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mariadb/storage/innobase/fts/fts0que.cc
Vasilii Lakhin 22efc2c784 Fix typos in C comments inside storage/
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/*****************************************************************************
Copyright (c) 2007, 2020, Oracle and/or its affiliates. All Rights Reserved.
Copyright (c) 2017, 2021, MariaDB Corporation.
This program is free software; you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation; version 2 of the License.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with
this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1335 USA
*****************************************************************************/
/**************************************************//**
@file fts/fts0que.cc
Full Text Search functionality.
Created 2007/03/27 Sunny Bains
Completed 2011/7/10 Sunny and Jimmy Yang
*******************************************************/
#include "dict0dict.h"
#include "ut0rbt.h"
#include "row0sel.h"
#include "fts0fts.h"
#include "fts0priv.h"
#include "fts0ast.h"
#include "fts0pars.h"
#include "fts0types.h"
#include "fts0plugin.h"
#include "fts0vlc.h"
#include <iomanip>
#include <vector>
#define FTS_ELEM(t, n, i, j) (t[(i) * n + (j)])
#define RANK_DOWNGRADE (-1.0F)
#define RANK_UPGRADE (1.0F)
/* Maximum number of words supported in a phrase or proximity search. */
#define MAX_PROXIMITY_ITEM 128
/* Memory used by rbt itself for create and node add */
#define SIZEOF_RBT_CREATE sizeof(ib_rbt_t) + sizeof(ib_rbt_node_t) * 2
#define SIZEOF_RBT_NODE_ADD sizeof(ib_rbt_node_t)
/*Initial byte length for 'words' in fts_ranking_t */
#define RANKING_WORDS_INIT_LEN 4
// FIXME: Need to have a generic iterator that traverses the ilist.
typedef std::vector<fts_string_t, ut_allocator<fts_string_t> > word_vector_t;
struct fts_word_freq_t;
/** State of an FTS query. */
struct fts_query_t {
mem_heap_t* heap; /*!< Heap to use for allocations */
trx_t* trx; /*!< The query transaction */
dict_index_t* index; /*!< The FTS index to search */
/*!< FTS auxiliary common table def */
fts_table_t fts_common_table;
fts_table_t fts_index_table;/*!< FTS auxiliary index table def */
size_t total_size; /*!< total memory size used by query */
fts_doc_ids_t* deleted; /*!< Deleted doc ids that need to be
filtered from the output */
fts_ast_node_t* root; /*!< Abstract syntax tree */
fts_ast_node_t* cur_node; /*!< Current tree node */
ib_rbt_t* word_map; /*!< Matched word map for
searching by word*/
word_vector_t* word_vector; /*!< Matched word vector for
searching by index */
ib_rbt_t* doc_ids; /*!< The current set of matching
doc ids, elements are of
type fts_ranking_t */
ib_rbt_t* intersection; /*!< The doc ids that were found in
doc_ids, this tree will become
the new doc_ids, elements are of type
fts_ranking_t */
/*!< Prepared statement to read the
nodes from the FTS INDEX */
que_t* read_nodes_graph;
fts_ast_oper_t oper; /*!< Current boolean mode operator */
/*!< TRUE if we want to collect the
word positions within the document */
ibool collect_positions;
ulint flags; /*!< Specify the full text search type,
such as boolean search, phrase
search, proximity search etc. */
ulint distance; /*!< The proximity distance of a
phrase search. */
/*!< These doc ids are used as a
boundary condition when searching the
FTS index rows */
doc_id_t lower_doc_id; /*!< Lowest doc id in doc_ids */
doc_id_t upper_doc_id; /*!< Highest doc id in doc_ids */
bool boolean_mode; /*!< TRUE if boolean mode query */
ib_vector_t* matched; /*!< Array of matching documents
(fts_match_t) to search for a phrase */
ib_vector_t** match_array; /*!< Used for proximity search, contains
position info for each matched word
in the word list */
ib_uint64_t total_docs; /*!< The total number of documents */
ulint total_words; /*!< The total number of words */
dberr_t error; /*!< Error code if any, that is
encountered during query processing */
ib_rbt_t* word_freqs; /*!< RB tree of word frequencies per
document, its elements are of type
fts_word_freq_t */
ib_rbt_t* wildcard_words; /*!< words with wildcard */
bool multi_exist; /*!< multiple FTS_EXIST oper */
byte visiting_sub_exp; /*!< count of nested
fts_ast_visit_sub_exp() */
st_mysql_ftparser* parser; /*!< fts plugin parser */
};
/** For phrase matching, first we collect the documents and the positions
then we match. */
struct fts_match_t {
doc_id_t doc_id; /*!< Document id */
ulint start; /*!< Start the phrase match from
this offset within the positions
vector. */
ib_vector_t* positions; /*!< Offsets of a word in a
document */
};
/** For matching tokens in a phrase search. We use this data structure in
the callback that determines whether a document should be accepted or
rejected for a phrase search. */
struct fts_select_t {
doc_id_t doc_id; /*!< The document id to match */
ulint min_pos; /*!< For found to be TRUE at least
one position must be greater than
min_pos. */
ibool found; /*!< TRUE if found */
fts_word_freq_t*
word_freq; /*!< Word frequency instance of the
current word being looked up in
the FTS index */
};
typedef std::vector<ulint, ut_allocator<ulint> > pos_vector_t;
/** structure defines a set of ranges for original documents, each of which
has a minimum position and maximum position. Text in such range should
contain all words in the proximity search. We will need to count the
words in such range to make sure it is less than the specified distance
of the proximity search */
struct fts_proximity_t {
ulint n_pos; /*!< number of position set, defines
a range (min to max) containing all
matching words */
pos_vector_t min_pos; /*!< the minimum position (in bytes)
of the range */
pos_vector_t max_pos; /*!< the maximum position (in bytes)
of the range */
};
/** The match positions and tokens to match */
struct fts_phrase_t {
fts_phrase_t(const dict_table_t* table)
:
found(false),
match(NULL),
tokens(NULL),
distance(0),
charset(NULL),
heap(NULL),
zip_size(table->space->zip_size()),
proximity_pos(NULL),
parser(NULL)
{
}
/** Match result */
ibool found;
/** Positions within text */
const fts_match_t* match;
/** Tokens to match */
const ib_vector_t* tokens;
/** For matching on proximity distance. Can be 0 for exact match */
ulint distance;
/** Phrase match charset */
CHARSET_INFO* charset;
/** Heap for word processing */
mem_heap_t* heap;
/** ROW_FORMAT=COMPRESSED page size, or 0 */
const ulint zip_size;
/** Position info for proximity search verification. Records the
min and max position of words matched */
fts_proximity_t* proximity_pos;
/** FTS plugin parser */
st_mysql_ftparser* parser;
};
/** Parameter passed to fts phrase match by parser */
struct fts_phrase_param_t {
fts_phrase_t* phrase; /*!< Match phrase instance */
ulint token_index; /*!< Index of token to match next */
mem_heap_t* heap; /*!< Heap for word processing */
};
/** For storing the frequency of a word/term in a document */
struct fts_doc_freq_t {
doc_id_t doc_id; /*!< Document id */
ulint freq; /*!< Frequency of a word in a document */
};
/** To determine the word frequency per document. */
struct fts_word_freq_t {
fts_string_t word; /*!< Word for which we need the freq,
it's allocated on the query heap */
ib_rbt_t* doc_freqs; /*!< RB Tree for storing per document
word frequencies. The elements are
of type fts_doc_freq_t */
ib_uint64_t doc_count; /*!< Total number of documents that
contain this word */
double idf; /*!< Inverse document frequency */
};
/********************************************************************
Callback function to fetch the rows in an FTS INDEX record.
@return always TRUE */
static
ibool
fts_query_index_fetch_nodes(
/*========================*/
void* row, /*!< in: sel_node_t* */
void* user_arg); /*!< in: pointer to ib_vector_t */
/********************************************************************
Read and filter nodes.
@return fts_node_t instance */
static
dberr_t
fts_query_filter_doc_ids(
/*=====================*/
fts_query_t* query, /*!< in: query instance */
const fts_string_t* word, /*!< in: the current word */
fts_word_freq_t* word_freq, /*!< in/out: word frequency */
const fts_node_t* node, /*!< in: current FTS node */
void* data, /*!< in: doc id ilist */
ulint len, /*!< in: doc id ilist size */
ibool calc_doc_count);/*!< in: whether to remember doc
count */
/** Process (nested) sub-expression, create a new result set to store the
sub-expression result by processing nodes under current sub-expression
list. Merge the sub-expression result with that of parent expression list.
@param[in,out] node current root node
@param[in,out] visitor callback function
@param[in,out] arg argument for callback
@return DB_SUCCESS if all go well */
static
dberr_t
fts_ast_visit_sub_exp(
fts_ast_node_t* node,
fts_ast_callback visitor,
void* arg);
#if 0
/*****************************************************************//***
Find a doc_id in a word's ilist.
@return TRUE if found. */
static
ibool
fts_query_find_doc_id(
/*==================*/
fts_select_t* select, /*!< in/out: search the doc id selected,
update the frequency if found. */
void* data, /*!< in: doc id ilist */
ulint len); /*!< in: doc id ilist size */
#endif
/*************************************************************//**
This function implements a simple "blind" query expansion search:
words in documents found in the first search pass will be used as
search arguments to search the document again, thus "expand"
the search result set.
@return DB_SUCCESS if success, otherwise the error code */
static
dberr_t
fts_expand_query(
/*=============*/
dict_index_t* index, /*!< in: FTS index to search */
fts_query_t* query) /*!< in: query result, to be freed
by the client */
MY_ATTRIBUTE((nonnull, warn_unused_result));
/*************************************************************//**
This function finds documents that contain all words in a
phrase or proximity search. And if proximity search, verify
the words are close enough to each other, as in specified distance.
This function is called for phrase and proximity search.
@return TRUE if documents are found, FALSE if otherwise */
static
ibool
fts_phrase_or_proximity_search(
/*===========================*/
fts_query_t* query, /*!< in/out: query instance
query->doc_ids might be instantiated
with qualified doc IDs */
ib_vector_t* tokens); /*!< in: Tokens contain words */
/*************************************************************//**
This function checks whether words in result documents are close to
each other (within proximity range as specified by "distance").
If "distance" is MAX_ULINT, then it will find all combinations of
positions of matching words and store min and max positions
in the "qualified_pos" for later verification.
@return true if words are close to each other, false if otherwise */
static
bool
fts_proximity_get_positions(
/*========================*/
fts_match_t** match, /*!< in: query instance */
ulint num_match, /*!< in: number of matching
items */
ulint distance, /*!< in: distance value
for proximity search */
fts_proximity_t* qualified_pos); /*!< out: the position info
records ranges containing
all matching words. */
#if 0
/********************************************************************
Get the total number of words in a documents. */
static
ulint
fts_query_terms_in_document(
/*========================*/
/*!< out: DB_SUCCESS if all go well
else error code */
fts_query_t* query, /*!< in: FTS query state */
doc_id_t doc_id, /*!< in: the word to check */
ulint* total); /*!< out: total words in document */
#endif
#if 0
/*******************************************************************//**
Print the table used for calculating LCS. */
static
void
fts_print_lcs_table(
/*================*/
const ulint* table, /*!< in: array to print */
ulint n_rows, /*!< in: total no. of rows */
ulint n_cols) /*!< in: total no. of cols */
{
ulint i;
for (i = 0; i < n_rows; ++i) {
ulint j;
printf("\n");
for (j = 0; j < n_cols; ++j) {
printf("%2lu ", FTS_ELEM(table, n_cols, i, j));
}
}
}
/********************************************************************
Find the longest common subsequence between the query string and
the document. */
static
ulint
fts_query_lcs(
/*==========*/
/*!< out: LCS (length) between
two ilists */
const ulint* p1, /*!< in: word positions of query */
ulint len_p1, /*!< in: no. of elements in p1 */
const ulint* p2, /*!< in: word positions within document */
ulint len_p2) /*!< in: no. of elements in p2 */
{
int i;
ulint len = 0;
ulint r = len_p1;
ulint c = len_p2;
ulint size = (r + 1) * (c + 1) * sizeof(ulint);
ulint* table = (ulint*) ut_malloc_nokey(size);
/* Traverse the table backwards, from the last row to the first and
also from the last column to the first. We compute the smaller
common subsequences first, then use the calculated values to determine
the longest common subsequence. The result will be in TABLE[0][0]. */
for (i = r; i >= 0; --i) {
int j;
for (j = c; j >= 0; --j) {
if (p1[i] == (ulint) -1 || p2[j] == (ulint) -1) {
FTS_ELEM(table, c, i, j) = 0;
} else if (p1[i] == p2[j]) {
FTS_ELEM(table, c, i, j) = FTS_ELEM(
table, c, i + 1, j + 1) + 1;
} else {
ulint value;
value = ut_max(
FTS_ELEM(table, c, i + 1, j),
FTS_ELEM(table, c, i, j + 1));
FTS_ELEM(table, c, i, j) = value;
}
}
}
len = FTS_ELEM(table, c, 0, 0);
fts_print_lcs_table(table, r, c);
printf("\nLen=" ULINTPF "\n", len);
ut_free(table);
return(len);
}
#endif
/*******************************************************************//**
Compare two fts_ranking_t instance on their rank value and doc ids in
descending order on the rank and ascending order on doc id.
@return 0 if p1 == p2, < 0 if p1 < p2, > 0 if p1 > p2 */
static
int
fts_query_compare_rank(
/*===================*/
const void* p1, /*!< in: pointer to elem */
const void* p2) /*!< in: pointer to elem */
{
const fts_ranking_t* r1 = (const fts_ranking_t*) p1;
const fts_ranking_t* r2 = (const fts_ranking_t*) p2;
if (r2->rank < r1->rank) {
return(-1);
} else if (r2->rank == r1->rank) {
if (r1->doc_id < r2->doc_id) {
return -1;
}
return r1->doc_id > r2->doc_id;
}
return(1);
}
/*******************************************************************//**
Create words in ranking */
static
void
fts_ranking_words_create(
/*=====================*/
fts_query_t* query, /*!< in: query instance */
fts_ranking_t* ranking) /*!< in: ranking instance */
{
ranking->words = static_cast<byte*>(
mem_heap_zalloc(query->heap, RANKING_WORDS_INIT_LEN));
ranking->words_len = RANKING_WORDS_INIT_LEN;
}
/*
The optimization here is using a char array(bitmap) to replace words rb tree
in fts_ranking_t.
