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