mifluz in an hypothetical full text indexing system.
Mifluz is a full text indexing library.
--- The Detailed Node Listing ---
Internals
Compression
Reference
htdb_dump
htdb_stat
htdb_load
mifluzdump
mifluzload
mifluzsearch
mifluzdict
WordContext
WordList
WordDict
WordListOne
WordKey
WordKeyInfo
WordType
WordDBInfo
WordRecordInfo
WordRecord
WordReference
WordCursor
WordCursorOne
WordMonitor
Configuration
mifluz
First of all, mifluz is at beta stage.
This program is part of the GNU project, released under the aegis of GNU.
The purpose of mifluz is to provide a C++ library
to store a full text inverted index. To put it briefly, it allows
storage of occurrences of words in such a way that they can later
be searched. The basic idea of an inverted index is to associate
each unique word with a list of documents in which they appear.
This list can then be searched to locate the documents containing a
specific word.
Implementing a library that manages an inverted index is a very
easy task when there is a small number of words and documents. It
becomes a lot harder when dealing with a large number of words and
documents. mifluz has been designed with the further
upper limits in mind : 500 million documents, 100 giga words, 18
million document updates per day. In the present state of
mifluz, it is possible to store 100 giga words using
600 giga bytes. The best average insertion rate observed as of
today 4000 key/sec on a 1 giga byte index.
mifluz has two main characteristics : it is very
simple (one might say stupidly simple :-) and uses 100% of the size
of the indexed text for the index. It is simple because it provides
only a few basic functions. It does not contain document parsers
(HTML, PDF etc...). It does not contain a full text query parser.
It does not provide result display functions or other user friendly
stuff. It only provides functions to store word occurrences and
retrieve them. The fact that it uses 100% of the size of the
indexed text is rather atypical. Most well known full text indexing
systems only use 30%. The advantage mifluz has over
most full text indexing systems is that it is fully dynamic
(update, delete, insert), uses only a controlled amount of memory
while resolving a query, has higher upper limits and has a simple
storage scheme. This is achieved by consuming more disk space.
In the following figure you can see the place of
mifluz in an hypothetical full text indexing system.
QueryMifluzParser SwitchIndexermifluz.The following list shows all the constraints imposed by
mifluz. It can also be seen as a list of functions
provided by mifluz that is more general than the API
specification.
Now AvailableFutureConstraints and LimitationsAn atomic datum is something that must be manipulated as whole, with no possibility of splitting it into smaller parts. For instance a posting (Word, document identifier and position) is an atomic datum: to manipulate it in memory it has to reside completely in memory. By contrast a postings list is not atomic. Manipulating a postings list can be done without loading all the postings list in memory.
In all of the literature dealing with full text indexing a
collection of documents is considered to be a flat set of documents
containing words. Each document has a unique name. The inverted
index associates terms found in the documents with a list of unique
document names. 
We found it more interesting to consider that the document names have a hierarchical structure, just like path names in file systems. The main difference is that each component of the document name (think path name in file system) may contain terms.
As shown in the figure above we can consider that the first
component of the document name is the name of a collection, the
second the logical name of a set of documents within the
collection, the third the name of the document, the fourth the name
of a part of the document. 
This logical structure may be applied to URLs in the following
way : there is only one collection, it contains servers (document
sets) containing URLs (documents) containing tags such as TITLE
(document parts). 
This logical structure may be also be applied to databases in the following way : there is one collection for each database, it contains tables (document set) containing fields (document) containing records (document part).
What does this imply for full text indexing ? Instead of having only one dictionary to map the document name to a numerical identifier (this is needed to compress the postings for a term), we must have a dictionary for each level of the hierarchy.
Using the database example again:
When coding the document identifier in the postings for a term, we have to code a list of numerical identifiers instead of a single numerical identifier. Alternatively one could see the document identifier as an aribtrary precision number sliced in parts.
The advantage of this document naming scheme are:
uniq query operator can be trivially
implemented. This is mostly useful to answer a query such as : I
want URLs matching the word foo but I only want to see one URL for
a given server (avoid the problem of having the first 40 URLs for a
request on the same server).Of course, the suggested hierarchy semantic is not mandatory and may be redefined according to sorting needs. For instance a relevance ranking algorithm can lead to a relevance ranking number being inserted into the hierarchy.
The space overhead implied by this name scheme is quite small for databases and URL pools. The big dictionary for URL pools maps URL to identifiers. The dictionary for tags (TITLE etc..) is only 10-50 at most. The dictionary for site names (www.domain.com) will be ~1/100 of the dictionary for URLs, assuming you have 100 URLs for a given site. For databases the situation is even better: the big dictionary would be the dictionary mapping rowids to numerical identifiers. But since rowids are already numerical we don't need this. We only need the database name, field name and table name dictionaries and they are small. Since we are able to encode small numbers using only a few bits in postings, the overhead of hierarchical names is acceptable.
Efficient management of the data storage space is an important issue of the management of inverted indexes. The needs of an inverted index are very similar to the needs of a regular file system. We need:
All these functionalities are provided by file systems and
kernel services. Since we also wanted the mifluz
library to be portable we chose the Berkeley DB library that
implements all the services above. The transparent compression is
not part of Berkeley DB and is implemented as a patch to Berkeley
DB (version 3.1.14).
Based on these low level services, Bekeley DB also implements a
Btree structure that mifluz used to store the
postings. Each posting is an entry in the Btree structure. Indexing
100 million words implies creating 100 million entries in the
Btree. When transparent compression is used and assuming we have 6
byte words and a document identifier using 7 * 8 bits, the average
disk size used per entry is 6 bytes.
Unique word statistics are also stored in the inverted index. For each unique word, an entry is created in a dictionnary and associated with a serial number (the word identifier and the total number of occurrences.
The cache memory used by mifluz has a tremendous
impact on performance. It is set by the
wordlist_cache_size attribute (see WordList(3) and
mifluz(3)). It holds pages from the inverted index in memory
(uncompressed if the file is compressed) to reduce disk access.
Pages migrate from disk to memory using a LRU.
Each page in the cache is really a node of the B-Tree used to
store the inverted index entries. The internal pages are
intermediate nodes that mifluz must traverse each time
a key is searched. It is therefore very important to keep them in
memory. Fortunately they only count for 1% of the total size of the
index, at most. The size of the cache must at least include enough
space for the internal pages.
The other factors that must be taken into account in sizing the cache are highly dependant on the application. A typical case is insertion of many random words in the index. In this case two factors are of special importance:
repartition of unique wordsThe general rule is : estimate or calculate how many unique
words fill 90% of your index. Multiply this number by the pagesize
and increase your cache by that amount. See
wordlist_page_size attribute in WordList(3) or
mifluz(3).
order of numbers following the keyfoo 100 foo 103
rather than
foo 103 foo 100
This hint must not be considered in isolation but with careful analysis of the distribution of the key components (word and numbers). For instance it does not matter much if a random key follows the word as long as the range of values of the number is small.