It can save lots of memory except in some cases of QUERY EXPANSION.
'word_map' is used as a word dictionary, in which the key is a word, the value
is a number. In 'fts_ranking_words_add', we first check if the word is in 'word_map'.
if not, we add it into 'word_map', and give it a position(actually a number).
then we set the corresponding bit to '1' at the position in the char array 'words'.
'word_vector' is a useful backup of 'word_map', and we can get a word by its position,
more quickly than searching by value in 'word_map'. we use 'word_vector'
in 'fts_query_calculate_ranking' and 'fts_expand_query'. In the two functions, we need
to scan the bitmap 'words', and get a word when a bit is '1', then we get word_freq
by the word.
*/
/*******************************************************************//**
Add a word into ranking */
static
void
fts_ranking_words_add(
/*==================*/
fts_query_t* query, /*!< in: query instance */
fts_ranking_t* ranking, /*!< in: ranking instance */
const fts_string_t* word) /*!< in: term/word to add */
{
ulint pos;
ulint byte_offset;
ulint bit_offset;
ib_rbt_bound_t parent;
/* Note: we suppose the word map and vector are append-only. */
ut_ad(query->word_vector->size() == rbt_size(query->word_map));
/* We use ib_rbt to simulate a map, f_n_char means position. */
if (rbt_search(query->word_map, &parent, word) == 0) {
fts_string_t* result_word;
result_word = rbt_value(fts_string_t, parent.last);
pos = result_word->f_n_char;
ut_ad(pos < rbt_size(query->word_map));
} else {
/* Add the word to map. */
fts_string_t new_word;
pos = rbt_size(query->word_map);
fts_string_dup(&new_word, word, query->heap);
new_word.f_n_char = pos;
rbt_add_node(query->word_map, &parent, &new_word);
ut_ad(rbt_validate(query->word_map));
query->word_vector->push_back(new_word);
}
/* Check words len */
byte_offset = pos / CHAR_BIT;
if (byte_offset >= ranking->words_len) {
byte* words = ranking->words;
ulint words_len = ranking->words_len;
while (byte_offset >= words_len) {
words_len *= 2;
}
ranking->words = static_cast<byte*>(
mem_heap_zalloc(query->heap, words_len));
memcpy(ranking->words, words, ranking->words_len);
ranking->words_len = words_len;
}
/* Set ranking words */
ut_ad(byte_offset < ranking->words_len);
bit_offset = pos % CHAR_BIT;
ranking->words[byte_offset] = static_cast<byte>(
ranking->words[byte_offset] | 1 << bit_offset);
}
/*******************************************************************//**
Get a word from a ranking
@return true if it's successful */
static
bool
fts_ranking_words_get_next(
/*=======================*/
const fts_query_t* query, /*!< in: query instance */
fts_ranking_t* ranking,/*!< in: ranking instance */
ulint* pos, /*!< in/out: word start pos */
fts_string_t* word) /*!< in/out: term/word to add */
{
bool ret = false;
ulint max_pos = ranking->words_len * CHAR_BIT;
/* Search for next word */
while (*pos < max_pos) {
ulint byte_offset = *pos / CHAR_BIT;
ulint bit_offset = *pos % CHAR_BIT;
if (ranking->words[byte_offset] & (1 << bit_offset)) {
ret = true;
break;
}
*pos += 1;
};
/* Get next word from word vector */
if (ret) {
ut_ad(*pos < query->word_vector->size());
*word = query->word_vector->at((size_t)*pos);
*pos += 1;
}
return ret;
}
/*******************************************************************//**
Add a word if it doesn't exist, to the term freq RB tree. We store
a pointer to the word that is passed in as the argument.
@return pointer to word */
static
fts_word_freq_t*
fts_query_add_word_freq(
/*====================*/
fts_query_t* query, /*!< in: query instance */
const fts_string_t* word) /*!< in: term/word to add */
{
ib_rbt_bound_t parent;
/* Lookup the word in our rb tree and add if it doesn't exist. */
if (rbt_search(query->word_freqs, &parent, word) != 0) {
fts_word_freq_t word_freq;
memset(&word_freq, 0, sizeof(word_freq));
fts_string_dup(&word_freq.word, word, query->heap);
word_freq.doc_count = 0;
static_assert(!offsetof(fts_doc_freq_t, doc_id), "ABI");
word_freq.doc_freqs = rbt_create(
sizeof(fts_doc_freq_t), fts_doc_id_cmp);
parent.last = rbt_add_node(
query->word_freqs, &parent, &word_freq);
query->total_size += word->f_len
+ SIZEOF_RBT_CREATE
+ SIZEOF_RBT_NODE_ADD
+ sizeof(fts_word_freq_t);
}
return(rbt_value(fts_word_freq_t, parent.last));
}
/*******************************************************************//**
Add a doc id if it doesn't exist, to the doc freq RB tree.
@return pointer to word */
static
fts_doc_freq_t*
fts_query_add_doc_freq(
/*===================*/
fts_query_t* query, /*!< in: query instance */
ib_rbt_t* doc_freqs, /*!< in: rb tree of fts_doc_freq_t */
doc_id_t doc_id) /*!< in: doc id to add */
{
ib_rbt_bound_t parent;
/* Lookup the doc id in our rb tree and add if it doesn't exist. */
if (rbt_search(doc_freqs, &parent, &doc_id) != 0) {
fts_doc_freq_t doc_freq;
memset(&doc_freq, 0, sizeof(doc_freq));
doc_freq.freq = 0;
doc_freq.doc_id = doc_id;
parent.last = rbt_add_node(doc_freqs, &parent, &doc_freq);
query->total_size += SIZEOF_RBT_NODE_ADD
+ sizeof(fts_doc_freq_t);
}
return(rbt_value(fts_doc_freq_t, parent.last));
}
/*******************************************************************//**
Add the doc id to the query set only if it's not in the
deleted array. */
static
void
fts_query_union_doc_id(
/*===================*/
fts_query_t* query, /*!< in: query instance */
doc_id_t doc_id, /*!< in: the doc id to add */
fts_rank_t rank) /*!< in: if non-zero, it is the
rank associated with the doc_id */
{
ib_rbt_bound_t parent;
ulint size = ib_vector_size(query->deleted->doc_ids);
doc_id_t* updates = (doc_id_t*) query->deleted->doc_ids->data;
/* Check if the doc id is deleted and it's not already in our set. */
if (fts_bsearch(updates, 0, static_cast<int>(size), doc_id) < 0
&& rbt_search(query->doc_ids, &parent, &doc_id) != 0) {
fts_ranking_t ranking;
ranking.rank = rank;
ranking.doc_id = doc_id;
fts_ranking_words_create(query, &ranking);
rbt_add_node(query->doc_ids, &parent, &ranking);
query->total_size += SIZEOF_RBT_NODE_ADD
+ sizeof(fts_ranking_t) + RANKING_WORDS_INIT_LEN;
}
}
/*******************************************************************//**
Remove the doc id from the query set only if it's not in the
deleted set. */
static
void
fts_query_remove_doc_id(
/*====================*/
fts_query_t* query, /*!< in: query instance */
doc_id_t doc_id) /*!< in: the doc id to add */
{
ib_rbt_bound_t parent;
ulint size = ib_vector_size(query->deleted->doc_ids);
doc_id_t* updates = (doc_id_t*) query->deleted->doc_ids->data;
/* Check if the doc id is deleted and it's in our set. */
if (fts_bsearch(updates, 0, static_cast<int>(size), doc_id) < 0
&& rbt_search(query->doc_ids, &parent, &doc_id) == 0) {
ut_free(rbt_remove_node(query->doc_ids, parent.last));
ut_ad(query->total_size >=
SIZEOF_RBT_NODE_ADD + sizeof(fts_ranking_t));
query->total_size -= SIZEOF_RBT_NODE_ADD
+ sizeof(fts_ranking_t);
}
}
/*******************************************************************//**
Find the doc id in the query set but not in the deleted set, artificially
downgrade or upgrade its ranking by a value and make/initialize its ranking
under or above its normal range 0 to 1. This is used for Boolean Search
operator such as Negation operator, which makes word's contribution to the
row's relevance to be negative */
static
void
fts_query_change_ranking(
/*====================*/
fts_query_t* query, /*!< in: query instance */
doc_id_t doc_id, /*!< in: the doc id to add */
ibool downgrade) /*!< in: Whether to downgrade ranking */
{
ib_rbt_bound_t parent;
ulint size = ib_vector_size(query->deleted->doc_ids);
doc_id_t* updates = (doc_id_t*) query->deleted->doc_ids->data;
/* Check if the doc id is deleted and it's in our set. */
if (fts_bsearch(updates, 0, static_cast<int>(size), doc_id) < 0
&& rbt_search(query->doc_ids, &parent, &doc_id) == 0) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, parent.last);
ranking->rank += downgrade ? RANK_DOWNGRADE : RANK_UPGRADE;
/* Allow at most 2 adjustment by RANK_DOWNGRADE (-0.5)
and RANK_UPGRADE (0.5) */
if (ranking->rank >= 1.0F) {
ranking->rank = 1.0F;
} else if (ranking->rank <= -1.0F) {
ranking->rank = -1.0F;
}
}
}
/*******************************************************************//**
Check the doc id in the query set only if it's not in the
deleted array. The doc ids that were found are stored in
another rb tree (fts_query_t::intersect). */
static
void
fts_query_intersect_doc_id(
/*=======================*/
fts_query_t* query, /*!< in: query instance */
doc_id_t doc_id, /*!< in: the doc id to add */
fts_rank_t rank) /*!< in: if non-zero, it is the
rank associated with the doc_id */
{
ib_rbt_bound_t parent;
ulint size = ib_vector_size(query->deleted->doc_ids);
doc_id_t* updates = (doc_id_t*) query->deleted->doc_ids->data;
fts_ranking_t* ranking= NULL;
/* There are three types of intersect:
1. '+a': doc_ids is empty, add doc into intersect if it matches 'a'.
2. 'a +b': docs match 'a' is in doc_ids, add doc into intersect
if it matches 'b'. if the doc is also in doc_ids, then change the
doc's rank, and add 'a' in doc's words.
3. '+a +b': docs matching '+a' is in doc_ids, add doc into intersect
if it matches 'b' and it's in doc_ids.(multi_exist = true). */
/* Check if the doc id is deleted and it's in our set */
if (fts_bsearch(updates, 0, static_cast<int>(size), doc_id) < 0) {
fts_ranking_t new_ranking;
if (rbt_search(query->doc_ids, &parent, &doc_id) != 0) {
if (query->multi_exist) {
return;
} else {
new_ranking.words = NULL;
}
} else {
ranking = rbt_value(fts_ranking_t, parent.last);
/* We've just checked the doc id before */
if (ranking->words == NULL) {
ut_ad(rbt_search(query->intersection, &parent,
ranking) == 0);
return;
}
/* Merge rank */
rank += ranking->rank;
if (rank >= 1.0F) {
rank = 1.0F;
} else if (rank <= -1.0F) {
rank = -1.0F;
}
/* Take words */
new_ranking.words = ranking->words;
new_ranking.words_len = ranking->words_len;
}
new_ranking.rank = rank;
new_ranking.doc_id = doc_id;
if (rbt_search(query->intersection, &parent,
&new_ranking) != 0) {
if (new_ranking.words == NULL) {
fts_ranking_words_create(query, &new_ranking);
query->total_size += RANKING_WORDS_INIT_LEN;
} else {
/* Note that the intersection has taken
ownership of the ranking data. */
ranking->words = NULL;
}
rbt_add_node(query->intersection,
&parent, &new_ranking);
query->total_size += SIZEOF_RBT_NODE_ADD
+ sizeof(fts_ranking_t);
}
}
}
/*******************************************************************//**
Free the document ranking rb tree. */
static
void
fts_query_free_doc_ids(
/*===================*/
fts_query_t* query, /*!< in: query instance */
ib_rbt_t* doc_ids) /*!< in: rb tree to free */
{
const ib_rbt_node_t* node;
for (node = rbt_first(doc_ids); node; node = rbt_first(doc_ids)) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, node);
if (ranking->words) {
ranking->words = NULL;
}
ut_free(rbt_remove_node(doc_ids, node));
ut_ad(query->total_size >=
SIZEOF_RBT_NODE_ADD + sizeof(fts_ranking_t));
query->total_size -= SIZEOF_RBT_NODE_ADD
+ sizeof(fts_ranking_t);
}
rbt_free(doc_ids);
ut_ad(query->total_size >= SIZEOF_RBT_CREATE);
query->total_size -= SIZEOF_RBT_CREATE;
}
/*******************************************************************//**
Add the word to the documents "list" of matching words from
the query. We make a copy of the word from the query heap. */
static
void
fts_query_add_word_to_document(
/*===========================*/
fts_query_t* query, /*!< in: query to update */
doc_id_t doc_id, /*!< in: the document to update */
const fts_string_t* word) /*!< in: the token to add */
{
ib_rbt_bound_t parent;
fts_ranking_t* ranking = NULL;
if (query->flags == FTS_OPT_RANKING) {
return;
}
/* First we search the intersection RB tree as it could have
taken ownership of the words rb tree instance. */
if (query->intersection
&& rbt_search(query->intersection, &parent, &doc_id) == 0) {
ranking = rbt_value(fts_ranking_t, parent.last);
}
if (ranking == NULL
&& rbt_search(query->doc_ids, &parent, &doc_id) == 0) {
ranking = rbt_value(fts_ranking_t, parent.last);
}
if (ranking != NULL) {
fts_ranking_words_add(query, ranking, word);
}
}
/*******************************************************************//**
Check the node ilist. */
static
void
fts_query_check_node(
/*=================*/
fts_query_t* query, /*!< in: query to update */
const fts_string_t* token, /*!< in: the token to search */
const fts_node_t* node) /*!< in: node to check */
{
/* Skip nodes whose doc ids are out range. */
if (query->oper == FTS_EXIST
&& ((query->upper_doc_id > 0
&& node->first_doc_id > query->upper_doc_id)
|| (query->lower_doc_id > 0
&& node->last_doc_id < query->lower_doc_id))) {
/* Ignore */
} else {
int ret;
ib_rbt_bound_t parent;
ulint ilist_size = node->ilist_size;
fts_word_freq_t*word_freqs;
/* The word must exist. */
ret = rbt_search(query->word_freqs, &parent, token);
ut_a(ret == 0);
word_freqs = rbt_value(fts_word_freq_t, parent.last);
query->error = fts_query_filter_doc_ids(
query, token, word_freqs, node,
node->ilist, ilist_size, TRUE);
}
}
/*****************************************************************//**
Search index cache for word with wildcard match.
