xapian-core  1.4.24
Public Types | Public Member Functions | List of all members
Xapian::MSet Class Reference

Class representing a list of search results. More...

#include <mset.h>

Public Types

enum  {
  SNIPPET_BACKGROUND_MODEL = 1 , SNIPPET_EXHAUSTIVE = 2 , SNIPPET_EMPTY_WITHOUT_MATCH = 4 , SNIPPET_NGRAMS = 2048 ,
  SNIPPET_CJK_NGRAM = SNIPPET_NGRAMS
}
 

Public Member Functions

 MSet (const MSet &o)
 Copying is allowed.
 
MSetoperator= (const MSet &o)
 Copying is allowed.
 
 MSet ()
 Default constructor.
 
 ~MSet ()
 Destructor.
 
int convert_to_percent (double weight) const
 Convert a weight to a percentage.
 
int convert_to_percent (const MSetIterator &it) const
 Convert the weight of the current iterator position to a percentage.
 
Xapian::doccount get_termfreq (const std::string &term) const
 Get the termfreq of a term.
 
double get_termweight (const std::string &term) const
 Get the term weight of a term.
 
Xapian::doccount get_firstitem () const
 Rank of first item in this MSet.
 
Xapian::doccount get_matches_lower_bound () const
 Lower bound on the total number of matching documents.
 
Xapian::doccount get_matches_estimated () const
 Estimate of the total number of matching documents.
 
Xapian::doccount get_matches_upper_bound () const
 Upper bound on the total number of matching documents.
 
Xapian::doccount get_uncollapsed_matches_lower_bound () const
 Lower bound on the total number of matching documents before collapsing.
 
Xapian::doccount get_uncollapsed_matches_estimated () const
 Estimate of the total number of matching documents before collapsing.
 
Xapian::doccount get_uncollapsed_matches_upper_bound () const
 Upper bound on the total number of matching documents before collapsing.
 
double get_max_attained () const
 The maximum weight attained by any document.
 
double get_max_possible () const
 The maximum possible weight any document could achieve.
 
std::string snippet (const std::string &text, size_t length=500, const Xapian::Stem &stemmer=Xapian::Stem(), unsigned flags=SNIPPET_BACKGROUND_MODEL|SNIPPET_EXHAUSTIVE, const std::string &hi_start="<b>", const std::string &hi_end="</b>", const std::string &omit="...") const
 Generate a snippet.
 
void fetch (const MSetIterator &begin, const MSetIterator &end) const
 Prefetch hint a range of items.
 
void fetch (const MSetIterator &item) const
 Prefetch hint a single MSet item.
 
void fetch () const
 Prefetch hint the whole MSet.
 
Xapian::doccount size () const
 Return number of items in this MSet object.
 
bool empty () const
 Return true if this MSet object is empty.
 
void swap (MSet &o)
 Efficiently swap this MSet object with another.
 
MSetIterator begin () const
 Return iterator pointing to the first item in this MSet.
 
MSetIterator end () const
 Return iterator pointing to just after the last item in this MSet.
 
MSetIterator operator[] (Xapian::doccount i) const
 Return iterator pointing to the i-th object in this MSet.
 
MSetIterator back () const
 Return iterator pointing to the last object in this MSet.
 
std::string get_description () const
 Return a string describing this object.
 

Detailed Description

Class representing a list of search results.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
Enumerator
SNIPPET_BACKGROUND_MODEL 

Model the relevancy of non-query terms in MSet::snippet().

    Non-query terms will be assigned a small weight, and the snippet
    will tend to prefer snippets which contain a more interesting
    background (where the query term content is equivalent).
SNIPPET_EXHAUSTIVE 

Exhaustively evaluate candidate snippets in MSet::snippet().

    Without this flag, snippet generation will stop once it thinks
    it has found a "good enough" snippet, which will generally reduce
    the time taken to generate a snippet.
SNIPPET_EMPTY_WITHOUT_MATCH 

Return the empty string if no term got matched.

    If enabled, snippet() returns an empty string if not a single match
    was found in text. If not enabled, snippet() returns a (sub)string
    of text without any highlighted terms.
SNIPPET_NGRAMS 

Generate n-grams for scripts without explicit word breaks.

    Text in other scripts is split into words as normal.

    Enable this option to highlight search results for queries parsed
    with the QueryParser::FLAG_NGRAMS flag.

    The TermGenerator::FLAG_NGRAMS flag needs to have been used at
    index time.

    This mode can also be enabled by setting environment variable
    XAPIAN_CJK_NGRAM to a non-empty value (but doing so was deprecated
    in 1.4.11).

    In 1.4.x this feature was specific to CJK (Chinese, Japanese and
    Korean), but in 1.5.0 it's been extended to other languages.  To
    reflect this change the new and preferred name is SNIPPET_NGRAMS,
    which was added as an alias for forward compatibility in Xapian
    1.4.23.  Use SNIPPET_CJK_NGRAM instead if you aim to support Xapian
    &lt; 1.4.23.

    @since Added in Xapian 1.4.23.
SNIPPET_CJK_NGRAM 

Generate n-grams for scripts without explicit word breaks.

    Old name - use SNIPPET_NGRAMS instead unless you aim to support
    Xapian &lt; 1.4.23.

    @since Added in Xapian 1.4.11.

Constructor & Destructor Documentation

◆ MSet() [1/2]

Xapian::MSet::MSet ( const MSet o)

Copying is allowed.

The internals are reference counted, so copying is cheap.