The conclusion is that the cache size should be at least 1% of the total index size (uncompressed) plus a number of bytes that depends on the usage pattern.
The key structure is what uniquely identifies each word that is inserted in the inverted index. A key is made of a string (which is the word being indexed), and a document identifier (which is really a list of numbers), as discussed above.
The exact structure of the inverted index key must be specified
in the configuration parameter
"wordlist_wordkey_description". See the WordKeyInfo(3)
manual page for more information on the format.
We will focus on three examples that illustrate common usage.
First example: a very simple inverted index would be to associate each word occurrence to an URL (coded as a 32 bit number). The key description would be:
Word 8/URL 32
Second example: if building a full text index of the content of a database, you need to know in which field, table and record the word appeared. This makes three numbers for the document id.
Only a few bits are needed to encode the field and table name (let's say you have a maximum of 16 field names and 16 table names, 4 bits each is enough). The record number uses 24 bits because we know we won't have more than 16 M records.
The structure of the key would then be:
Word 8/Table 4/Field 4/Record 32
When you have more than one field involved in a key you must chose the order in which they appear. It is mandatory that the Word is first. It is the part of the key that has highest precedence when sorting. The fields that follow have lower and lower precedence.
Third example: we go back to the first example and imagine we have a relevance ranking function that calculates a value for each word occurrence. By inserting this relevance ranking value in the inverted index key, all the occurrences will be sorted with the most relevant first.
Word 8/Rank 5/URL 32
Compressing the index reduces disk space consumption and speeds up the indexing by reducing I/O.
Compressing at the mifluz level would imply
choosing complicated key structures, slowing down and complexifying
insert and delete operations. We have chosen to do the compression
within Berkeley DB in the memory pool subsystem. Berkeley DB keeps
fixed size pages in a memory cache, when it is full it writes the
least recently used pages to disk. When a page is needed Berkeley
DB looks for it in memory and retrieves it from disk if its not in
memory. The compression/uncompression occurs when a page moves
between the memory pool and the disk. 
Berkeley DB uses fixed size pages. Suppose, for example that our
compression algorithm can compress by a factor of 8 in most cases,
we use a disk page size that's 1/8 of the memory page size. However
there are exceptions. Some pages won't compress well and therefore
won't fit on one disk page. Extra pages are therefore allocated and
are linked into a chained list. Allocating extra pages implies that
some pages may become free as a result of a better compression.
The mifluz classes WordDBCompress and
WordBitCompress do the compression/decompression work. From the
list of keys stored in a page it extracts several lists of numbers.
Each list of numbers has common statistical properties that allow
good compression.
The WordDBCompress_compress_c and WordDBCompress_uncompress_c functions are C callbacks that are called by the the page compression code in BerkeleyDB. The C callbacks then call the WordDBCompress compress/uncompress methods. The WordDBCompress creates a WordBitCompress object that acts as a buffer holding the compressed stream.
Compression algorithm.
Most DB pages contain redundant data because mifluz
chose to store one word occurrence per entry. Because of this
choice the pages have a very simple structure.
Here is a real world example of what a page can look like: (key structure: word identifier + 4 numerical fields)
756 1 4482 1 10b 756 1 4482 1 142 756 1 4484 1 40 756 1 449f 1 11e 756 1 4545 1 11 756 1 45d3 1 545 756 1 45e0 1 7e5 756 1 45e2 1 830 756 1 45e8 1 545 756 1 45fe 1 ec 756 1 4616 1 395 756 1 461a 1 1eb 756 1 4631 1 49 756 1 4634 1 48 .... etc ....
To compress we chose to only code differences between adjacent entries. A flag is stored for each entry indicating which fields have changed. When a field is different from the previous one, the compression stores the difference which is likely to be small since the entries are sorted.
The basic idea is to build columns of numbers, one for each field, and then compress them individually. One can see that the first and second columns will compress very well since all the values are the same. The third column will also compress well since the differences between the numbers are small, leading to a small set of numbers.
The development of mifluz is shared between
Senga (www.senga.org) and the Ht://dig
Group (dev.htdig.org). Part of the distribution comes from the
Ht://dig CVS tree and part from the Senga
CVS tree. The idea is to share efforts between two development
groups that have very similar needs. Since Senga and
Ht://dig are both developped under the GPL licence,
such cooperation occurs naturally.
To compile a program using the mifluz library use
something that looks like the following:
gcc -o word -I/usr/local/include -L/usr/local/lib -lmifluz word.cc
dump the content of an inverted index in Berkeley DB fashion
htdb_dump [-klNpWz] [-S pagesize] [-C cachesize] [-d ahr] [-f file] [-h home] [-s subdb] db_file
htdb_dump is a slightly modified version of the standard Berkeley DB db_dump utility.
The htdb_dump utility reads the database file
db_file and writes it to the standard output using
a portable flat-text format understood by the
htdb_load utility. The argument
db_file must be a file produced using the Berkeley
DB library functions.
Initialize WordContext(3) before dumping. With the
-z flag allows to dump inverted indexes using the
mifluz(3) specific compression scheme. The MIFLUZ_CONFIG
environment variable must be set to a file containing the mifluz(3)
configuration.
The db_file is compressed. If
-W is given the mifluz(3) specific compression
scheme is used. Otherwise the default gzip compression scheme is
used.
Dump the specified database in a format helpful for debugging the Berkeley DB library routines.
Display all information.
Display only page headers.
Do not display the free-list or pages on the free list. This mode is used by the recovery tests.
Write to the specified file instead of to the
standard output.
Specify a home directory for the database. As Berkeley DB
versions before 2.0 did not support the concept of a database
home.
Dump record numbers from Queue and Recno databases as
keys.
List the subdatabases stored in the database.
Do not acquire shared region locks while running. Other problems
such as potentially fatal errors in Berkeley DB will be ignored as
well. This option is intended only for debugging errors and should
not be used under any other circumstances.
If characters in either the key or data items are printing characters (as defined by isprint (3)), use printing characters in file to represent them. This option permits users to use standard text editors and tools to modify the contents of databases.
Note, different systems may have different notions as to what
characters are considered printing characters , and
databases dumped in this manner may be less portable to external
systems.
Specify a subdatabase to dump. If no subdatabase is specified,
all subdatabases found in the database are dumped.
Write the version number to the standard output and exit.
Dumping and reloading Hash databases that use user-defined hash functions will result in new databases that use the default hash function. While using the default hash function may not be optimal for the new database, it will continue to work correctly.
Dumping and reloading Btree databases that use user-defined prefix or comparison functions will result in new databases that use the default prefix and comparison functions. In this case, it is quite likely that the database will be damaged beyond repair permitting neither record storage or retrieval.