@return number of words matched */
static
ulint
fts_cache_find_wildcard(
/*====================*/
fts_query_t* query, /*!< in: query instance */
const fts_index_cache_t*index_cache, /*!< in: cache to search */
const fts_string_t* token) /*!< in: token to search */
{
ib_rbt_bound_t parent;
const ib_vector_t* nodes = NULL;
fts_string_t srch_text;
byte term[FTS_MAX_WORD_LEN + 1];
ulint num_word = 0;
srch_text.f_len = (token->f_str[token->f_len - 1] == '%')
? token->f_len - 1
: token->f_len;
strncpy((char*) term, (char*) token->f_str, srch_text.f_len);
term[srch_text.f_len] = '\0';
srch_text.f_str = term;
/* Lookup the word in the rb tree */
if (rbt_search_cmp(index_cache->words, &parent, &srch_text, NULL,
innobase_fts_text_cmp_prefix) == 0) {
const fts_tokenizer_word_t* word;
ulint i;
const ib_rbt_node_t* cur_node;
ibool forward = FALSE;
word = rbt_value(fts_tokenizer_word_t, parent.last);
cur_node = parent.last;
while (innobase_fts_text_cmp_prefix(
index_cache->charset, &srch_text, &word->text) == 0) {
nodes = word->nodes;
for (i = 0; nodes && i < ib_vector_size(nodes); ++i) {
int ret;
const fts_node_t* node;
ib_rbt_bound_t freq_parent;
fts_word_freq_t* word_freqs;
node = static_cast<const fts_node_t*>(
ib_vector_get_const(nodes, i));
ret = rbt_search(query->word_freqs,
&freq_parent,
&srch_text);
ut_a(ret == 0);
word_freqs = rbt_value(
fts_word_freq_t,
freq_parent.last);
query->error = fts_query_filter_doc_ids(
query, &srch_text,
word_freqs, node,
node->ilist, node->ilist_size, TRUE);
if (query->error != DB_SUCCESS) {
return(0);
}
}
num_word++;
if (!forward) {
cur_node = rbt_prev(
index_cache->words, cur_node);
} else {
cont_search:
cur_node = rbt_next(
index_cache->words, cur_node);
}
if (!cur_node) {
break;
}
word = rbt_value(fts_tokenizer_word_t, cur_node);
}
if (!forward) {
forward = TRUE;
cur_node = parent.last;
goto cont_search;
}
}
return(num_word);
}
/*****************************************************************//**
Set difference.
@return DB_SUCCESS if all go well */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_difference(
/*=================*/
fts_query_t* query, /*!< in: query instance */
const fts_string_t* token) /*!< in: token to search */
{
ulint n_doc_ids= 0;
trx_t* trx = query->trx;
dict_table_t* table = query->index->table;
ut_a(query->oper == FTS_IGNORE);
#ifdef FTS_INTERNAL_DIAG_PRINT
{
ib::info out;
out << "DIFFERENCE: Searching: '";
out.write(token->f_str, token->f_len);
out << "'";
}
#endif
if (query->doc_ids) {
n_doc_ids = rbt_size(query->doc_ids);
}
/* There is nothing we can substract from an empty set. */
if (query->doc_ids && !rbt_empty(query->doc_ids)) {
ulint i;
fts_fetch_t fetch;
const ib_vector_t* nodes;
const fts_index_cache_t*index_cache;
que_t* graph = NULL;
fts_cache_t* cache = table->fts->cache;
dberr_t error;
mysql_mutex_lock(&cache->lock);
index_cache = fts_find_index_cache(cache, query->index);
/* Must find the index cache */
ut_a(index_cache != NULL);
/* Search the cache for a matching word first. */
if (query->cur_node->term.wildcard
&& query->flags != FTS_PROXIMITY
&& query->flags != FTS_PHRASE) {
fts_cache_find_wildcard(query, index_cache, token);
} else {
nodes = fts_cache_find_word(index_cache, token);
for (i = 0; nodes && i < ib_vector_size(nodes)
&& query->error == DB_SUCCESS; ++i) {
const fts_node_t* node;
node = static_cast<const fts_node_t*>(
ib_vector_get_const(nodes, i));
fts_query_check_node(query, token, node);
}
}
mysql_mutex_unlock(&cache->lock);
/* error is passed by 'query->error' */
if (query->error != DB_SUCCESS) {
ut_ad(query->error == DB_FTS_EXCEED_RESULT_CACHE_LIMIT);
return(query->error);
}
/* Setup the callback args for filtering and
consolidating the ilist. */
fetch.read_arg = query;
fetch.read_record = fts_query_index_fetch_nodes;
error = fts_index_fetch_nodes(
trx, &graph, &query->fts_index_table, token, &fetch);
/* DB_FTS_EXCEED_RESULT_CACHE_LIMIT passed by 'query->error' */
ut_ad(!(query->error != DB_SUCCESS && error != DB_SUCCESS));
if (error != DB_SUCCESS) {
query->error = error;
}
que_graph_free(graph);
}
/* The size can't increase. */
ut_a(rbt_size(query->doc_ids) <= n_doc_ids);
return(query->error);
}
/* Free the query intersection
@param query query instance */
static void fts_query_free_intersection(fts_query_t* query)
{
fts_query_free_doc_ids(query, query->intersection);
query->intersection = NULL;
}
/*****************************************************************//**
Intersect the token doc ids with the current set.
@return DB_SUCCESS if all go well */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_intersect(
/*================*/
fts_query_t* query, /*!< in: query instance */
const fts_string_t* token) /*!< in: the token to search */
{
trx_t* trx = query->trx;
dict_table_t* table = query->index->table;
ut_a(query->oper == FTS_EXIST);
#ifdef FTS_INTERNAL_DIAG_PRINT
{
ib::info out;
out << "INTERSECT: Searching: '";
out.write(token->f_str, token->f_len);
out << "'";
}
#endif
/* If the words set is not empty and multi exist is true,
we know the intersection set is empty in advance. */
if (!(rbt_empty(query->doc_ids) && query->multi_exist)) {
ulint n_doc_ids = 0;
ulint i;
fts_fetch_t fetch;
const ib_vector_t* nodes;
const fts_index_cache_t*index_cache;
que_t* graph = NULL;
fts_cache_t* cache = table->fts->cache;
dberr_t error;
ut_a(!query->intersection);
n_doc_ids = rbt_size(query->doc_ids);
/* Create the rb tree that will hold the doc ids of
the intersection. */
static_assert(!offsetof(fts_ranking_t, doc_id), "ABI");
query->intersection = rbt_create(
sizeof(fts_ranking_t), fts_doc_id_cmp);
query->total_size += SIZEOF_RBT_CREATE;
/* This is to avoid decompressing the ilist if the
node's ilist doc ids are out of range. */
if (!rbt_empty(query->doc_ids) && query->multi_exist) {
const ib_rbt_node_t* node;
doc_id_t* doc_id;
node = rbt_first(query->doc_ids);
doc_id = rbt_value(doc_id_t, node);
query->lower_doc_id = *doc_id;
node = rbt_last(query->doc_ids);
doc_id = rbt_value(doc_id_t, node);
query->upper_doc_id = *doc_id;
} else {
query->lower_doc_id = 0;
query->upper_doc_id = 0;
}
/* Search the cache for a matching word first. */
mysql_mutex_lock(&cache->lock);
/* Search for the index specific cache. */
index_cache = fts_find_index_cache(cache, query->index);
/* Must find the index cache. */
ut_a(index_cache != NULL);
if (query->cur_node->term.wildcard) {
/* Wildcard search the index cache */
fts_cache_find_wildcard(query, index_cache, token);
} else {
nodes = fts_cache_find_word(index_cache, token);
for (i = 0; nodes && i < ib_vector_size(nodes)
&& query->error == DB_SUCCESS; ++i) {
const fts_node_t* node;
node = static_cast<const fts_node_t*>(
ib_vector_get_const(nodes, i));
fts_query_check_node(query, token, node);
}
}
mysql_mutex_unlock(&cache->lock);
/* error is passed by 'query->error' */
if (query->error != DB_SUCCESS) {
ut_ad(query->error == DB_FTS_EXCEED_RESULT_CACHE_LIMIT);
fts_query_free_intersection(query);
return(query->error);
}
/* Setup the callback args for filtering and
consolidating the ilist. */
fetch.read_arg = query;
fetch.read_record = fts_query_index_fetch_nodes;
error = fts_index_fetch_nodes(
trx, &graph, &query->fts_index_table, token, &fetch);
/* DB_FTS_EXCEED_RESULT_CACHE_LIMIT passed by 'query->error' */
ut_ad(!(query->error != DB_SUCCESS && error != DB_SUCCESS));
if (error != DB_SUCCESS) {
query->error = error;
}
que_graph_free(graph);
if (query->error == DB_SUCCESS) {
/* Make the intesection (rb tree) the current doc id
set and free the old set. */
fts_query_free_doc_ids(query, query->doc_ids);
query->doc_ids = query->intersection;
query->intersection = NULL;
ut_a(!query->multi_exist || (query->multi_exist
&& rbt_size(query->doc_ids) <= n_doc_ids));
} else if (query->intersection) {
fts_query_free_intersection(query);
}
}
return(query->error);
}
/*****************************************************************//**
Query index cache.
@return DB_SUCCESS if all go well */
static
dberr_t
fts_query_cache(
/*============*/
fts_query_t* query, /*!< in/out: query instance */
const fts_string_t* token) /*!< in: token to search */
{
const fts_index_cache_t*index_cache;
dict_table_t* table = query->index->table;
fts_cache_t* cache = table->fts->cache;
/* Search the cache for a matching word first. */
mysql_mutex_lock(&cache->lock);
/* Search for the index specific cache. */
index_cache = fts_find_index_cache(cache, query->index);
/* Must find the index cache. */
ut_a(index_cache != NULL);
if (query->cur_node->term.wildcard
&& query->flags != FTS_PROXIMITY
&& query->flags != FTS_PHRASE) {
/* Wildcard search the index cache */
fts_cache_find_wildcard(query, index_cache, token);
} else {
const ib_vector_t* nodes;
ulint i;
nodes = fts_cache_find_word(index_cache, token);
for (i = 0; nodes && i < ib_vector_size(nodes)
&& query->error == DB_SUCCESS; ++i) {
const fts_node_t* node;
node = static_cast<const fts_node_t*>(
ib_vector_get_const(nodes, i));
fts_query_check_node(query, token, node);
}
}
mysql_mutex_unlock(&cache->lock);
return(query->error);
}
/*****************************************************************//**
Set union.
@return DB_SUCCESS if all go well */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_union(
/*============*/
fts_query_t* query, /*!< in: query instance */
fts_string_t* token) /*!< in: token to search */
{
fts_fetch_t fetch;
ulint n_doc_ids = 0;
trx_t* trx = query->trx;
que_t* graph = NULL;
dberr_t error;
ut_a(query->oper == FTS_NONE || query->oper == FTS_DECR_RATING ||
query->oper == FTS_NEGATE || query->oper == FTS_INCR_RATING);
#ifdef FTS_INTERNAL_DIAG_PRINT
{
ib::info out;
out << "UNION: Searching: '";
out.write(token->f_str, token->f_len);
out << "'";
}
#endif
if (query->doc_ids) {
n_doc_ids = rbt_size(query->doc_ids);
}
if (token->f_len == 0) {
return(query->error);
}
fts_query_cache(query, token);
/* Setup the callback args for filtering and
consolidating the ilist. */
fetch.read_arg = query;
fetch.read_record = fts_query_index_fetch_nodes;
/* Read the nodes from disk. */
error = fts_index_fetch_nodes(
trx, &graph, &query->fts_index_table, token, &fetch);
/* DB_FTS_EXCEED_RESULT_CACHE_LIMIT passed by 'query->error' */
ut_ad(!(query->error != DB_SUCCESS && error != DB_SUCCESS));
if (error != DB_SUCCESS) {
query->error = error;
}
que_graph_free(graph);
if (query->error == DB_SUCCESS) {
/* The size can't decrease. */
ut_a(rbt_size(query->doc_ids) >= n_doc_ids);
/* Calculate the number of doc ids that were added to
the current doc id set. */
if (query->doc_ids) {
n_doc_ids = rbt_size(query->doc_ids) - n_doc_ids;
}
}
return(query->error);
}
/*****************************************************************//**
Depending upon the current query operator process the doc id.