◆ MSet() [2/2]

Xapian::MSet::MSet ( )

Default constructor.

Creates an empty MSet, mostly useful as a placeholder.

Member Function Documentation

◆ convert_to_percent() [1/2]

int Xapian::MSet::convert_to_percent ( const MSetIterator it) const
inline

Convert the weight of the current iterator position to a percentage.

The matching document with the highest weight will get 100% if it matches all the weighted query terms, and proportionally less if it only matches some, and other weights are scaled by the same factor.

Documents with a non-zero score will always score at least 1%.

Note that these generally aren't percentages of anything meaningful (unless you use a custom weighting formula where they are!)

References convert_to_percent(), and Xapian::MSetIterator::get_weight().

◆ convert_to_percent() [2/2]

int Xapian::MSet::convert_to_percent ( double  weight) const

Convert a weight to a percentage.

The matching document with the highest weight will get 100% if it matches all the weighted query terms, and proportionally less if it only matches some, and other weights are scaled by the same factor.

Documents with a non-zero score will always score at least 1%.

Note that these generally aren't percentages of anything meaningful (unless you use a custom weighting formula where they are!)

Referenced by convert_to_percent(), and Xapian::MSetIterator::get_percent().

◆ fetch() [1/3]

void Xapian::MSet::fetch ( ) const
inline

Prefetch hint the whole MSet.

For a remote database, this may start a pipelined fetch of the requested documents from the remote server.

For a disk-based database, this may send prefetch hints to the operating system such that the disk blocks the requested documents are stored in are more likely to be in the cache when we come to actually read them.

◆ fetch() [2/3]

void Xapian::MSet::fetch ( const MSetIterator begin,
const MSetIterator end 
) const
inline

Prefetch hint a range of items.

For a remote database, this may start a pipelined fetch of the requested documents from the remote server.

For a disk-based database, this may send prefetch hints to the operating system such that the disk blocks the requested documents are stored in are more likely to be in the cache when we come to actually read them.

◆ fetch() [3/3]

void Xapian::MSet::fetch ( const MSetIterator item) const
inline

Prefetch hint a single MSet item.

For a remote database, this may start a pipelined fetch of the requested documents from the remote server.

For a disk-based database, this may send prefetch hints to the operating system such that the disk blocks the requested documents are stored in are more likely to be in the cache when we come to actually read them.

◆ get_firstitem()

Xapian::doccount Xapian::MSet::get_firstitem ( ) const

Rank of first item in this MSet.

This is the parameter first passed to Xapian::Enquire::get_mset().

Referenced by Xapian::MSetIterator::get_rank().

◆ get_termfreq()

Xapian::doccount Xapian::MSet::get_termfreq ( const std::string &  term) const

Get the termfreq of a term.

Returns
The number of documents which term occurs in. This considers all documents in the database being searched, so gives the same answer as db.get_termfreq(term) (but is more efficient for query terms as it returns a value cached during the search.)

◆ get_termweight()

double Xapian::MSet::get_termweight ( const std::string &  term) const

Get the term weight of a term.

Returns
The maximum weight that term could have contributed to a document.

◆ get_uncollapsed_matches_estimated()

Xapian::doccount Xapian::MSet::get_uncollapsed_matches_estimated ( ) const

Estimate of the total number of matching documents before collapsing.

Conceptually the same as get_matches_estimated() for the same query without any collapse part (though the actual value may differ).

◆ get_uncollapsed_matches_lower_bound()

Xapian::doccount Xapian::MSet::get_uncollapsed_matches_lower_bound ( ) const

Lower bound on the total number of matching documents before collapsing.

Conceptually the same as get_matches_lower_bound() for the same query without any collapse part (though the actual value may differ).

◆ get_uncollapsed_matches_upper_bound()

Xapian::doccount Xapian::MSet::get_uncollapsed_matches_upper_bound ( ) const

Upper bound on the total number of matching documents before collapsing.

Conceptually the same as get_matches_upper_bound() for the same query without any collapse part (though the actual value may differ).

◆ operator=()

MSet & Xapian::MSet::operator= ( const MSet o)

Copying is allowed.

The internals are reference counted, so assignment is cheap.

◆ snippet()

std::string Xapian::MSet::snippet ( const std::string &  text,
size_t  length = 500,
const Xapian::Stem stemmer = Xapian::Stem(),
unsigned  flags = SNIPPET_BACKGROUND_MODEL|SNIPPET_EXHAUSTIVE,
const std::string &  hi_start = "<b>",
const std::string &  hi_end = "</b>",
const std::string &  omit = "..." 
) const

Generate a snippet.

This method selects a continuous run of words from text, based mainly on where the query matches (currently terms, exact phrases and wildcards are taken into account). If flag SNIPPET_BACKGROUND_MODEL is used (which it is by default) then the selection algorithm also considers the non-query terms in the text with the aim of showing a context which provides more useful information.

The size of the text selected can be controlled by the length parameter, which specifies a number of bytes of text to aim to select. However slightly more text may be selected. Also the size of any escaping, highlighting or omission markers is not considered.

The returned text is escaped to make it suitable for use in HTML (though beware that in upstream releases 1.4.5 and earlier this escaping was sometimes incomplete), and matches with the query will be highlighted using hi_start and hi_end.

If the snippet seems to start or end mid-sentence, then omit is prepended or append (respectively) to indicate this.

The same stemming algorithm which was used to build the query should be specified in stemmer.

And flags contains flags controlling behaviour.

Added in 1.3.5.


The documentation for this class was generated from the following file: