleyDB log files (the files prefixed
"log").
- run ``db_archive -h /the/environment/directory`` against your
environment directory to find out which log files are no longer
participating in transactions (they will be printed to stdout one
file per line).
- delete the log files that were reported by "db_archive" as no longer
participating in any transactions.
"Hot" backup and rotation of log files is slightly different. See the
above-referenced link regarding archival for more information.
Disaster recovery
-----------------
To recover from an out-of-disk-space error on the log file partition,
or another recoverable failure which causes the storage to raise a
fatal exception, you may need to use the BerkeleyDB "db_recover"
executable. For more information, see the BerkeleyDB documentation
at::
http://www.sleepycat.com/docs/ref/transapp/recovery.html
BerkeleyDB temporary files
--------------------------
BerkeleyDB creates temporary files in the directory referenced by the
$TMPDIR environment variable. If you do not have a $TMPDIR set, your
temp files will be created somewhere else (see
http://www.sleepycat.com/docs/api_c/env_set_tmp_dir.html for the
tempfile decision algorithm used by BerkeleyDB). These temporary
files are different than BerkeleyDB "log" files, but they can also
become quite large. Make sure you have plenty of temp space
available.
Linux 2GB Limit
---------------
BerkeleyDB is effected by the 2GB single-file-size limit on 32-bit
Linux ext2-based systems. The Berkeley storage pickle database (by
default named "zodb_pickle"), which holds the bulk of the data for the
Berkeley storages is particularly susceptible to large growth.
If you anticipate your database growing larger than 2GB, it's
worthwhile to make sure your system can support files larger than 2GB.
Start with your operating system and file system. Most modern Linux
distributions have large file support.
Next, you need to make sure that your Python executable has large file
support (LFS) built in. Python 2.2.2 and beyond is automatically
configured with LFS, but for Python 2.1.3 you will need to rebuild
your executable according to the instructions on this page:
http://www.python.org/doc/2.1.3/lib/posix-large-files.html
IMPORTANT NOTE: If any of your BerkeleyDB files reaches the 2GB limit
before you notice the failure situation, you will most likely need to
restore the database environment from a backup, putting the restored
files on a filesystem which can handle large files. This is due to
the fact that the database file which "hit the limit" on a 2GB-limited
filesystem will be left in an inconsistent state, and will probably be
rendered unusable. Be very cautious if you're dealing with large
databases.
For More Information
--------------------
Information about ZODB in general is kept on the ZODB Wiki at
http://www.zope.org/Wikis/ZODB
Information about the BerkeleyDB storages in particular is at
http://www.zope.org/Wikis/ZODB/BerkeleyStorage
The email list zodb-dev@lists.zope.org are where all the
discussion about the Berkeley storages should take place.
Subscribe or view the archives at
http://lists.zope.org/mailman/listinfo/zodb-dev
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