return DB_SUCCESS if all go well
or return DB_FTS_EXCEED_RESULT_CACHE_LIMIT */
static
dberr_t
fts_query_process_doc_id(
/*=====================*/
fts_query_t* query, /*!< in: query instance */
doc_id_t doc_id, /*!< in: doc id to process */
fts_rank_t rank) /*!< in: if non-zero, it is the
rank associated with the doc_id */
{
if (query->flags == FTS_OPT_RANKING) {
return(DB_SUCCESS);
}
switch (query->oper) {
case FTS_NONE:
fts_query_union_doc_id(query, doc_id, rank);
break;
case FTS_EXIST:
fts_query_intersect_doc_id(query, doc_id, rank);
break;
case FTS_IGNORE:
fts_query_remove_doc_id(query, doc_id);
break;
case FTS_NEGATE:
fts_query_change_ranking(query, doc_id, TRUE);
break;
case FTS_DECR_RATING:
fts_query_union_doc_id(query, doc_id, rank);
fts_query_change_ranking(query, doc_id, TRUE);
break;
case FTS_INCR_RATING:
fts_query_union_doc_id(query, doc_id, rank);
fts_query_change_ranking(query, doc_id, FALSE);
break;
default:
ut_error;
}
if (query->total_size > fts_result_cache_limit) {
return(DB_FTS_EXCEED_RESULT_CACHE_LIMIT);
} else {
return(DB_SUCCESS);
}
}
/*****************************************************************//**
Merge two result sets. */
static
dberr_t
fts_merge_doc_ids(
/*==============*/
fts_query_t* query, /*!< in,out: query instance */
const ib_rbt_t* doc_ids) /*!< in: result set to merge */
{
const ib_rbt_node_t* node;
DBUG_ENTER("fts_merge_doc_ids");
ut_a(!query->intersection);
/* To process FTS_EXIST operation (intersection), we need
to create a new result set for fts_query_intersect(). */
if (query->oper == FTS_EXIST) {
static_assert(!offsetof(fts_ranking_t, doc_id), "ABI");
query->intersection = rbt_create(
sizeof(fts_ranking_t), fts_doc_id_cmp);
query->total_size += SIZEOF_RBT_CREATE;
}
/* Merge the elements to the result set. */
for (node = rbt_first(doc_ids); node; node = rbt_next(doc_ids, node)) {
fts_ranking_t* ranking;
ulint pos = 0;
fts_string_t word;
ranking = rbt_value(fts_ranking_t, node);
query->error = fts_query_process_doc_id(
query, ranking->doc_id, ranking->rank);
if (query->error != DB_SUCCESS) {
if (query->intersection) {
ut_a(query->oper == FTS_EXIST);
fts_query_free_intersection(query);
}
DBUG_RETURN(query->error);
}
/* Merge words. Don't need to take operator into account. */
ut_a(ranking->words);
while (fts_ranking_words_get_next(query, ranking, &pos, &word)) {
fts_query_add_word_to_document(query, ranking->doc_id,
&word);
}
}
/* If it is an intersection operation, reset query->doc_ids
to query->intersection and free the old result list. */
if (query->oper == FTS_EXIST && query->intersection != NULL) {
fts_query_free_doc_ids(query, query->doc_ids);
query->doc_ids = query->intersection;
query->intersection = NULL;
}
DBUG_RETURN(DB_SUCCESS);
}
/*****************************************************************//**
Skip non-whitespace in a string. Move ptr to the next word boundary.
@return pointer to first whitespace character or end */
UNIV_INLINE
byte*
fts_query_skip_word(
/*================*/
byte* ptr, /*!< in: start of scan */
const byte* end) /*!< in: pointer to end of string */
{
/* TODO: Does this have to be UTF-8 too ? */
while (ptr < end && !(ispunct(*ptr) || isspace(*ptr))) {
++ptr;
}
return(ptr);
}
/*****************************************************************//**
Check whether the remaining terms in the phrase match the text.
@return TRUE if matched else FALSE */
static
ibool
fts_query_match_phrase_terms(
/*=========================*/
fts_phrase_t* phrase, /*!< in: phrase to match */
byte** start, /*!< in/out: text to search, we can't
make this const becase we need to
first convert the string to
lowercase */
const byte* end, /*!< in: pointer to the end of
the string to search */
mem_heap_t* heap) /*!< in: heap */
{
ulint i;
byte* ptr = *start;
const ib_vector_t* tokens = phrase->tokens;
ulint distance = phrase->distance;
/* We check only from the second term onwards, since the first
must have matched otherwise we wouldn't be here. */
for (i = 1; ptr < end && i < ib_vector_size(tokens); /* No op */) {
fts_string_t match;
fts_string_t cmp_str;
const fts_string_t* token;
int result;
ulint ret;
ret = innobase_mysql_fts_get_token(
phrase->charset, ptr,
const_cast<byte*>(end), &match);
if (match.f_len > 0) {
/* Get next token to match. */
token = static_cast<const fts_string_t*>(
ib_vector_get_const(tokens, i));
cmp_str = fts_string_dup_casedn(phrase->charset,
match, heap);
result = innobase_fts_text_cmp(
phrase->charset, token, &cmp_str);
/* Skip the rest of the tokens if this one doesn't
match and the proximity distance is exceeded. */
if (result
&& (distance == ULINT_UNDEFINED
|| distance == 0)) {
break;
}
/* This token matched move to the next token. */
if (result == 0) {
/* Advance the text to search by the length
of the last token. */
ptr += ret;
/* Advance to the next token. */
++i;
} else {
ut_a(distance != ULINT_UNDEFINED);
ptr = fts_query_skip_word(ptr, end);
}
/* Distance can be 0 for exact matches. */
if (distance != ULINT_UNDEFINED && distance > 0) {
--distance;
}
} else {
ptr += ret;
}
}
*start = ptr;
/* Can't be greater than the number of elements. */
ut_a(i <= ib_vector_size(tokens));
/* This is the case for multiple words. */
if (i == ib_vector_size(tokens)) {
phrase->found = TRUE;
}
return(phrase->found);
}
/*****************************************************************//**
Callback function to count the number of words in position ranges,
and see whether the word count is in specified "phrase->distance"
@return true if the number of characters is less than the "distance" */
static
bool
fts_proximity_is_word_in_range(
/*===========================*/
const fts_phrase_t*
phrase, /*!< in: phrase with the search info */
byte* start, /*!< in: text to search */
ulint total_len) /*!< in: length of text */
{
fts_proximity_t* proximity_pos = phrase->proximity_pos;
ut_ad(proximity_pos->n_pos == proximity_pos->min_pos.size());
ut_ad(proximity_pos->n_pos == proximity_pos->max_pos.size());
/* Search each matched position pair (with min and max positions)
and count the number of words in the range */
for (ulint i = 0; i < proximity_pos->n_pos; i++) {
ulint cur_pos = proximity_pos->min_pos[i];
ulint n_word = 0;
ut_ad(proximity_pos->max_pos[i] <= total_len);
/* Walk through words in the range and count them */
while (cur_pos <= proximity_pos->max_pos[i]) {
ulint len;
fts_string_t str;
len = innobase_mysql_fts_get_token(
phrase->charset,
start + cur_pos,
start + total_len, &str);
if (len == 0) {
break;
}
/* Advances position with "len" bytes */
cur_pos += len;
/* Record the number of words */
if (str.f_n_char > 0) {
n_word++;
}
if (n_word > phrase->distance) {
break;
}
}
/* Check if the number of words is less than specified
"distance" */
if (n_word && n_word <= phrase->distance) {
return(true);
}
}
return(false);
}
/*****************************************************************//**
FTS plugin parser 'myql_add_word' callback function for phrase match
Refer to 'st_mysql_ftparser_param' for more detail.
@return 0 if match, or return non-zero */
static
int
fts_query_match_phrase_add_word_for_parser(
/*=======================================*/
MYSQL_FTPARSER_PARAM* param, /*!< in: parser param */
const char* word, /*!< in: token */
int word_len, /*!< in: token length */
MYSQL_FTPARSER_BOOLEAN_INFO*)
{
fts_phrase_param_t* phrase_param;
fts_phrase_t* phrase;
const ib_vector_t* tokens;
fts_string_t match;
fts_string_t cmp_str;
const fts_string_t* token;
int result;
mem_heap_t* heap;
phrase_param = static_cast<fts_phrase_param_t*>(param->mysql_ftparam);
heap = phrase_param->heap;
phrase = phrase_param->phrase;
tokens = phrase->tokens;
/* In case plugin parser doesn't check return value */
if (phrase_param->token_index == ib_vector_size(tokens)) {
return(1);
}
match.f_str = (uchar *)(word);
match.f_len = ulint(word_len);
match.f_n_char= fts_get_token_size(phrase->charset, word, match.f_len);
if (match.f_len > 0) {
/* Get next token to match. */
ut_a(phrase_param->token_index < ib_vector_size(tokens));
token = static_cast<const fts_string_t*>(
ib_vector_get_const(tokens, phrase_param->token_index));
cmp_str = fts_string_dup_casedn(phrase->charset, match, heap);
result = innobase_fts_text_cmp(
phrase->charset, token, &cmp_str);
if (result == 0) {
phrase_param->token_index++;
} else {
return(1);
}
}
/* Can't be greater than the number of elements. */
ut_a(phrase_param->token_index <= ib_vector_size(tokens));
/* This is the case for multiple words. */
if (phrase_param->token_index == ib_vector_size(tokens)) {
phrase->found = TRUE;
}
return(static_cast<int>(phrase->found));
}
/*****************************************************************//**
Check whether the terms in the phrase match the text.
@return TRUE if matched else FALSE */
static
ibool
fts_query_match_phrase_terms_by_parser(
/*===================================*/
fts_phrase_param_t* phrase_param, /* in/out: phrase param */
st_mysql_ftparser* parser, /* in: plugin fts parser */
byte* text, /* in: text to check */
ulint len) /* in: text length */
{
MYSQL_FTPARSER_PARAM param;
ut_a(parser);
/* Set paramters for param */
param.mysql_parse = fts_tokenize_document_internal;
param.mysql_add_word = fts_query_match_phrase_add_word_for_parser;
param.mysql_ftparam = phrase_param;
param.cs = phrase_param->phrase->charset;
param.doc = reinterpret_cast<char*>(text);
param.length = static_cast<int>(len);
param.mode= MYSQL_FTPARSER_WITH_STOPWORDS;
PARSER_INIT(parser, &param);
parser->parse(&param);
PARSER_DEINIT(parser, &param);
return(phrase_param->phrase->found);
}
/*****************************************************************//**
Callback function to fetch and search the document.
@return TRUE if matched else FALSE */
static
ibool
fts_query_match_phrase(
/*===================*/
fts_phrase_t* phrase, /*!< in: phrase to match */
byte* start, /*!< in: text to search, we can't make
this const becase we need to first
convert the string to lowercase */
ulint cur_len, /*!< in: length of text */
ulint prev_len, /*!< in: total length for searched
doc fields*/
mem_heap_t* heap) /* heap */
{
ulint i;
const fts_string_t* first;
const byte* end = start + cur_len;
const ib_vector_t* tokens = phrase->tokens;
const ib_vector_t* positions = phrase->match->positions;
ut_a(!phrase->found);
ut_a(phrase->match->doc_id > 0);
ut_a(ib_vector_size(tokens) > 0);
ut_a(ib_vector_size(positions) > 0);
first = static_cast<const fts_string_t*>(
ib_vector_get_const(tokens, 0));
ut_a(phrase->match->start < ib_vector_size(positions));
for (i = phrase->match->start; i < ib_vector_size(positions); ++i) {
ulint pos;
byte* ptr = start;
pos = *(ulint*) ib_vector_get_const(positions, i);
if (pos == ULINT_UNDEFINED) {
break;
}
if (pos < prev_len) {
continue;
}
/* Document positions are calculated from the beginning
of the first field, need to save the length for each
searched field to adjust the doc position when search
phrases. */
pos -= prev_len;
ptr = start + pos;
/* Within limits ? */
if (ptr >= end) {
break;
}
if (phrase->parser) {
fts_phrase_param_t phrase_param;
phrase_param.phrase = phrase;
phrase_param.token_index = 0;
phrase_param.heap = heap;
if (fts_query_match_phrase_terms_by_parser(
&phrase_param,
phrase->parser,
ptr,
ulint(end - ptr))) {
break;
}
} else {
fts_string_t match;
fts_string_t cmp_str;
ulint ret;
match.f_str = ptr;
ret = innobase_mysql_fts_get_token(
phrase->charset, start + pos,
const_cast<byte*>(end), &match);
if (match.f_len == 0) {
break;
}
cmp_str = fts_string_dup_casedn(phrase->charset,
match, heap);
if (innobase_fts_text_cmp(
phrase->charset, first, &cmp_str) == 0) {
/* This is the case for the single word
in the phrase. */
if (ib_vector_size(phrase->tokens) == 1) {
phrase->found = TRUE;
break;
}
ptr += ret;
/* Match the remaining terms in the phrase. */
if (fts_query_match_phrase_terms(phrase, &ptr,
end, heap)) {
break;
}
}
}
}
return(phrase->found);
}
/*****************************************************************//**
Callback function to fetch and search the document.