The only available workaround for either case is to modify the
sources for the htdb_load utility to load the database
using the correct hash, prefix and comparison functions.
DB_HOME If the -h option is not specified and the environment variable DB_HOME is set, it is used as the path of the database home.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
displays statistics for Berkeley DB environments.
htdb_stat [-celmNtzW] [-C Acfhlmo] [-d file [-s file]] [-h home] [-M Ahlm]
htdb_stat is a slightly modified version of the standard Berkeley DB db_stat utility which displays statistics for Berkeley DB environments.
Initialize WordContext(3) before gathering statistics. With the
-z flag allows to gather statistics on inverted
indexes generated with the mifluz(3) specific compression scheme.
The MIFLUZ_CONFIG environment variable must be set to a file
containing the mifluz(3) configuration.
The file is compressed. If -W
is given the mifluz(3) specific compression scheme is used.
Otherwise the default gzip compression scheme is used.
Display internal information about the lock region. (The output from this option is often both voluminous and meaningless, and is intended only for debugging.)
Display all information.
Display lock conflict matrix.
Display lock and object free lists.
Display lockers within hash chains.
Display region memory information.
Display objects within hash chains.
Display lock region statistics.
Display database statistics for the specified database. If the
database contains subdatabases, the statistics are for the database
or subdatabase specified, and not for the database as a
whole.
Display current environment statistics.
Specify a home directory for the database.
Display log region statistics.
Display internal information about the shared memory buffer pool. (The output from this option is often both voluminous and meaningless, and is intended only for debugging.)
Display all information.
Display buffers within hash chains.
Display buffers within LRU chains.
Display region memory information.
Display shared memory buffer pool statistics.
Do not acquire shared region locks while running. Other problems
such as potentially fatal errors in Berkeley DB will be ignored as
well. This option is intended only for debugging errors and should
not be used under any other circumstances.
Display database statistics for the specified subdatabase of the
database specified with the -d flag.
Display transaction region statistics.
Write the version number to the standard output and exit.
Only one set of statistics is displayed for each run, and the last option specifying a set of statistics takes precedence.
Values smaller than 10 million are generally displayed without any special notation. Values larger than 10 million are normally displayed as <number>M .
The htdb_stat utility attaches to one or more of the Berkeley DB shared memory regions. In order to avoid region corruption, it should always be given the chance to detach and exit gracefully. To cause htdb_stat to clean up after itself and exit, send it an interrupt signal (SIGINT).
DB_HOME If the -h option is not specified and the environment variable DB_HOME is set, it is used as the path of the database home.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
displays statistics for Berkeley DB environments.
htdb_load [-nTzW] [-c name=value] [-f file] [-h home] [-C cachesize] [-t btree | hash | recno] db_file
The htdb_load utility reads from the standard input and loads it into the database db_file . The database db_file is created if it does not already exist.
The input to htdb_load must be in the output format specified by the htdb_dump utility, or as specified for the -T below.
Initialize WordContext(3) before loading. With the
-z flag allows to load inverted indexes using the
mifluz(3) specific compression scheme. The MIFLUZ_CONFIG
environment variable must be set to a file containing the mifluz(3)
configuration.
The db_file is compressed. If
-W is given the mifluz(3) specific compression
scheme is used. Otherwise the default gzip compression scheme is
used.
Specify configuration options for the DB structure ignoring any
value they may have based on the input. The command-line format is
name=value . See Supported Keywords
for a list of supported words for the -c
option.
Read from the specified input file instead of
from the standard input.
Specify a home directory for the database. If a home directory
is specified, the database environment is opened using the
DB_INIT_LOCK , DB_INIT_LOG ,
DB_INIT_MPOOL , DB_INIT_TXN and
DB_USE_ENVIRON flags to DBENV->open. This means
that htdb_load can be used to load data into databases while they
are in use by other processes. If the DBENV->open call fails, or
if no home directory is specified, the database is still updated,
but the environment is ignored, e.g., no locking is done.
Do not overwrite existing keys in the database when loading into
an already existing database. If a key/data pair cannot be loaded
into the database for this reason, a warning message is displayed
on the standard error output and the key/data pair are
skipped.
The -T option allows non-Berkeley DB applications to easily load text files into databases.
If the database to be created is of type Btree or Hash, or the keyword keys is specified as set, the input must be paired lines of text, where the first line of the pair is the key item, and the second line of the pair is its corresponding data item. If the database to be created is of type Queue or Recno and the keywork keys is not set, the input must be lines of text, where each line is a new data item for the database.
A simple escape mechanism, where newline and backslash (\) characters are special, is applied to the text input. Newline characters are interpreted as record separators. Backslash characters in the text will be interpreted in one of two ways: if the backslash character precedes another backslash character, the pair will be interpreted as a literal backslash. If the backslash character precedes any other character, the two characters following the backslash will be interpreted as hexadecimal specification of a single character, e.g., \0a is a newline character in the ASCII character set.
For this reason, any backslash or newline characters that naturally occur in the text input must be escaped to avoid misinterpretation by htdb_load
If the -T option is specified, the underlying
access method type must be specified using the -t
option.
Specify the underlying access method. If no -t option is specified, the database will be loaded into a database of the same type as was dumped, e.g., a Hash database will be created if a Hash database was dumped.
Btree and Hash databases may be converted from one to the other.
Queue and Recno databases may be converted from one to the other.
If the -k option was specified on the call to
htdb_dump then Queue and Recno databases may be converted to Btree
or Hash, with the key being the integer record number.
Write the version number to the standard output and exit.
The htdb_load utility attaches to one or more of the Berkeley DB shared memory regions. In order to avoid region corruption, it should always be given the chance to detach and exit gracefully. To cause htdb_load to clean up after itself and exit, send it an interrupt signal (SIGINT).
The htdb_load utility exits 0 on success, 1 if one or more key/data pairs were not loaded into the database because the key already existed, and >1 if an error occurs.
The following keywords are supported for the -c command-line option to the htdb_load utility. See DB->open for further discussion of these keywords and what values should be specified.
The parenthetical listing specifies how the value part of the name=value pair is interpreted. Items listed as (boolean) expect value to be 1 (set) or 0 (unset). Items listed as (number) convert value to a number. Items listed as (string) use the string value without modification.
bt_minkey (number)db_lorder (number)db_pagesize (number)duplicates (boolean)h_ffactor (number)h_nelem (number)keys (boolean)re_len (number)re_pad (string)recnum (boolean)renumber (boolean)subdatabase (string)DB_HOME If the -h option is not specified and the environment variable DB_HOME is set, it is used as the path of the database home.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
dump the content of an inverted index.
mifluzdump file
mifluzdump writes on stdout a complete ascii
description of the file inverted index using the
WordList::Write method.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
load the content of an inverted index.
mifluzload file
mifluzload reads from stdout a complete ascii
description of the file inverted index using the
WordList::Read method.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
search the content of an inverted index.
mifluzsearch -f words [options]
mifluzsearch searches a mifluz index for documents matching a Alt*Vista expression (simple syntax).
Debugging information interpretation. A cursor is open in the index for every word and they are stored in a list. The list of cursors is always processed in the same order, as a single link list. With -v, each block is an individual action on behalf of the word shown on the first line. The last line of the block is the conclusion of the action described in the block. REDO means the same cursor must be examined again because the conditions have changed. RESTART means we go back to the first cursor in the list because it may not match the new conditions anymore. NEXT means the cursor and all the cursors before it match the conditions and we may proceed to the next cursor. ATEND means the cursor cannot match the conditions because it is at the end of the index.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
dump the dictionnary of an inverted index.
mifluzdict file
mifluzdict writes on stdout a complete ascii
description of the file inverted index using the
WordList::Write method.
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz.
read configuration and setup mifluz context.
#include <mifluz.h> WordContext context;
The WordContext object must be the first object created. All other objects (WordList, WordReference, WordKey and WordRecord) are allocated via the corresponding methods of WordContext (List, Word, Key and Record respectively).
The WordContext object contains a Configuration
object that holds the configuration parameters used by the
instance. If a configuration parameter is changed, the
ReInitialize method should be called to take them in
account.
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_monitor {true|false} (default false)WordMonitor instance to gather
statistics and build reports.WordContext()~/.mifluz configuration file or
/usr/etc/mifluz.conf . See the mifluz manual page for
a complete list of the configuration attributes.WordContext(const Configuration &config)WordContext(const ConfigDefaults *array)void Initialize(const Configuration
&config)When calling Initialize a second time, one must ensure that all WordList and WordCursor objects have been destroyed. WordList and WordCursor internal state depends on the current WordContext that will be lost by a second call.
For those interested by the internals, the Initialize function maintains a Berkeley DB environment (DB_ENV) in the following way:
First invocation:
Initialize -> new DB_ENV (thru WordDBInfo)
Second invocation:
Initialize -> delete DB_ENV -> new DB_ENV (thru WordDBInfo)
int Initialize(const ConfigDefaults* config_defaults =
0)Configuration object from the file pointed to by the
MIFLUZ_CONFIG environment variable or ~/.mifluz or
/usr/etc/mifluz.conf. The config_defaults
argument, if provided, is passed to the Configuration
object using the Defaults method. The
Initialize(const Configuration &) method is
then called with the Configuration object. Return OK
if success, NOTOK otherwise. Refer to the
Configuration description for more information.int ReInitialize()Configuration
object and rebuild it. May be used when the configuration is
changed to take these changes in account. Return OK if success,
NOTOK otherwise.const WordType& GetType() constWordType& GetType()const WordKeyInfo& GetKeyInfo() constWordKeyInfo& GetKeyInfo()const WordRecordInfo& GetRecordInfo()
constWordRecordInfo& GetRecordInfo()const WordDBInfo& GetDBInfo() constWordDBInfo& GetDBInfo()const WordMonitor* GetMonitor() constWordMonitor* GetMonitor()const Configuration& GetConfiguration()
constConfiguration& GetConfiguration()WordList* List()WordReference* Word()WordReference* Word(const String& key0, const
String& record0)WordReference* Word(const String& word)WordRecord* Record()WordKey* Key()WordKey* Key(const String& word)WordKey* Key(const WordKey& other)static String ConfigFile()MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz. or /usr/etc/mifluz.conf
abstract class to manage and use an inverted index file.
#include <mifluz.h> WordContext context; WordList* words = context->List(); delete words;
WordList is the mifluz equivalent of a database
handler. Each WordList object is bound to an inverted index file
and implements the operations to create it, fill it with word
occurrences and search for an entry matching a given criterion.
WordList is an abstract class and cannot be instanciated. The List method of the class WordContext will create an instance using the appropriate derived class, either WordListOne or WordListMulti. Refer to the corresponding manual pages for more information on their specific semantic.
When doing bulk insertions, mifluz creates temporary files that
contain the entries to be inserted in the index. Those files are
typically named indexC00000000 . The maximum size of
the temporary file is wordlist_cache_size / 2.
When the maximum size of the temporary file is reached, mifluz
creates another temporary file named indexC00000001 .
The process continues until mifluz created 50 temporary file. At
this point it merges all temporary files into one that replaces the
first indexC00000000 . Then it continues to create
temporary file again and keeps following this algorithm until the
bulk insertion is finished. When the bulk insertion is finished,
mifluz has one big file named indexC00000000 that
contains all the entries to be inserted in the index. mifluz
inserts all the entries from indexC00000000 into the
index and delete the temporary file when done. The insertion will
be fast since all the entries in indexC00000000 are
already sorted.
The parameter wordlist_cache_max can be used to
prevent the temporary files to grow indefinitely. If the total
cumulated size of the indexC* files grow beyond this
parameter, they are merged into the main index and deleted. For
instance setting this parameter value to 500Mb garanties that the
total size of the indexC* files will not grow above
500Mb.
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_extend {true|false} (default false)wordlist_verbose <number> (default 0)1 walk logic
2 walk logic details
3 walk logic lots of details
wordlist_page_size <bytes> (default
8192)wordlist_cache_size <bytes> (default
500K)wordlist_cache_max <bytes> (default 0)wordlist_cache_inserts {true|false} (default
false)wordlist_compress {true|false} (default
false)inline WordContext* GetContext()inline const WordContext* GetContext() constvirtual inline int Override(const WordReference&
wordRef)Key() part of the wordRef exists in
the index, override it. Returns OK on success, NOTOK on
error.virtual int Exists(const WordReference&
wordRef)inline int Exists(const String& word)virtual int WalkDelete(const WordReference&
wordRef)Key() part of wordRef , using the
Walk method. Returns the number of entries
successfully deleted.virtual int Delete(const WordReference&
wordRef)Key() part of wordRef. Returns OK if
deletion is successfull, NOTOK otherwise.virtual int Open(const String& filename, int
mode)O_RDONLY or
O_RDWR. If mode is O_RDWR it can be or'ed
with O_TRUNC to reset the content of an existing
inverted index. Return OK on success, NOTOK otherwise.virtual int Close()virtual unsigned int Size() constvirtual int Pagesize() constvirtual WordDict *Dict()const String& Filename() constint Flags() constinline List *Find(const WordReference&
wordRef)Key() part of wordRef. The
List returned contains pointers to
WordReference objects. It is the responsibility of the
caller to free the list. See List.h header for usage.inline List *FindWord(const String& word)List returned contains
pointers to WordReference objects. It is the
responsibility of the caller to free the list. See List.h header
for usage.virtual List *operator [] (const WordReference&
wordRef)inline List *operator [] (const String&
word)virtual List *Prefix (const WordReference&
prefix)Key() part of wordRef. In the
Key() , the string (accessed with
GetWord() ) matches any string that begins with it.
