# $OpenLDAP: pkg/openldap-guide/admin/tuning.sdf,v 1.8.2.2 2007/01/02 21:43:43 kurt Exp $ # Copyright 1999-2007 The OpenLDAP Foundation, All Rights Reserved. # COPYING RESTRICTIONS APPLY, see COPYRIGHT. H1: Performance Tuning Note: this chapter needs to be updated to discuss BDB tuning. There are several things you can do to tune the performance of slapd for your system. Most of them have to do with the LDBM backend. LDBM uses an index mechanism to store and retrieve information in slapd. Each entry is assigned a unique ID, used to refer to the entry in the indexes. A search for entries with a surname of "Jensen", for example, would look up the index entry "=JENSEN" in the surname index. The data returned is a list of IDs of entries having that value for the surname attribute. We have found several things to be useful in improving the performance of this indexing scheme, especially on modify operations. H2: The allIDs threshold Some index entries become so large as to be useless. For example, if every entry in your database is a person entry, the "=PERSON" index entry in the objectclass index contains every entry. This returns very little useful information, and can cause significant delays, especially on updates. To alleviate this problem, we have introduced the idea of an allIDs index entry. The allIDs entry stands for a real index entry containing the IDs of every entry in the database, but it takes up very little space, never needs updating, and can be manipulated quickly and efficiently. The trade-off is that it does not prune the set of candidate entries at all during a search. This must be done using other, more "high-powered" index entries. You can set the minimum number of IDs that an index entry may contain before it turns into an allIDs block by changing the {{EX: SLAPD_LDBM_MIN_MAXIDS}} variable in the {{EX: include/ldapconfig.h}} file. The actual number is determined at runtime by the LDBM backend, depending on the block size of the underlying device (i.e., the number you provide is rounded up to the nearest multiple of a block size). H2: The entry cache The LDBM backend can be configured to keep a cache of entries in memory. Since the LDBM database spends much of its time reading entries from the id2entry file into memory, this cache can greatly speed performance. The trade-off is that the cache uses some extra memory. The default cache size is 1000 entries. See the discussion of the cachesize option in Section 5.2.3 on LDBM configuration. H2: The DB cache The LDBM backend uses a number of disk-based index files. If the underlying hash or B-tree package supports in-memory caching of these files, performance can be greatly improved, especially on modifies. The size of this in-memory file cache is given by the dbcachesize option, discussed in more detail in section 5.2.3 on LDBM configuration. The default {{EX: dbcachesize}} is 100K. H2: Maintain the right indices Finally, one of the best performance tune-ups you can do is to make sure you are maintaining the right indices. Too few indices can lead to poor search performance. Too many indices can lead to poor update performance. For example, the LDBM backend would be perfectly happy to maintain substring and approximate indices for the {{EX: objectclass attribute}}, but this would not be useful and would just slow down update operations. If your database has many entries and is handling queries for substring equality on the surname attribute, you should make sure to maintain a surname substring index so these queries are answered quickly. So, take a look at the index lines in your slapd configuration file to ensure that only those indices that make sense and are needed are being maintained.