@return whether the phrase is found */
static
ibool
fts_query_fetch_document(
/*=====================*/
void* row, /*!< in: sel_node_t* */
void* user_arg) /*!< in: fts_doc_t* */
{
que_node_t* exp;
sel_node_t* node = static_cast<sel_node_t*>(row);
fts_phrase_t* phrase = static_cast<fts_phrase_t*>(user_arg);
ulint prev_len = 0;
ulint total_len = 0;
byte* document_text = NULL;
exp = node->select_list;
phrase->found = FALSE;
/* For proximity search, we will need to get the whole document
from all fields, so first count the total length of the document
from all the fields */
if (phrase->proximity_pos) {
while (exp) {
ulint field_len;
dfield_t* dfield = que_node_get_val(exp);
byte* data = static_cast<byte*>(
dfield_get_data(dfield));
if (dfield_is_ext(dfield)) {
ulint local_len = dfield_get_len(dfield);
local_len -= BTR_EXTERN_FIELD_REF_SIZE;
field_len = mach_read_from_4(
data + local_len + BTR_EXTERN_LEN + 4);
} else {
field_len = dfield_get_len(dfield);
}
if (field_len != UNIV_SQL_NULL) {
total_len += field_len + 1;
}
exp = que_node_get_next(exp);
}
document_text = static_cast<byte*>(mem_heap_zalloc(
phrase->heap, total_len));
if (!document_text) {
return(FALSE);
}
}
exp = node->select_list;
while (exp) {
dfield_t* dfield = que_node_get_val(exp);
byte* data = static_cast<byte*>(
dfield_get_data(dfield));
ulint cur_len;
if (dfield_is_ext(dfield)) {
data = btr_copy_externally_stored_field(
&cur_len, data, phrase->zip_size,
dfield_get_len(dfield), phrase->heap);
} else {
cur_len = dfield_get_len(dfield);
}
if (cur_len != UNIV_SQL_NULL && cur_len != 0) {
if (phrase->proximity_pos) {
ut_ad(prev_len + cur_len <= total_len);
memcpy(document_text + prev_len, data, cur_len);
} else {
/* For phrase search */
phrase->found =
fts_query_match_phrase(
phrase,
static_cast<byte*>(data),
cur_len, prev_len,
phrase->heap);
}
/* Document positions are calculated from the beginning
of the first field, need to save the length for each
searched field to adjust the doc position when search
phrases. */
prev_len += cur_len + 1;
}
if (phrase->found) {
break;
}
exp = que_node_get_next(exp);
}
if (phrase->proximity_pos) {
ut_ad(prev_len <= total_len);
phrase->found = fts_proximity_is_word_in_range(
phrase, document_text, total_len);
}
return(phrase->found);
}
#if 0
/********************************************************************
Callback function to check whether a record was found or not. */
static
ibool
fts_query_select(
/*=============*/
void* row, /*!< in: sel_node_t* */
void* user_arg) /*!< in: fts_doc_t* */
{
int i;
que_node_t* exp;
sel_node_t* node = row;
fts_select_t* select = user_arg;
ut_a(select->word_freq);
ut_a(select->word_freq->doc_freqs);
exp = node->select_list;
for (i = 0; exp && !select->found; ++i) {
dfield_t* dfield = que_node_get_val(exp);
void* data = dfield_get_data(dfield);
ulint len = dfield_get_len(dfield);
switch (i) {
case 0: /* DOC_COUNT */
if (len != UNIV_SQL_NULL && len != 0) {
select->word_freq->doc_count +=
mach_read_from_4(data);
}
break;
case 1: /* ILIST */
if (len != UNIV_SQL_NULL && len != 0) {
fts_query_find_doc_id(select, data, len);
}
break;
default:
ut_error;
}
exp = que_node_get_next(exp);
}
return(FALSE);
}
/********************************************************************
Read the rows from the FTS index, that match word and where the
doc id is between first and last doc id.
@return DB_SUCCESS if all go well else error code */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_find_term(
/*================*/
fts_query_t* query, /*!< in: FTS query state */
que_t** graph, /*!< in: prepared statement */
const fts_string_t* word, /*!< in: the word to fetch */
doc_id_t doc_id, /*!< in: doc id to match */
ulint* min_pos,/*!< in/out: pos found must be
greater than this minimum value. */
ibool* found) /*!< out: TRUE if found else FALSE */
{
pars_info_t* info;
dberr_t error;
fts_select_t select;
doc_id_t match_doc_id;
trx_t* trx = query->trx;
char table_name[MAX_FULL_NAME_LEN];
trx->op_info = "fetching FTS index matching nodes";
if (*graph) {
info = (*graph)->info;
} else {
ulint selected;
info = pars_info_create();
selected = fts_select_index(*word->f_str);
query->fts_index_table.suffix = fts_get_suffix(selected);
fts_get_table_name(&query->fts_index_table, table_name);
pars_info_bind_id(info, "index_table_name", table_name);
}
select.found = FALSE;
select.doc_id = doc_id;
select.min_pos = *min_pos;
select.word_freq = fts_query_add_word_freq(query, word->f_str);
pars_info_bind_function(info, "my_func", fts_query_select, &select);
pars_info_bind_varchar_literal(info, "word", word->f_str, word->f_len);
/* Convert to "storage" byte order. */
fts_write_doc_id((byte*) &match_doc_id, doc_id);
fts_bind_doc_id(info, "min_doc_id", &match_doc_id);
fts_bind_doc_id(info, "max_doc_id", &match_doc_id);
if (!*graph) {
*graph = fts_parse_sql(
&query->fts_index_table,
info,
"DECLARE FUNCTION my_func;\n"
"DECLARE CURSOR c IS"
" SELECT doc_count, ilist\n"
" FROM $index_table_name\n"
" WHERE word LIKE :word AND"
" first_doc_id <= :min_doc_id AND"
" last_doc_id >= :max_doc_id\n"
" ORDER BY first_doc_id;\n"
"BEGIN\n"
"\n"
"OPEN c;\n"
"WHILE 1 = 1 LOOP\n"
" FETCH c INTO my_func();\n"
" IF c % NOTFOUND THEN\n"
" EXIT;\n"
" END IF;\n"
"END LOOP;\n"
"CLOSE c;");
}
for (;;) {
error = fts_eval_sql(trx, *graph);
if (error == DB_SUCCESS) {
break; /* Exit the loop. */
} else {
if (error == DB_LOCK_WAIT_TIMEOUT) {
ib::warn() << "lock wait timeout reading FTS"
" index. Retrying!";
trx->error_state = DB_SUCCESS;
} else {
ib::error() << error
<< " while reading FTS index.";
break; /* Exit the loop. */
}
}
}
/* Value to return */
*found = select.found;
if (*found) {
*min_pos = select.min_pos;
}
return(error);
}
/********************************************************************
Callback aggregator for int columns. */
static
ibool
fts_query_sum(
/*==========*/
/*!< out: always returns TRUE */
void* row, /*!< in: sel_node_t* */
void* user_arg) /*!< in: ulint* */
{
que_node_t* exp;
sel_node_t* node = row;
ulint* total = user_arg;
exp = node->select_list;
while (exp) {
dfield_t* dfield = que_node_get_val(exp);
void* data = dfield_get_data(dfield);
ulint len = dfield_get_len(dfield);
if (len != UNIV_SQL_NULL && len != 0) {
*total += mach_read_from_4(data);
}
exp = que_node_get_next(exp);
}
return(TRUE);
}
/********************************************************************
Calculate the total documents that contain a particular word (term).
@return DB_SUCCESS if all go well else error code */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_total_docs_containing_term(
/*=================================*/
fts_query_t* query, /*!< in: FTS query state */
const fts_string_t* word, /*!< in: the word to check */
ulint* total) /*!< out: documents containing word */
{
pars_info_t* info;
dberr_t error;
que_t* graph;
ulint selected;
trx_t* trx = query->trx;
char table_name[MAX_FULL_NAME_LEN]
trx->op_info = "fetching FTS index document count";
*total = 0;
info = pars_info_create();
pars_info_bind_function(info, "my_func", fts_query_sum, total);
pars_info_bind_varchar_literal(info, "word", word->f_str, word->f_len);
selected = fts_select_index(*word->f_str);
query->fts_index_table.suffix = fts_get_suffix(selected);
fts_get_table_name(&query->fts_index_table, table_name);
pars_info_bind_id(info, "index_table_name", table_name);
graph = fts_parse_sql(
&query->fts_index_table,
info,
"DECLARE FUNCTION my_func;\n"
"DECLARE CURSOR c IS"
" SELECT doc_count\n"
" FROM $index_table_name\n"
" WHERE word = :word"
" ORDER BY first_doc_id;\n"
"BEGIN\n"
"\n"
"OPEN c;\n"
"WHILE 1 = 1 LOOP\n"
" FETCH c INTO my_func();\n"
" IF c % NOTFOUND THEN\n"
" EXIT;\n"
" END IF;\n"
"END LOOP;\n"
"CLOSE c;");
for (;;) {
error = fts_eval_sql(trx, graph);
if (error == DB_SUCCESS) {
break; /* Exit the loop. */
} else {
if (error == DB_LOCK_WAIT_TIMEOUT) {
ib::warn() << "lock wait timeout reading FTS"
" index. Retrying!";
trx->error_state = DB_SUCCESS;
} else {
ib::error() << error
<< " while reading FTS index.";
break; /* Exit the loop. */
}
}
}
que_graph_free(graph);
return(error);
}
/********************************************************************
Get the total number of words in a documents.
@return DB_SUCCESS if all go well else error code */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_terms_in_document(
/*========================*/
fts_query_t* query, /*!< in: FTS query state */
doc_id_t doc_id, /*!< in: the word to check */
ulint* total) /*!< out: total words in document */
{
pars_info_t* info;
dberr_t error;
que_t* graph;
doc_id_t read_doc_id;
trx_t* trx = query->trx;
char table_name[MAX_FULL_NAME_LEN];
trx->op_info = "fetching FTS document term count";
*total = 0;
info = pars_info_create();
pars_info_bind_function(info, "my_func", fts_query_sum, total);
/* Convert to "storage" byte order. */
fts_write_doc_id((byte*) &read_doc_id, doc_id);
fts_bind_doc_id(info, "doc_id", &read_doc_id);
query->fts_index_table.suffix = "DOC_ID";
fts_get_table_name(&query->fts_index_table, table_name);
pars_info_bind_id(info, "index_table_name", table_name);
graph = fts_parse_sql(
&query->fts_index_table,
info,
"DECLARE FUNCTION my_func;\n"
"DECLARE CURSOR c IS"
" SELECT count\n"
" FROM $index_table_name\n"
" WHERE doc_id = :doc_id"
" BEGIN\n"
"\n"
"OPEN c;\n"
"WHILE 1 = 1 LOOP\n"
" FETCH c INTO my_func();\n"
" IF c % NOTFOUND THEN\n"
" EXIT;\n"
" END IF;\n"
"END LOOP;\n"
"CLOSE c;");
for (;;) {
error = fts_eval_sql(trx, graph);
if (error == DB_SUCCESS) {
break; /* Exit the loop. */
} else {
if (error == DB_LOCK_WAIT_TIMEOUT) {
ib::warn() << "lock wait timeout reading FTS"
" doc id table. Retrying!";
trx->error_state = DB_SUCCESS;
} else {
ib::error() << error << " while reading FTS"
" doc id table.";
break; /* Exit the loop. */
}
}
}
que_graph_free(graph);
return(error);
}
#endif
/*****************************************************************//**
Retrieve the document and match the phrase tokens.
@return DB_SUCCESS or error code */
MY_ATTRIBUTE((nonnull(1,2,3,6), warn_unused_result))
static
dberr_t
fts_query_match_document(
/*=====================*/
ib_vector_t* tokens, /*!< in: phrase tokens */
fts_get_doc_t* get_doc, /*!< in: table and prepared statements */
fts_match_t* match, /*!< in: doc id and positions */
ulint distance, /*!< in: proximity distance */
st_mysql_ftparser* parser, /*!< in: fts plugin parser */
ibool* found) /*!< out: TRUE if phrase found */
{
dberr_t error;
fts_phrase_t phrase(get_doc->index_cache->index->table);
phrase.match = match; /* Positions to match */
phrase.tokens = tokens; /* Tokens to match */
phrase.distance = distance;
phrase.charset = get_doc->index_cache->charset;
phrase.heap = mem_heap_create(512);
phrase.parser = parser;
*found = phrase.found = FALSE;
error = fts_doc_fetch_by_doc_id(
get_doc, match->doc_id, NULL, FTS_FETCH_DOC_BY_ID_EQUAL,
fts_query_fetch_document, &phrase);
if (UNIV_UNLIKELY(error != DB_SUCCESS)) {
ib::error() << "(" << error << ") matching document.";
} else {
*found = phrase.found;
}
mem_heap_free(phrase.heap);
return(error);
}
/*****************************************************************//**
This function fetches the original documents and count the
words in between matching words to see that is in specified distance
@return DB_SUCCESS if all OK */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
bool
fts_query_is_in_proximity_range(
/*============================*/
const fts_query_t* query, /*!< in: query instance */
fts_match_t** match, /*!< in: query instance */
fts_proximity_t* qualified_pos) /*!< in: position info for
qualified ranges */
{
fts_get_doc_t get_doc;
fts_cache_t* cache = query->index->table->fts->cache;
dberr_t err;
memset(&get_doc, 0x0, sizeof(get_doc));
mysql_mutex_lock(&cache->lock);
get_doc.index_cache = fts_find_index_cache(cache, query->index);
mysql_mutex_unlock(&cache->lock);
ut_a(get_doc.index_cache != NULL);
fts_phrase_t phrase(get_doc.index_cache->index->table);
phrase.distance = query->distance;
phrase.charset = get_doc.index_cache->charset;
phrase.heap = mem_heap_create(512);
phrase.proximity_pos = qualified_pos;
phrase.found = FALSE;
err = fts_doc_fetch_by_doc_id(
&get_doc, match[0]->doc_id, NULL, FTS_FETCH_DOC_BY_ID_EQUAL,
fts_query_fetch_document, &phrase);
if (UNIV_UNLIKELY(err != DB_SUCCESS)) {
ib::error() << "(" << err << ") in verification"
" phase of proximity search";
}
/* Free the prepared statement. */
if (get_doc.get_document_graph) {
que_graph_free(get_doc.get_document_graph);
get_doc.get_document_graph = NULL;
}
mem_heap_free(phrase.heap);
return(err == DB_SUCCESS && phrase.found);
}
/*****************************************************************//**
Iterate over the matched document ids and search the for the
actual phrase in the text.