The List returned contains pointers to
WordReference objects. It is the responsibility of the
caller to free the list.inline List *Prefix (const String&
prefix)Key() , the string
(accessed with GetWord() ) matches any string that
begins with it. The List returned contains pointers to
WordReference objects. It is the responsibility of the
caller to free the list.virtual List *Words()List returned contains pointers to
String objects. It is the responsibility of the caller
to free the list. See List.h header for usage.virtual List *WordRefs()List returned contains pointers to
WordReference objects. It is the responsibility of the
caller to free the list. See List.h header for usage.virtual WordCursor *Cursor(wordlist_walk_callback_t
callback, Object *callback_data)virtual WordCursor *Cursor(const WordKey &searchKey,
int action = HTDIG_WORDLIST_WALKER)virtual WordCursor *Cursor(const WordKey &searchKey,
wordlist_walk_callback_t callback, Object *
callback_data)virtual WordKey Key(const String&
bufferin)virtual WordReference Word(const String& bufferin,
int exists = 0)virtual WordReference WordExists(const String&
bufferin)virtual void BatchStart()virtual void BatchEnd()virtual int Noccurrence(const String& key, unsigned
int& noccurrence) constGetWord()
part of key. Returns OK on success, NOTOK
otherwise.virtual int Write(FILE* f)WordReference ASCII description. Return OK on success,
NOTOK otherwise.virtual int WriteDict(FILE* f)virtual int Read(FILE* f)WordReference ASCII descriptions from
f , returns the number of inserted WordReference
or < 0 if an error occurs. Invalid descriptions are ignored as
well as empty lines.manage and use an inverted index dictionary.
#include <mifluz.h> WordList* words = ...; WordDict* dict = words->Dict();
WordDict maps strings to unique identifiers and frequency in the inverted index. Whenever a new word is found, the WordDict class can be asked to assign it a serial number. When doing so, an entry is created in the dictionary with a frequency of zero. The application may then increment or decrement the frequency to reflect the inverted index content.
The serial numbers range from 1 to 2^32 inclusive.
A WordDict object is automatically created by the WordList object and should not be created directly by the application.
WordDict()int Initialize(WordList* words)int Open()words data member. Return OK on
success, NOTOK otherwise.int Remove()int Close()int Serial(const String& word, unsigned int&
serial)int SerialExists(const String& word, unsigned
int& serial)int SerialRef(const String& word, unsigned int&
serial)int Noccurrence(const String& word, unsigned int&
noccurrence) constint Normalize(String& word) constint Ref(const String& word)int Incr(const String& word, unsigned int
incr)int Unref(const String& word)int Decr(const String& word, unsigned int
decr)int Put(const String& word, unsigned int
noccurrence)int Exists(const String& word) constList* Words() constWordDictCursor* Cursor() constint Next(WordDictCursor* cursor, String& word,
WordDictRecord& record)Cursor method. The word is returned in the
word argument and the record is returned in the
record argument. On success the function returns
0, at the end of the dictionnary it returns DB_NOTFOUND. The
cursor argument is deallocated when the function
hits the end of the dictionnary or an error occurs.WordDictCursor* CursorPrefix(const String& prefix)
constint NextPrefix(WordDictCursor* cursor, String& word,
WordDictRecord& record)CursorPrefix method. The word is returned in the
word argument and the record is returned in the
record argument. The word is
guaranteed to start with the prefix specified to the
CursorPrefix method. On success the function
returns 0, at the end of the dictionnary it returns DB_NOTFOUND.
The cursor argument is deallocated when the
function hits the end of the dictionnary or an error occurs.int Write(FILE* f)word
serial frequency , one by line.manage and use an inverted index file.
#include <mifluz.h> WordContext context; WordList* words = context->List(); WordList* words = WordListOne(context)
WordList is the mifluz equivalent of a database
handler. Each WordList object is bound to an inverted index file
and implements the operations to create it, fill it with word
occurrences and search for an entry matching a given criterion.
The general behavious of WordListOne is described in the
WordList manual page. It is prefered to create a WordListOne
instance by setting the wordlist_multi configuration
parameter to false and calling the
WordContext::List method.
Only the methods that differ from WordList are listed here. All the methods of WordList are implemented by WordListOne and you should refer to the manual page for more information.
The Cursor methods all return a WordCursorOne instance cast to a WordCursor object.
WordListOne(WordContext* ncontext)int DeleteCursor(WordDBCursor& cursor)inverted index key.
#include <WordKey.h>
#define WORD_KEY_DOCID 1
#define WORD_KEY_LOCATION 2
WordList* words = ...;
WordKey key = words->Key("word 100 20");
WordKey searchKey;
words->Dict()->SerialExists("dog", searchKey.Get(WORD_KEY_WORD));
searchKey.Set(WORD_KEY_LOCATION, 5);
WordCursor* cursor = words->Key(searchKey);
Describes the key used to store a entry in the inverted index.
Each field in the key has a bit in the set member
that says if it is set or not. This bit allows to say that a
particular field is undefined regardless of the actual
value stored. The methods IsDefined, SetDefined
and Undefined are used to manipulate the
defined status of a field. The Pack
and Unpack methods are used to convert to and from
the disk storage representation of the key.
Although constructors may be used, the prefered way to create a WordKey object is by using the WordContext::Key method.
The following constants are defined:
WORD_KEY_WORDWORD_KEY_VALUE_INVALIDThe ASCII description is a string with fields separated by tabs or white space.
Example: 200 <UNDEF> 1 4 2
Field 1: The word identifier or <UNDEF> if not defined
Field 2 to the end: numerical value of the field or <UNDEF> if
not defined
WordKey(WordContext* ncontext)WordKey(WordContext* ncontext, const String&
desc)ASCII FORMAT section. The ncontext
argument must be a pointer to a valid WordContext object.void Clear()inline int NFields() constWordKeyInfo(3) ).inline WordKeyNum MaxValue(int position)WordKeyInfo(3) ).inline WordContext* GetContext()inline const WordContext* GetContext() constinline WordKeyNum Get(int position) constinline WordKeyNum& Get(int position)inline const WordKeyNum & operator[] (int position)
constinline WordKeyNum & operator[] (int
position)inline void Set(int position, WordKeyNum val)int IsDefined(int position) constdefined , false otherwise.void SetDefined(int position)defined. A bit is set in the bit field describing the
defined/undefined state of the value and the actual value of the
field is not modified.void Undefined(int position)undefined. A bit is set in the bit field describing
the defined/undefined state of the value and the actual value of
the field is not modified.int Set(const String& bufferin)ASCII FORMAT section.
Return OK if successfull, NOTOK otherwise.int Get(String& bufferout) constASCII FORMAT section.