@return DB_SUCCESS if all OK */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_search_phrase(
/*====================*/
fts_query_t* query, /*!< in: query instance */
ib_vector_t* orig_tokens, /*!< in: tokens to search,
with any stopwords in the
original phrase */
ib_vector_t* tokens) /*!< in: tokens that does
not include stopwords and
can be used to calculate
ranking */
{
ulint i;
fts_get_doc_t get_doc;
ulint n_matched;
fts_cache_t* cache = query->index->table->fts->cache;
n_matched = ib_vector_size(query->matched);
/* Setup the doc retrieval infrastructure. */
memset(&get_doc, 0x0, sizeof(get_doc));
mysql_mutex_lock(&cache->lock);
get_doc.index_cache = fts_find_index_cache(cache, query->index);
/* Must find the index cache */
ut_a(get_doc.index_cache != NULL);
mysql_mutex_unlock(&cache->lock);
#ifdef FTS_INTERNAL_DIAG_PRINT
ib::info() << "Start phrase search";
#endif
/* Read the document from disk and do the actual
match, matching documents will be added to the current
doc id set. */
for (i = 0; i < n_matched && query->error == DB_SUCCESS; ++i) {
fts_match_t* match;
ibool found = FALSE;
match = static_cast<fts_match_t*>(
ib_vector_get(query->matched, i));
/* Skip the document ids that were filtered out by
an earlier pass. */
if (match->doc_id != 0) {
query->error = fts_query_match_document(
orig_tokens, &get_doc, match,
query->distance, query->parser, &found);
if (query->error == DB_SUCCESS && found) {
ulint z;
query->error = fts_query_process_doc_id(query,
match->doc_id, 0);
if (query->error != DB_SUCCESS) {
goto func_exit;
}
for (z = 0; z < ib_vector_size(tokens); z++) {
fts_string_t* token;
token = static_cast<fts_string_t*>(
ib_vector_get(tokens, z));
fts_query_add_word_to_document(
query, match->doc_id, token);
}
}
}
}
func_exit:
/* Free the prepared statement. */
if (get_doc.get_document_graph) {
que_graph_free(get_doc.get_document_graph);
get_doc.get_document_graph = NULL;
}
return(query->error);
}
/** Split the phrase into tokens
@param[in,out] query query instance
@param[in] node query node to search
@param[in,out] tokens token vector
@param[in,out] orig_tokens original node tokens include stopword
@param[in,out] heap mem heap */
static
void
fts_query_phrase_split(
fts_query_t* query,
const fts_ast_node_t* node,
ib_vector_t* tokens,
ib_vector_t* orig_tokens,
mem_heap_t* heap)
{
fts_string_t phrase;
ulint len = 0;
ulint cur_pos = 0;
fts_ast_node_t* term_node = NULL;
if (node->type == FTS_AST_TEXT) {
phrase.f_str = node->text.ptr->str;
phrase.f_len = node->text.ptr->len;
len = phrase.f_len;
} else {
ut_ad(node->type == FTS_AST_PARSER_PHRASE_LIST);
phrase.f_str = NULL;
phrase.f_len = 0;
term_node = node->list.head;
}
while (true) {
fts_cache_t* cache = query->index->table->fts->cache;
ulint cur_len;
fts_string_t result_str;
if (node->type == FTS_AST_TEXT) {
if (cur_pos >= len) {
break;
}
cur_len = innobase_mysql_fts_get_token(
query->fts_index_table.charset,
reinterpret_cast<const byte*>(phrase.f_str)
+ cur_pos,
reinterpret_cast<const byte*>(phrase.f_str)
+ len,
&result_str);
if (cur_len == 0) {
break;
}
cur_pos += cur_len;
} else {
ut_ad(node->type == FTS_AST_PARSER_PHRASE_LIST);
/* Term node in parser phrase list */
if (term_node == NULL) {
break;
}
ut_a(term_node->type == FTS_AST_TERM);
result_str.f_str = term_node->term.ptr->str;
result_str.f_len = term_node->term.ptr->len;
result_str.f_n_char = fts_get_token_size(
query->fts_index_table.charset,
reinterpret_cast<char*>(result_str.f_str),
result_str.f_len);
term_node = term_node->next;
}
if (result_str.f_n_char == 0) {
continue;
}
fts_string_t* token = static_cast<fts_string_t*>(
ib_vector_push(tokens, NULL));
fts_string_dup(token, &result_str, heap);
if (fts_check_token(
&result_str,
cache->stopword_info.cached_stopword,
query->fts_index_table.charset)) {
/* Add the word to the RB tree so that we can
calculate its frequency within a document. */
fts_query_add_word_freq(query, token);
} else {
ib_vector_pop(tokens);
}
/* we will start to store all words including stopwords
in the "orig_tokens" vector, but skip any leading words
that are stopwords */
if (!ib_vector_is_empty(tokens)) {
fts_string_t* orig_token = static_cast<fts_string_t*>(
ib_vector_push(orig_tokens, NULL));
orig_token->f_str = token->f_str;
orig_token->f_len = token->f_len;
}
}
}
/*****************************************************************//**
Text/Phrase search.
@return DB_SUCCESS or error code */
static MY_ATTRIBUTE((warn_unused_result))
dberr_t
fts_query_phrase_search(
/*====================*/
fts_query_t* query, /*!< in: query instance */
const fts_ast_node_t* node) /*!< in: node to search */
{
ib_vector_t* tokens;
ib_vector_t* orig_tokens;
mem_heap_t* heap = mem_heap_create(sizeof(fts_string_t));
ib_alloc_t* heap_alloc;
ulint num_token;
heap_alloc = ib_heap_allocator_create(heap);
tokens = ib_vector_create(heap_alloc, sizeof(fts_string_t), 4);
orig_tokens = ib_vector_create(heap_alloc, sizeof(fts_string_t), 4);
if (query->distance != ULINT_UNDEFINED && query->distance > 0) {
query->flags = FTS_PROXIMITY;
} else {
query->flags = FTS_PHRASE;
}
/* Split the phrase into tokens. */
fts_query_phrase_split(query, node, tokens, orig_tokens, heap);
num_token = ib_vector_size(tokens);
if (num_token > MAX_PROXIMITY_ITEM) {
query->error = DB_FTS_TOO_MANY_WORDS_IN_PHRASE;
goto func_exit;
}
ut_ad(ib_vector_size(orig_tokens) >= num_token);
/* Ignore empty strings. */
if (num_token > 0) {
fts_string_t* token = NULL;
fts_fetch_t fetch;
trx_t* trx = query->trx;
fts_ast_oper_t oper = query->oper;
que_t* graph = NULL;
ulint i;
dberr_t error;
/* Create the vector for storing matching document ids
and the positions of the first token of the phrase. */
if (!query->matched) {
ib_alloc_t* heap_alloc;
heap_alloc = ib_heap_allocator_create(heap);
if (!(query->flags & FTS_PROXIMITY)
&& !(query->flags & FTS_PHRASE)) {
query->matched = ib_vector_create(
heap_alloc, sizeof(fts_match_t),
64);
} else {
ut_a(num_token <= MAX_PROXIMITY_ITEM);
query->match_array =
(ib_vector_t**) mem_heap_alloc(
heap,
num_token *
sizeof(query->matched));
for (i = 0; i < num_token; i++) {
query->match_array[i] =
ib_vector_create(
heap_alloc, sizeof(fts_match_t),
64);
}
query->matched = query->match_array[0];
}
}
/* Setup the callback args for filtering and consolidating
the ilist. */
fetch.read_arg = query;
fetch.read_record = fts_query_index_fetch_nodes;
for (i = 0; i < num_token; i++) {
/* Search for the first word from the phrase. */
token = static_cast<fts_string_t*>(
ib_vector_get(tokens, i));
if (query->flags & FTS_PROXIMITY
|| query->flags & FTS_PHRASE) {
query->matched = query->match_array[i];
}
error = fts_index_fetch_nodes(
trx, &graph, &query->fts_index_table,
token, &fetch);
/* DB_FTS_EXCEED_RESULT_CACHE_LIMIT passed by 'query->error' */
ut_ad(!(query->error != DB_SUCCESS && error != DB_SUCCESS));
if (error != DB_SUCCESS) {
query->error = error;
}
que_graph_free(graph);
graph = NULL;
fts_query_cache(query, token);
if (!(query->flags & FTS_PHRASE)
&& !(query->flags & FTS_PROXIMITY)) {
break;
}
/* If any of the token can't be found,
no need to continue match */
if (ib_vector_is_empty(query->match_array[i])
|| query->error != DB_SUCCESS) {
goto func_exit;
}
}
/* Just a single word, no need to fetch the original
documents to do phrase matching */
if (ib_vector_size(orig_tokens) == 1
&& !ib_vector_is_empty(query->match_array[0])) {
fts_match_t* match;
ulint n_matched;
n_matched = ib_vector_size(query->match_array[0]);
for (i = 0; i < n_matched; i++) {
match = static_cast<fts_match_t*>(
ib_vector_get(
query->match_array[0], i));
query->error = fts_query_process_doc_id(
query, match->doc_id, 0);
if (query->error != DB_SUCCESS) {
goto func_exit;
}
fts_query_add_word_to_document(
query, match->doc_id, token);
}
query->oper = oper;
goto func_exit;
}
/* If we are doing proximity search, verify the distance
between all words, and check they are in specified distance. */
if (query->flags & FTS_PROXIMITY) {
fts_phrase_or_proximity_search(query, tokens);
} else {
ibool matched;
/* Phrase Search case:
We filter out the doc ids that don't contain
all the tokens in the phrase. It's cheaper to
search the ilist than bringing the documents in
and then doing a search through the text. Isolated
testing shows this also helps in mitigating disruption
of the buffer cache. */
matched = fts_phrase_or_proximity_search(query, tokens);
query->matched = query->match_array[0];
/* Read the actual text in and search for the phrase. */
if (matched) {
ut_ad(query->error == DB_SUCCESS);
query->error = fts_query_search_phrase(
query, orig_tokens, tokens);
}
}
/* Restore original operation. */
query->oper = oper;
if (query->error != DB_SUCCESS) {
goto func_exit;
}
}
func_exit:
mem_heap_free(heap);
/* Don't need it anymore. */
query->matched = NULL;
return(query->error);
}
/*****************************************************************//**
Find the word and evaluate.
@return DB_SUCCESS if all go well */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_query_execute(
/*==============*/
fts_query_t* query, /*!< in: query instance */
fts_string_t* token) /*!< in: token to search */
{
switch (query->oper) {
case FTS_NONE:
case FTS_NEGATE:
case FTS_INCR_RATING:
case FTS_DECR_RATING:
query->error = fts_query_union(query, token);
break;
case FTS_EXIST:
query->error = fts_query_intersect(query, token);
break;
case FTS_IGNORE:
query->error = fts_query_difference(query, token);
break;
default:
ut_error;
}
return(query->error);
}
/*****************************************************************//**
Create a wildcard string. It's the responsibility of the caller to
free the byte* pointer. It's allocated using ut_malloc_nokey().
@return ptr to allocated memory */
static
byte*
fts_query_get_token(
/*================*/
fts_ast_node_t* node, /*!< in: the current sub tree */
fts_string_t* token) /*!< in: token to create */
{
ulint str_len;
byte* new_ptr = NULL;
str_len = node->term.ptr->len;
ut_a(node->type == FTS_AST_TERM);
token->f_len = str_len;
token->f_str = node->term.ptr->str;
if (node->term.wildcard) {
token->f_str = static_cast<byte*>(ut_malloc_nokey(str_len + 2));
token->f_len = str_len + 1;
memcpy(token->f_str, node->term.ptr->str, str_len);
token->f_str[str_len] = '%';
token->f_str[token->f_len] = 0;
new_ptr = token->f_str;
}
return(new_ptr);
}
static dberr_t fts_ast_visit_sub_exp(fts_ast_node_t*, fts_ast_callback, void*);
/*****************************************************************//**
Visit every node of the AST. */
static
dberr_t
fts_query_visitor(
/*==============*/
fts_ast_oper_t oper, /*!< in: current operator */
fts_ast_node_t* node, /*!< in: The root of the current subtree*/
void* arg) /*!< in: callback arg*/
{
byte* ptr;
fts_string_t token;
fts_query_t* query = static_cast<fts_query_t*>(arg);
ut_a(node);
DBUG_ENTER("fts_query_visitor");
DBUG_PRINT("fts", ("nodetype: %s", fts_ast_node_type_get(node->type)));
token.f_n_char = 0;
query->oper = oper;
query->cur_node = node;
switch (node->type) {
case FTS_AST_TEXT:
case FTS_AST_PARSER_PHRASE_LIST:
if (query->oper == FTS_EXIST) {
ut_ad(query->intersection == NULL);
static_assert(!offsetof(fts_ranking_t, doc_id), "ABI");
query->intersection = rbt_create(
sizeof(fts_ranking_t), fts_doc_id_cmp);
query->total_size += SIZEOF_RBT_CREATE;
}
/* Set the current proximity distance. */
query->distance = node->text.distance;
/* Force collection of doc ids and the positions. */
query->collect_positions = TRUE;
query->error = fts_query_phrase_search(query, node);
query->collect_positions = FALSE;
if (query->oper == FTS_EXIST) {
fts_query_free_doc_ids(query, query->doc_ids);
query->doc_ids = query->intersection;
query->intersection = NULL;
}
break;
case FTS_AST_TERM:
token.f_str = node->term.ptr->str;
token.f_len = node->term.ptr->len;
/* Collect wildcard words for QUERY EXPANSION. */
if (node->term.wildcard && query->wildcard_words != NULL) {
ib_rbt_bound_t parent;
if (rbt_search(query->wildcard_words, &parent, &token)
!= 0) {
fts_string_t word;
fts_string_dup(&word, &token, query->heap);
rbt_add_node(query->wildcard_words, &parent,
&word);
}
}
/* Add the word to our RB tree that will be used to
calculate this terms per document frequency. */
fts_query_add_word_freq(query, &token);
ptr = fts_query_get_token(node, &token);
query->error = fts_query_execute(query, &token);
if (ptr) {
ut_free(ptr);
}
break;
case FTS_AST_SUBEXP_LIST:
query->error = fts_ast_visit_sub_exp(node, fts_query_visitor, arg);
break;
default:
ut_error;
}
if (query->oper == FTS_EXIST) {
query->multi_exist = true;
}
DBUG_RETURN(query->error);
}
/** Process (nested) sub-expression, create a new result set to store the
sub-expression result by processing nodes under current sub-expression
list. Merge the sub-expression result with that of parent expression list.
@param[in,out] node current root node
@param[in,out] visitor callback function
@param[in,out] arg argument for callback
@return DB_SUCCESS if all go well */
static
dberr_t
fts_ast_visit_sub_exp(
fts_ast_node_t* node,
fts_ast_callback visitor,
void* arg)
{
fts_ast_oper_t cur_oper;
fts_query_t* query = static_cast<fts_query_t*>(arg);
ib_rbt_t* parent_doc_ids;
ib_rbt_t* subexpr_doc_ids;
dberr_t error = DB_SUCCESS;
bool will_be_ignored = false;
bool multi_exist;
DBUG_ENTER("fts_ast_visit_sub_exp");
ut_a(node->type == FTS_AST_SUBEXP_LIST);
/* To avoid stack overflow, we limit the mutual recursion
depth between fts_ast_visit(), fts_query_visitor() and
fts_ast_visit_sub_exp(). */
if (query->visiting_sub_exp++ > 31) {
query->error = DB_OUT_OF_MEMORY;
DBUG_RETURN(query->error);
}
cur_oper = query->oper;
/* Save current result set */
parent_doc_ids = query->doc_ids;
/* Create new result set to store the sub-expression result. We
will merge this result set with the parent after processing. */
static_assert(!offsetof(fts_ranking_t, doc_id), "ABI");
query->doc_ids = rbt_create(sizeof(fts_ranking_t), fts_doc_id_cmp);
query->total_size += SIZEOF_RBT_CREATE;
multi_exist = query->multi_exist;
query->multi_exist = false;
/* Process nodes in current sub-expression and store its
result set in query->doc_ids we created above. */
error = fts_ast_visit(FTS_NONE, node, visitor,
arg, &will_be_ignored);
/* Reinstate parent node state */
query->multi_exist = multi_exist;
query->oper = cur_oper;
query->visiting_sub_exp--;
/* Merge the sub-expression result with the parent result set. */
subexpr_doc_ids = query->doc_ids;
query->doc_ids = parent_doc_ids;
if (error == DB_SUCCESS) {
error = fts_merge_doc_ids(query, subexpr_doc_ids);
}
/* Free current result set. Result already merged into parent. */
fts_query_free_doc_ids(query, subexpr_doc_ids);
DBUG_RETURN(error);
}
#if 0
/*****************************************************************//***
Check if the doc id exists in the ilist.
@return TRUE if doc id found */
static
ulint
fts_query_find_doc_id(
/*==================*/
fts_select_t* select, /*!< in/out: contains the doc id to
find, we update the word freq if
document found */
void* data, /*!< in: doc id ilist */
ulint len) /*!< in: doc id ilist size */
{
byte* ptr = data;
doc_id_t doc_id = 0;
ulint decoded = 0;
/* Decode the ilist and search for selected doc_id. We also
calculate the frequency of the word in the document if found. */
while (decoded < len && !select->found) {
ulint freq = 0;
ulint min_pos = 0;
ulint last_pos = 0;
ulint pos = fts_decode_vlc(&ptr);
/* Add the delta. */
doc_id += pos;
while (*ptr) {
++freq;
last_pos += fts_decode_vlc(&ptr);
/* Only if min_pos is not set and the current
term exists in a position greater than the
min_pos of the previous term. */
if (min_pos == 0 && last_pos > select->min_pos) {
min_pos = last_pos;
}
}
/* Skip the end of word position marker. */
++ptr;
/* Bytes decoded so far. */
decoded = ptr - (byte*) data;
/* A word may exist in the document but we only consider a
match if it exists in a position that is greater than the
position of the previous term. */
if (doc_id == select->doc_id && min_pos > 0) {
fts_doc_freq_t* doc_freq;
/* Add the doc id to the doc freq rb tree, if
the doc id doesn't exist it will be created. */
doc_freq = fts_query_add_doc_freq(
select->word_freq->doc_freqs, doc_id);
/* Avoid duplicating the frequency tally */
if (doc_freq->freq == 0) {
doc_freq->freq = freq;
}
select->found = TRUE;
select->min_pos = min_pos;
}
}
return(select->found);
}
#endif
/*****************************************************************//**
Read and filter nodes.
@return DB_SUCCESS if all go well,
or return DB_FTS_EXCEED_RESULT_CACHE_LIMIT */
static
dberr_t
fts_query_filter_doc_ids(
/*=====================*/
fts_query_t* query, /*!< in: query instance */
const fts_string_t* word, /*!< in: the current word */
fts_word_freq_t* word_freq, /*!< in/out: word frequency */
const fts_node_t* node, /*!< in: current FTS node */
void* data, /*!< in: doc id ilist */
ulint len, /*!< in: doc id ilist size */
ibool calc_doc_count) /*!< in: whether to remember doc count */
{
const byte* ptr = static_cast<byte*>(data);
doc_id_t doc_id = 0;
ulint decoded = 0;
ib_rbt_t* doc_freqs = word_freq->doc_freqs;
/* Decode the ilist and add the doc ids to the query doc_id set. */
while (decoded < len) {
ulint freq = 0;
fts_doc_freq_t* doc_freq;
fts_match_t* match = NULL;
doc_id_t last_pos = 0;
doc_id_t pos = fts_decode_vlc(&ptr);
/* Some sanity checks. */
if (doc_id == 0) {
ut_a(pos == node->first_doc_id);
}
/* Add the delta. */
doc_id += pos;
if (calc_doc_count) {
word_freq->doc_count++;
}
/* We simply collect the matching instances here. */
if (query->collect_positions) {
ib_alloc_t* heap_alloc;
/* Create a new fts_match_t instance. */
match = static_cast<fts_match_t*>(
ib_vector_push(query->matched, NULL));
match->start = 0;
match->doc_id = doc_id;
heap_alloc = ib_vector_allocator(query->matched);
/* Allocate from the same heap as the
parent container. */
match->positions = ib_vector_create(
heap_alloc, sizeof(ulint), 64);
query->total_size += sizeof(fts_match_t)
+ sizeof(ib_vector_t)
+ sizeof(ulint) * 64;
}
/* Unpack the positions within the document. */
while (*ptr) {
last_pos += fts_decode_vlc(&ptr);
/* Collect the matching word positions, for phrase
matching later. */
if (query->collect_positions) {
ib_vector_push(match->positions, &last_pos);
}
++freq;
}
/* End of list marker. */
last_pos = (ulint) -1;
if (query->collect_positions) {
ut_a(match != NULL);
ib_vector_push(match->positions, &last_pos);
}
/* Add the doc id to the doc freq rb tree, if the doc id
doesn't exist it will be created. */
doc_freq = fts_query_add_doc_freq(query, doc_freqs, doc_id);
/* Avoid duplicating frequency tally. */
if (doc_freq->freq == 0) {
doc_freq->freq = freq;
}
/* Skip the end of word position marker. */
++ptr;
/* Bytes decoded so far */
decoded = ulint(ptr - (byte*) data);
/* We simply collect the matching documents and the
positions here and match later. */
if (!query->collect_positions) {
/* We ignore error here and will check it later */
fts_query_process_doc_id(query, doc_id, 0);
/* Add the word to the document's matched RB tree. */
fts_query_add_word_to_document(query, doc_id, word);
}
}
/* Some sanity checks. */
ut_a(doc_id == node->last_doc_id);
if (query->total_size > fts_result_cache_limit) {
return(DB_FTS_EXCEED_RESULT_CACHE_LIMIT);
} else {
return(DB_SUCCESS);
}
}
/*****************************************************************//**
Read the FTS INDEX row.
@return DB_SUCCESS if all go well. */
static
dberr_t
fts_query_read_node(
/*================*/
fts_query_t* query, /*!< in: query instance */
const fts_string_t* word, /*!< in: current word */
que_node_t* exp) /*!< in: query graph node */
{
int i;
int ret;
fts_node_t node;
ib_rbt_bound_t parent;
fts_word_freq_t* word_freq;
ibool skip = FALSE;
fts_string_t term;
byte buf[FTS_MAX_WORD_LEN + 1];
dberr_t error = DB_SUCCESS;
ut_a(query->cur_node->type == FTS_AST_TERM
|| query->cur_node->type == FTS_AST_TEXT
|| query->cur_node->type == FTS_AST_PARSER_PHRASE_LIST);
memset(&node, 0, sizeof(node));
term.f_str = buf;
/* Need to consider the wildcard search case, the word frequency
is created on the search string not the actual word. So we need
to assign the frequency on search string behalf. */
if (query->cur_node->type == FTS_AST_TERM
&& query->cur_node->term.wildcard) {
term.f_len = query->cur_node->term.ptr->len;
ut_ad(FTS_MAX_WORD_LEN >= term.f_len);
memcpy(term.f_str, query->cur_node->term.ptr->str, term.f_len);
} else {
term.f_len = word->f_len;
ut_ad(FTS_MAX_WORD_LEN >= word->f_len);
memcpy(term.f_str, word->f_str, word->f_len);
}
/* Lookup the word in our rb tree, it must exist. */
ret = rbt_search(query->word_freqs, &parent, &term);
ut_a(ret == 0);
word_freq = rbt_value(fts_word_freq_t, parent.last);
/* Start from 1 since the first column has been read by the caller.
Also, we rely on the order of the columns projected, to filter
out ilists that are out of range and we always want to read
the doc_count irrespective of the suitability of the row. */
for (i = 1; exp && !skip; exp = que_node_get_next(exp), ++i) {
dfield_t* dfield = que_node_get_val(exp);
byte* data = static_cast<byte*>(
dfield_get_data(dfield));
ulint len = dfield_get_len(dfield);
ut_a(len != UNIV_SQL_NULL);
/* Note: The column numbers below must match the SELECT. */
switch (i) {
case 1: /* DOC_COUNT */
word_freq->doc_count += mach_read_from_4(data);
break;
case 2: /* FIRST_DOC_ID */
node.first_doc_id = fts_read_doc_id(data);
/* Skip nodes whose doc ids are out range. */
if (query->oper == FTS_EXIST
&& query->upper_doc_id > 0
&& node.first_doc_id > query->upper_doc_id) {
skip = TRUE;
}
break;
case 3: /* LAST_DOC_ID */
node.last_doc_id = fts_read_doc_id(data);
/* Skip nodes whose doc ids are out range. */
if (query->oper == FTS_EXIST
&& query->lower_doc_id > 0
&& node.last_doc_id < query->lower_doc_id) {
skip = TRUE;
}
break;
case 4: /* ILIST */
error = fts_query_filter_doc_ids(
query, &word_freq->word, word_freq,
&node, data, len, FALSE);
break;
default:
ut_error;
}
}
if (!skip) {
/* Make sure all columns were read. */
ut_a(i == 5);
}
return error;
}
/*****************************************************************//**
Callback function to fetch the rows in an FTS INDEX record.