Return OK if successfull, NOTOK otherwise.String Get() constASCII FORMAT section.int Unpack(const char* string, int length)inline int Unpack(const String& data)int Pack(String& data) constint Merge(const WordKey& other)defined field from other into the
object, if the corresponding field of the object is not defined.
Return OK if successfull, NOTOK otherwise.int PrefixOnly()int SetToFollowing(int position =
WORD_FOLLOWING_MAX)It behaves like arithmetic but follows these rules:
. Increment starts at field <position> . If a field value overflows, increment field position - 1 . Undefined fields are ignored and their value untouched . When a field is incremented all fields to the left are set to 0If position is not specified it is equivalent to NFields() - 1. It returns OK if successfull, NOTOK if position out of range or WORD_FOLLOWING_ATEND if the maximum possible value was reached.
int Filled() constdefined , false
otherwise.int Empty() constdefined , false
otherwise.int Equal(const WordKey& other) constint ExactEqual(const WordKey& other)
constint Cmp(const WordKey& other) constint PackEqual(const WordKey& other) constundefined numerical
field will be 0 and therefore undistinguishable from a
defined field whose value is 0.int Outbound(int position, int increment)int Overflow(int position, int increment)int Underflow(int position, int increment)int Prefix() conststatic int Compare(WordContext* context, const
String& a, const String& b)WordKeyInfo.
Returns a positive number if a is greater than
b , zero if they are equal, a negative number if
a is lower than b.static int Compare(WordContext* context, const unsigned
char *a, int a_length, const unsigned char *b, int
b_length)WordKeyInfo.
Returns a positive number if a is greater than
b , zero if they are equal, a negative number if
a is lower than b.int Diff(const WordKey& other, int& position,
int& lower)int Write(FILE* f) constGet method). See ASCII FORMAT
section.void Print() constGet method). See ASCII FORMAT
section.information on the key structure of the inverted index.
Helper for the WordKey class.
Describe the structure of the index key ( WordKey
). The description includes the layout of the packed version stored
on disk.
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_wordkey_description <desc> (no
default)<desc> format,
mandatory words are in bold and values that must be replaced in
italic.
Word bits/name bits [/...]
The name is an alphanumerical symbolic name for the
key field. The bits is the number of bits required to
store this field. Note that all values are stored in unsigned
integers (unsigned int). Example:
Word 8/Document 16/Location 8
defines a word in term of allowed characters, length etc.
Only called thru WordContext::Initialize()
WordType defines an indexed word and operations to validate a
word to be indexed. All words inserted into the mifluz
index are Normalize d before insertion. The
configuration options give some control over the definition of a
word.
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_locale <locale> (default C)wordlist_allow_numbers {true|false} <number>
(default false)true otherwise it is
an error to insert a word containing digits. See the
Normalize method for more information.wordlist_mimimun_word_length <number> (default
3)wordlist_maximum_word_length <number> (default
25)wordlist_allow_numbers {true|false} <number>
(default false)true otherwise it is
an error to insert a word containing digits. See the
Normalize method for more information.wordlist_truncate {true|false} <number> (default
true)wordlist_maximum_word_length it is truncated if this
configuration parameter is true otherwise it is
considered an invalid word.wordlist_lowercase {true|false} <number> (default
true)wordlist_valid_punctuation [characters] (default
none)int Normalize(String &s) constWORD_NORMALIZE_TOOLONGwordlist_maximum_word_length configuration
parameter.WORD_NORMALIZE_TOOSHORTwordlist_minimum_word_length configuration
parameter.WORD_NORMALIZE_CAPITALwordlist_lowercase configuration parameter is
true.WORD_NORMALIZE_NUMBERwordlist_allow_numbers is set to false.WORD_NORMALIZE_CONTROLWORD_NORMALIZE_BADwordlist_bad_word_list configuration parameter.WORD_NORMALIZE_NULLWORD_NORMALIZE_PUNCTUATIONwordlist_valid_punctuation attribute was removed from
the word.WORD_NORMALIZE_NOALPHAstatic String NormalizeStatus(int flags)inverted index usage environment.
Only called thru WordContext::Initialize()
The inverted indexes may be shared among processes/threads and
provide the appropriate locking to prevent mistakes. In addition
the memory cache used by WordList objects may be
shared by processes/threads, greatly reducing the memory needs in
multi-process applications. For more information about the shared
environment, check the Berkeley DB documentation.
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_env_skip {true,false} (default
false)WordList object is created. It may be useful
if only WordKey objects are used, for instance.wordlist_env_share {true,false} (default
false)wordlist_env_dir <directory> (default
.)wordlist_env_share set to
true. Specify the directory in which the sharable
environment will be created. All inverted indexes specified with a
non-absolute pathname will be created relative to this
directory.information on the record structure of the inverted index.
Only called thru WordContext::Initialize()
The structure of a record is very limited. It can contain a single integer value or a string.
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_wordrecord_description {NONE|DATA|STR} (no
default)DATA: the record contains an integer (unsigned int)
STR: the record contains a string (String)
inverted index record.
#include <WordRecord.h>
WordContext* context;
WordRecord* record = context->Record();
if(record->DefaultType() == WORD_RECORD_DATA) {
record->info.data = 120;
} else if(record->DefaultType() == WORD_RECORD_STR) {
record->info.str = "foobar";
}
delete record;
The record can contain an integer, if the default record type
(see CONFIGURATION in WordKeyInfo ) is set to
DATA or a string if set to STR. If the
type is set to NONE the record does not contain any
usable information.
Although constructors may be used, the prefered way to create a WordRecord object is by using the WordContext::Record method.
If default type is DATA it is the decimal
representation of an integer. If default type is NONE
it is the empty string.
inline WordRecord(WordContext* ncontext)inline void Clear()inline int DefaultType()inline int Pack(String& packed) constinline int Unpack(const char* string, int
length)inline int Unpack(const String& packed)int Set(const String& bufferin)int Get(String& bufferout) constString Get() constinline WordContext* GetContext()inline const WordContext* GetContext() constint Write(FILE* f) constinverted index occurrence.
#include <WordReference.h>
WordContext* context;
WordReference* word = context->Word("word");
WordReference* word = context->Word();
WordReference* word = context->Word(WordKey("key 1 2"), WordRecord());
WordKey key = word->Key()
WordKey record = word->Record()
word->Clear();
delete word;
A WordReference object is an agregate of a
WordKey object and a WordRecord
object.
Although constructors may be used, the prefered way to create a WordReference object is by using the WordContext::Word method.
The ASCII description is a string with fields separated by tabs
or white space. It is made of the ASCII description of a
WordKey object immediately followed by the ASCII
description of a WordRecord object. See the
corresponding manual pages for more information.
WordReference(WordContext* ncontext) :WordReference(WordContext* ncontext, const String&
key0, const String& record0) :WordReference(WordContext* ncontext, const String&
word) :void Clear()inline WordContext* GetContext()inline const WordContext* GetContext() constinline String& GetWord()inline const String& GetWord() constinline void SetWord(const String& nword)WordKey& Key()const WordKey& Key() constWordRecord& Record()const WordRecord& Record() constvoid Key(const WordKey& arg)int KeyUnpack(const String& packed)String KeyPack() constint KeyPack(String& packed) constvoid Record(const WordRecord& arg)int RecordUnpack(const String& packed)String RecordPack() constint RecordPack(String& packed) constinline int Pack(String& ckey, String& crecord)
constint Unpack(const String& ckey, const String&
crecord)int Merge(const WordReference& other)WordKey::Merge method: key.Merge(other.Key()). See the
corresponding manual page for details. Copy other.record into the
record part of the object.static WordReference Merge(const WordReference&
master, const WordReference& slave)int Set(const String& bufferin)ASCII FORMAT section.
Return OK if successfull, NOTOK otherwise.int Get(String& bufferout) constASCII FORMAT section.
Return OK if successfull, NOTOK otherwise.String Get() constASCII FORMAT section.int Write(FILE* f) constGet method). See ASCII FORMAT
section.void Print() constGet method). See ASCII FORMAT
section.abstract class to search and retrieve entries in a WordList object.
#include <WordList.h>
int callback(WordList *, WordDBCursor& , const WordReference *, Object &)
{
...
}
Object* data = ...
WordList *words = ...;
WordCursor *search = words->Cursor(WordKey("word <UNDEF> <UNDEF>"), HTDIG_WORDLIST_COLLECTOR);
if(search->Walk() == NOTOK) bark;
List* results = search->GetResults();
WordCursor *search = words->Cursor(callback, data);
WordCursor *search = words->Cursor(WordKey("word <UNDEF> <UNDEF>"));
WordCursor *search = words->Cursor(WordKey("word <UNDEF> <UNDEF>"), callback, data);
WordCursor *search = words->Cursor(WordKey());
search->WalkInit();
if(search->WalkNext() == OK)
dosomething(search->GetFound());
search->WalkFinish();
WordCursor is an iterator on an inverted index. It is created by
asking a WordList object with the Cursor.
There is no other way to create a WordCursor object. When the
Walk* methods return, the WordCursor object contains
the result of the search and status information that indicates if
it reached the end of the list (IsAtEnd() method).
The callback function that is called each time a match is found takes the following arguments:
WordList* words pointer to the inverted index handle.
WordDBCursor& cursor to call Del() and delete the current match
WordReference* wordRef is the match
Object& data is the user data provided by the caller when
search began.
The WordKey object that specifies the search
criterion may be used as follows (assuming word is followed by
DOCID and LOCATION):
Ex1: WordKey() walk the entire list of occurences.
Ex2: WordKey("word <UNDEF>
<UNDEF>") find all occurrences of word
.
Ex3: WordKey("meet <UNDEF> 1") find all
occurrences of meet that occur at LOCATION 1 in any
DOCID. This can be inefficient since the search has to scan all
occurrences of meet to find the ones that occur at
LOCATION 1.
Ex4: WordKey("meet 2 <UNDEF>") find all
occurrences of meet that occur in DOCID 2, at any
location.
WordList is an abstract class and cannot be instanciated. See the WordCursorOne manual page for an actual implementation of a WordCursor object.
virtual void Clear() = 0virtual inline int IsA() constvirtual inline int Optimize()virtual int ContextSave(String& buffer) const =
0virtual int ContextRestore(const String& buffer) =
0DB_NEXT.virtual int Walk() = 0virtual int WalkInit() = 0virtual int WalkRewind() = 0virtual int WalkNext() = 0virtual int WalkNextStep() = 0virtual int WalkNextExclude(const WordKey&
key)virtual int WalkFinish() = 0virtual int Seek(const WordKey& patch) =
0WalkNext or WalkNextStep method.
Copy defined fields from patch into a copy of the
found data member and initialize internal state so
that WalkNext jumps to this key next time it's called
(cursor_get_flag set to DB_SET_RANGE). Returns OK if successfull,
NOTOK otherwise.virtual inline int IsAtEnd() constvirtual inline int IsNoMatch() constinline WordKey& GetSearch()inline int GetAction() constinline List *GetResults()inline List *GetTraces()inline void SetTraces(List* traceRes_arg)inline const WordReference& GetFound()WalkNext or
WalkNextStep call was successfull (i.e. returned
OK).inline int GetStatus() constvirtual int Get(String& bufferout) const =
0inline String Get() constvirtual int Initialize(WordList *nwords, const WordKey
&nsearchKey, wordlist_walk_callback_t ncallback, Object *
ncallback_data, int naction) = 0WordKey searchKeyWordReference foundint statusWordList *wordssearch and retrieve entries in a WordListOne object.
#include <WordList.h>
int callback(WordList *, WordDBCursor& , const WordReference *, Object &)
{
...
}
Object* data = ...
WordList *words = ...;
WordCursor *search = words->Cursor(callback, data);
WordCursor *search = words->Cursor(WordKey("word <UNDEF> <UNDEF>"));
WordCursor *search = words->Cursor(WordKey("word <UNDEF> <UNDEF>"), callback, data);
WordCursor *search = words->Cursor(WordKey());
...
if(search->Walk() == NOTOK) bark;
List* results = search->GetResults();
search->WalkInit();
if(search->WalkNext() == OK)
dosomething(search->GetFound());
search->WalkFinish();
WordCursorOne is a WordCursor derived class that implements search in a WordListOne object. It currently is the only derived class of the WordCursor object. Most of its behaviour is described in the WordCursor manual page, only the behaviour specific to WordCursorOne is documented here.
WordCursorOne(WordList *words)WordCursorOne(WordList *words, wordlist_walk_callback_t
callback, Object * callback_data)WordCursorOne(WordList *words, const WordKey
&searchKey, int action = HTDIG_WORDLIST_WALKER)WordCursorOne(WordList *words, const WordKey
&searchKey, wordlist_walk_callback_t callback, Object *
callback_data)monitoring classes activity.
Only called thru WordContext::Initialize()
The test directory contains a benchmark-report
script used to generate and archive graphs from the output of
WordMonitor .
For more information on the configuration attributes and a complete list of attributes, see the mifluz(3) manual page.
wordlist_monitor_period <sec> (default
0)wordlist_monitor_output <file>[,{rrd,readable]
(default stderr)benchmark-report script. Otherwise it a (hardly :-)
readable string.reads the configuration file and manages it in memory.
#include <Configuration.h>
Configuration config;
ConfigDefault config_defaults = {
{ "verbose", "true" },
{ 0, 0 }
};
config.Defaults(config_defaults);
config.Read("/spare2/myconfig") ;
config.Add("sync", "false");
if(config["sync"]) ...
if(config.Value("rate") < 50) ...
if(config.Boolean("sync")) ...
The primary purpose of the Configuration class
is to parse a configuration file and allow the application to
modify the internal data structure produced. All values are strings
and are converted by the appropriate accessors. For instance the
Boolean method will return numerical true (not
zero) if the string either contains a number that is different from
zero or the string true .
The ConfigDefaults type is a structure of two char
pointers: the name of the configuration attribute and it's value.
The end of the array is the first entry that contains a null
pointer instead of the attribute name. Numerical values must be in
strings. For instance:
ConfigDefault* config_defaults = {
{ "wordlist_compress", "true" },
{ "wordlist_page_size", "8192" },
{ 0, 0 }
};
The additional fields of the ConfigDefault are
purely informative.
The configuration file is a plain ASCII text file. Each line in the file is either a comment or an attribute. Comment lines are blank lines or lines that start with a '#'. Attributes consist of a variable name and an associated value:
<name>:<whitespace><value><newline>
The <name> contains any alphanumeric character or underline (_) The <value> can include any character except newline. It also cannot start with spaces or tabs since those are considered part of the whitespace after the colon. It is important to keep in mind that any trailing spaces or tabs will be included.
It is possible to split the <value> across several lines of the configuration file by ending each line with a backslash (\). The effect on the value is that a space is added where the line split occurs.
A configuration file can include another file, by using the
special <name>, include . The <value> is
taken as the file name of another configuration file to be read in
at this point. If the given file name is not fully qualified, it is
taken relative to the directory in which the current configuration
file is found. Variable expansion is permitted in the file name.
Multiple include statements, and nested includes are also
permitted.
include: common.conf
Configuration()~Configuration()void Add(const String& str)void Add(const String& name, const String&
value)int Remove(const String& name)void NameValueSeparators(const String& s)name and the value.virtual int Read(const String& filename)const String Find(const String& name)
constString .const String operator[](const String& name)
constint Value(const String& name, int default_value = 0)
constdouble Double(const String& name, double
default_value = 0) constint Boolean(const String& name, int default_value =
0) constvoid Defaults(const ConfigDefaults *array)name and
value members of the array
argument.C++ library to use and manage inverted indexes
#include <mifluz.h>
main()
{
Configuration* config = WordContext::Initialize();
WordList* words = new WordList(*config);
...
delete words;
WordContext::Finish();
}
The purpose of mifluz is to provide a C++ library
to build and query a full text inverted index. It is dynamically
updatable, scalable (up to 1Tb indexes), uses a controlled amount
of memory, shares index files and memory cache among processes or
threads and compresses index files to 50% of the raw data. The
structure of the index is configurable at runtime and allows
inclusion of relevance ranking information. The query functions do
not require loading all the occurrences of a searched term. They
consume very few resources and many searches can be run in
parallel.
The file management library used in mifluz is a modified Berkeley DB (www.sleepycat.com) version 3.1.14.
Configurationreads the configuration file and manages it in memory.
WordContextread configuration and setup mifluz context.
WordCursorabstract class to search and retrieve entries in a WordList
object.
WordCursorOnesearch and retrieve entries in a WordListOne object.
WordDBInfoWordDictmanage and use an inverted index dictionary.
WordKeyWordKeyInfoWordListabstract class to manage and use an inverted index file.
WordListOnemanage and use an inverted index file.
WordMonitorWordRecordWordRecordInfoWordReferenceWordTypehtdb_dumpdump the content of an inverted index in Berkeley DB
fashion
htdb_loaddisplays statistics for Berkeley DB environments.
htdb_statdisplays statistics for Berkeley DB environments.
mifluzdictdump the dictionnary of an inverted index.
mifluzdumpdump the content of an inverted index.
mifluzloadload the content of an inverted index.
mifluzsearchThe format of the configuration file read by WordContext::Initialize is:
keyword: valueComments may be added on lines starting with a #. The default configuration file is read from from the file pointed by the MIFLUZ_CONFIG environment variable or ~/.mifluz or /etc/mifluz.conf in this order. If no configuration file is available, builtin defaults are used. Here is an example configuration file:
wordlist_extend: true wordlist_cache_size: 10485760 wordlist_page_size: 32768 wordlist_compress: 1 wordlist_wordrecord_description: NONE wordlist_wordkey_description: Word/DocID 32/Flags 8/Location 16 wordlist_monitor: true wordlist_monitor_period: 30 wordlist_monitor_output: monitor.out,rrd
wordlist_allow_numbers {true|false} <number>
(default false)true otherwise it is
an error to insert a word containing digits. See the
Normalize method for more information.wordlist_cache_inserts {true|false} (default
false)wordlist_cache_max <bytes> (default 0)wordlist_cache_size <bytes> (default
500K)wordlist_compress {true|false} (default
false)wordlist_env_dir <directory> (default
.)wordlist_env_share set to
true. Specify the directory in which the sharable
environment will be created. All inverted indexes specified with a
non-absolute pathname will be created relative to this
directory.wordlist_env_share {true,false} (default
false)wordlist_env_skip {true,false} (default
false)WordList object is created. It may be useful
if only WordKey objects are used, for instance.wordlist_extend {true|false} (default false)wordlist_locale <locale> (default C)wordlist_lowercase {true|false} <number> (default
true)wordlist_maximum_word_length <number> (default
25)wordlist_mimimun_word_length <number> (default
3)wordlist_monitor {true|false} (default false)WordMonitor instance to gather
statistics and build reports.wordlist_monitor_output <file>[,{rrd,readable]
(default stderr)benchmark-report script. Otherwise it a (hardly :-)
readable string.wordlist_monitor_period <sec> (default
0)wordlist_page_size <bytes> (default
8192)wordlist_truncate {true|false} <number> (default
true)wordlist_maximum_word_length it is truncated if this
configuration parameter is true otherwise it is
considered an invalid word.wordlist_valid_punctuation [characters] (default
none)wordlist_verbose <number> (default 0)1 walk logic
2 walk logic details
3 walk logic lots of details
wordlist_wordkey_description <desc> (no
default)<desc> format,
mandatory words are in bold and values that must be replaced in
italic.
Word bits/name bits [/...]
The name is an alphanumerical symbolic name for the
key field. The bits is the number of bits required to
store this field. Note that all values are stored in unsigned
integers (unsigned int). Example:
Word 8/Document 16/Location 8
wordlist_wordkey_document [field ...] (default
none)wordlist_wordkey_location field (default
none)wordlist_wordrecord_description {NONE|DATA|STR} (no
default)DATA: the record contains an integer (unsigned int)
STR: the record contains a string (String)
MIFLUZ_CONFIG file name of configuration file read by WordContext(3). Defaults to ~/.mifluz. or /usr/etc/mifluz.conf