@return always returns TRUE */
static
ibool
fts_query_index_fetch_nodes(
/*========================*/
void* row, /*!< in: sel_node_t* */
void* user_arg) /*!< in: pointer to fts_fetch_t */
{
fts_string_t key;
sel_node_t* sel_node = static_cast<sel_node_t*>(row);
fts_fetch_t* fetch = static_cast<fts_fetch_t*>(user_arg);
fts_query_t* query = static_cast<fts_query_t*>(fetch->read_arg);
que_node_t* exp = sel_node->select_list;
dfield_t* dfield = que_node_get_val(exp);
void* data = dfield_get_data(dfield);
ulint dfield_len = dfield_get_len(dfield);
key.f_str = static_cast<byte*>(data);
key.f_len = dfield_len;
ut_a(dfield_len <= FTS_MAX_WORD_LEN);
/* Note: we pass error out by 'query->error' */
query->error = fts_query_read_node(query, &key, que_node_get_next(exp));
if (query->error != DB_SUCCESS) {
ut_ad(query->error == DB_FTS_EXCEED_RESULT_CACHE_LIMIT);
return(FALSE);
} else {
return(TRUE);
}
}
/*****************************************************************//**
Calculate the inverse document frequency (IDF) for all the terms. */
static
void
fts_query_calculate_idf(
/*====================*/
fts_query_t* query) /*!< in: Query state */
{
const ib_rbt_node_t* node;
ib_uint64_t total_docs = query->total_docs;
/* We need to free any instances of fts_doc_freq_t that we
may have allocated. */
for (node = rbt_first(query->word_freqs);
node;
node = rbt_next(query->word_freqs, node)) {
fts_word_freq_t* word_freq;
word_freq = rbt_value(fts_word_freq_t, node);
if (word_freq->doc_count > 0) {
if (total_docs == word_freq->doc_count) {
/* QP assume ranking > 0 if we find
a match. Since Log10(1) = 0, we cannot
make IDF a zero value if do find a
word in all documents. So let's make
it an arbitrary very small number */
word_freq->idf = log10(1.0001);
} else {
word_freq->idf = log10(
static_cast<double>(total_docs)
/ static_cast<double>(
word_freq->doc_count));
}
}
}
}
/*****************************************************************//**
Calculate the ranking of the document. */
static
void
fts_query_calculate_ranking(
/*========================*/
const fts_query_t* query, /*!< in: query state */
fts_ranking_t* ranking) /*!< in: Document to rank */
{
ulint pos = 0;
fts_string_t word;
/* At this stage, ranking->rank should not exceed the 1.0
bound */
ut_ad(ranking->rank <= 1.0 && ranking->rank >= -1.0);
ut_ad(rbt_size(query->word_map) == query->word_vector->size());
while (fts_ranking_words_get_next(query, ranking, &pos, &word)) {
int ret;
ib_rbt_bound_t parent;
double weight;
fts_doc_freq_t* doc_freq;
fts_word_freq_t* word_freq;
ret = rbt_search(query->word_freqs, &parent, &word);
/* It must exist. */
ut_a(ret == 0);
word_freq = rbt_value(fts_word_freq_t, parent.last);
ret = rbt_search(
word_freq->doc_freqs, &parent, &ranking->doc_id);
/* It must exist. */
ut_a(ret == 0);
doc_freq = rbt_value(fts_doc_freq_t, parent.last);
weight = (double) doc_freq->freq * word_freq->idf;
ranking->rank += (fts_rank_t) (weight * word_freq->idf);
}
}
/*****************************************************************//**
Add ranking to the result set. */
static
void
fts_query_add_ranking(
/*==================*/
fts_query_t* query, /*!< in: query state */
ib_rbt_t* ranking_tree, /*!< in: ranking tree */
const fts_ranking_t* new_ranking) /*!< in: ranking of a document */
{
ib_rbt_bound_t parent;
/* Lookup the ranking in our rb tree and add if it doesn't exist. */
if (rbt_search(ranking_tree, &parent, new_ranking) == 0) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, parent.last);
ranking->rank += new_ranking->rank;
ut_a(ranking->words == NULL);
} else {
rbt_add_node(ranking_tree, &parent, new_ranking);
query->total_size += SIZEOF_RBT_NODE_ADD
+ sizeof(fts_ranking_t);
}
}
/*****************************************************************//**
Retrieve the FTS Relevance Ranking result for doc with doc_id
@return the relevance ranking value, 0 if no ranking value
present. */
float
fts_retrieve_ranking(
/*=================*/
fts_result_t* result, /*!< in: FTS result structure */
doc_id_t doc_id) /*!< in: doc_id of the item to retrieve */
{
ib_rbt_bound_t parent;
fts_ranking_t new_ranking;
DBUG_ENTER("fts_retrieve_ranking");
if (!result || !result->rankings_by_id) {
DBUG_RETURN(0);
}
new_ranking.doc_id = doc_id;
/* Lookup the ranking in our rb tree */
if (rbt_search(result->rankings_by_id, &parent, &new_ranking) == 0) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, parent.last);
DBUG_RETURN(ranking->rank);
}
DBUG_RETURN(0);
}
/*****************************************************************//**
Create the result and copy the data to it. */
static
fts_result_t*
fts_query_prepare_result(
/*=====================*/
fts_query_t* query, /*!< in: Query state */
fts_result_t* result) /*!< in: result this can contain
data from a previous search on
another FTS index */
{
const ib_rbt_node_t* node;
bool result_is_null = false;
DBUG_ENTER("fts_query_prepare_result");
if (result == NULL) {
result = static_cast<fts_result_t*>(
ut_zalloc_nokey(sizeof(*result)));
static_assert(!offsetof(fts_ranking_t, doc_id), "ABI");
result->rankings_by_id = rbt_create(
sizeof(fts_ranking_t), fts_doc_id_cmp);
query->total_size += sizeof(fts_result_t) + SIZEOF_RBT_CREATE;
result_is_null = true;
}
if (query->flags == FTS_OPT_RANKING) {
fts_word_freq_t* word_freq;
ulint size = ib_vector_size(query->deleted->doc_ids);
doc_id_t* updates =
(doc_id_t*) query->deleted->doc_ids->data;
node = rbt_first(query->word_freqs);
ut_ad(node);
word_freq = rbt_value(fts_word_freq_t, node);
for (node = rbt_first(word_freq->doc_freqs);
node;
node = rbt_next(word_freq->doc_freqs, node)) {
fts_doc_freq_t* doc_freq;
fts_ranking_t ranking;
doc_freq = rbt_value(fts_doc_freq_t, node);
/* Don't put deleted docs into result */
if (fts_bsearch(updates, 0, static_cast<int>(size),
doc_freq->doc_id) >= 0) {
/* one less matching doc count */
--word_freq->doc_count;
continue;
}
ranking.doc_id = doc_freq->doc_id;
ranking.rank = static_cast<fts_rank_t>(doc_freq->freq);
ranking.words = NULL;
fts_query_add_ranking(query, result->rankings_by_id,
&ranking);
if (query->total_size > fts_result_cache_limit) {
query->error = DB_FTS_EXCEED_RESULT_CACHE_LIMIT;
fts_query_free_result(result);
DBUG_RETURN(NULL);
}
}
/* Calculate IDF only after we exclude the deleted items */
fts_query_calculate_idf(query);
node = rbt_first(query->word_freqs);
word_freq = rbt_value(fts_word_freq_t, node);
/* Calculate the ranking for each doc */
for (node = rbt_first(result->rankings_by_id);
node != NULL;
node = rbt_next(result->rankings_by_id, node)) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, node);
ranking->rank = static_cast<fts_rank_t>(
ranking->rank * word_freq->idf * word_freq->idf);
}
DBUG_RETURN(result);
}
ut_a(rbt_size(query->doc_ids) > 0);
for (node = rbt_first(query->doc_ids);
node;
node = rbt_next(query->doc_ids, node)) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, node);
fts_query_calculate_ranking(query, ranking);
// FIXME: I think we may requre this information to improve the
// ranking of doc ids which have more word matches from
// different FTS indexes.
/* We don't need these anymore free the resources. */
ranking->words = NULL;
if (!result_is_null) {
fts_query_add_ranking(query, result->rankings_by_id, ranking);
if (query->total_size > fts_result_cache_limit) {
query->error = DB_FTS_EXCEED_RESULT_CACHE_LIMIT;
fts_query_free_result(result);
DBUG_RETURN(NULL);
}
}
}
if (result_is_null) {
/* Use doc_ids directly */
rbt_free(result->rankings_by_id);
result->rankings_by_id = query->doc_ids;
query->doc_ids = NULL;
}
DBUG_RETURN(result);
}
/*****************************************************************//**
Get the result of the query. Calculate the similarity coefficient. */
static
fts_result_t*
fts_query_get_result(
/*=================*/
fts_query_t* query, /*!< in: query instance */
fts_result_t* result) /*!< in: result */
{
DBUG_ENTER("fts_query_get_result");
if (rbt_size(query->doc_ids) > 0 || query->flags == FTS_OPT_RANKING) {
/* Copy the doc ids to the result. */
result = fts_query_prepare_result(query, result);
} else {
/* Create an empty result instance. */
result = static_cast<fts_result_t*>(
ut_zalloc_nokey(sizeof(*result)));
}
DBUG_RETURN(result);
}
/*****************************************************************//**
FTS Query free resources and reset. */
static
void
fts_query_free(
/*===========*/
fts_query_t* query) /*!< in: query instance to free*/
{
if (query->read_nodes_graph) {
que_graph_free(query->read_nodes_graph);
}
if (query->root) {
fts_ast_free_node(query->root);
}
if (query->deleted) {
fts_doc_ids_free(query->deleted);
}
if (query->intersection) {
fts_query_free_doc_ids(query, query->intersection);
}
if (query->doc_ids) {
fts_query_free_doc_ids(query, query->doc_ids);
}
if (query->word_freqs) {
const ib_rbt_node_t* node;
/* We need to free any instances of fts_doc_freq_t that we
may have allocated. */
for (node = rbt_first(query->word_freqs);
node;
node = rbt_next(query->word_freqs, node)) {
fts_word_freq_t* word_freq;
word_freq = rbt_value(fts_word_freq_t, node);
/* We need to cast away the const. */
rbt_free(word_freq->doc_freqs);
}
rbt_free(query->word_freqs);
}
if (query->wildcard_words != NULL) {
rbt_free(query->wildcard_words);
}
ut_a(!query->intersection);
if (query->word_map) {
rbt_free(query->word_map);
}
if (query->word_vector != NULL) {
UT_DELETE(query->word_vector);
}
if (query->heap) {
mem_heap_free(query->heap);
}
memset(query, 0, sizeof(*query));
}
/*****************************************************************//**
Parse the query using flex/bison or plugin parser.
@return parse tree node. */
static
fts_ast_node_t*
fts_query_parse(
/*============*/
fts_query_t* query, /*!< in: query instance */
byte* query_str, /*!< in: query string */
ulint query_len) /*!< in: query string length */
{
int error;
fts_ast_state_t state;
bool mode = query->boolean_mode;
DBUG_ENTER("fts_query_parse");
memset(&state, 0x0, sizeof(state));
state.charset = query->fts_index_table.charset;
DBUG_EXECUTE_IF("fts_instrument_query_disable_parser",
query->parser = NULL;);
if (query->parser) {
state.root = state.cur_node =
fts_ast_create_node_list(&state, NULL);
error = fts_parse_by_parser(mode, query_str, query_len,
query->parser, &state);
} else {
/* Setup the scanner to use, this depends on the mode flag. */
state.lexer = fts_lexer_create(mode, query_str, query_len);
state.charset = query->fts_index_table.charset;
error = fts_parse(&state);
fts_lexer_free(state.lexer);
state.lexer = NULL;
}
/* Error during parsing ? */
if (error) {
/* Free the nodes that were allocated during parsing. */
fts_ast_state_free(&state);
} else {
query->root = state.root;
if (UNIV_UNLIKELY(fts_enable_diag_print) && query->root) {
fts_ast_node_print(query->root);
}
}
DBUG_RETURN(state.root);
}
/*******************************************************************//**
FTS Query optimization
Set FTS_OPT_RANKING if it is a simple term query */
static
void
fts_query_can_optimize(
/*===================*/
fts_query_t* query, /*!< in/out: query instance */
uint flags) /*!< In: FTS search mode */
{
fts_ast_node_t* node = query->root;
if (flags & FTS_EXPAND) {
return;
}
/* Check if it has only a term without oper */
ut_ad(node->type == FTS_AST_LIST);
node = node->list.head;
if (node != NULL && node->type == FTS_AST_TERM && node->next == NULL) {
query->flags = FTS_OPT_RANKING;
}
}
/** FTS Query entry point.
@param[in,out] trx transaction
@param[in] index fts index to search
@param[in] flags FTS search mode
@param[in] query_str FTS query
@param[in] query_len FTS query string len in bytes
@param[in,out] result result doc ids
@return DB_SUCCESS if successful otherwise error code */
dberr_t
fts_query(
trx_t* trx,
dict_index_t* index,
uint flags,
const byte* query_str,
ulint query_len,
fts_result_t** result)
{
fts_query_t query;
dberr_t error = DB_SUCCESS;
byte* lc_query_str;
ulint lc_query_str_len;
ulint result_len;
bool boolean_mode;
trx_t* query_trx; /* FIXME: use provided trx */
CHARSET_INFO* charset;
ulint start_time_ms;
bool will_be_ignored = false;
boolean_mode = flags & FTS_BOOL;
*result = NULL;
memset(&query, 0x0, sizeof(query));
query_trx = trx_create();
query_trx->op_info = "FTS query";
start_time_ms = ut_time_ms();
query.trx = query_trx;
query.index = index;
query.boolean_mode = boolean_mode;
query.deleted = fts_doc_ids_create();
query.cur_node = NULL;
query.fts_common_table.type = FTS_COMMON_TABLE;
query.fts_common_table.table_id = index->table->id;
query.fts_common_table.table = index->table;
charset = fts_index_get_charset(index);
query.fts_index_table.type = FTS_INDEX_TABLE;
query.fts_index_table.index_id = index->id;
query.fts_index_table.table_id = index->table->id;
query.fts_index_table.charset = charset;
query.fts_index_table.table = index->table;
query.word_map = rbt_create_arg_cmp(
sizeof(fts_string_t), innobase_fts_text_cmp, (void*)charset);
query.word_vector = UT_NEW_NOKEY(word_vector_t());
query.error = DB_SUCCESS;
/* Setup the RB tree that will be used to collect per term
statistics. */
query.word_freqs = rbt_create_arg_cmp(
sizeof(fts_word_freq_t), innobase_fts_text_cmp,
(void*) charset);
if (flags & FTS_EXPAND) {
query.wildcard_words = rbt_create_arg_cmp(
sizeof(fts_string_t), innobase_fts_text_cmp, (void *)charset);
}
query.total_size += SIZEOF_RBT_CREATE;
query.total_docs = dict_table_get_n_rows(index->table);
query.fts_common_table.suffix = "DELETED";
/* Read the deleted doc_ids, we need these for filtering. */
error = fts_table_fetch_doc_ids(
NULL, &query.fts_common_table, query.deleted);
if (error != DB_SUCCESS) {
goto func_exit;
}
query.fts_common_table.suffix = "DELETED_CACHE";
error = fts_table_fetch_doc_ids(
NULL, &query.fts_common_table, query.deleted);
if (error != DB_SUCCESS) {
goto func_exit;
}
/* Get the deleted doc ids that are in the cache. */
fts_cache_append_deleted_doc_ids(
index->table->fts->cache, query.deleted->doc_ids);
DEBUG_SYNC_C("fts_deleted_doc_ids_append");
/* Sort the vector so that we can do a binary search over the ids. */
fts_doc_ids_sort(query.deleted->doc_ids);
/* Convert the query string to lower case before parsing. We own
the ut_malloc'ed result and so remember to free it before return. */
lc_query_str_len = query_len * charset->casedn_multiply() + 1;
lc_query_str = static_cast<byte*>(ut_malloc_nokey(lc_query_str_len));
/* For binary collations, a case sensitive search is
performed. Hence don't convert to lower case. */
if (my_binary_compare(charset)) {
memcpy(lc_query_str, query_str, query_len);
lc_query_str[query_len]= 0;
result_len= query_len;
} else {
result_len = charset->casedn_z(
(const char*) query_str, query_len,
(char*) lc_query_str, lc_query_str_len);
}
ut_ad(result_len < lc_query_str_len);
query.heap = mem_heap_create(128);
/* Create the rb tree for the doc id (current) set. */
static_assert(!offsetof(fts_ranking_t, doc_id), "ABI");
query.doc_ids = rbt_create(
sizeof(fts_ranking_t), fts_doc_id_cmp);
query.parser = index->parser;
query.total_size += SIZEOF_RBT_CREATE;
/* Parse the input query string. */
if (fts_query_parse(&query, lc_query_str, result_len)) {
fts_ast_node_t* ast = query.root;
ast->trx = trx;
/* Optimize query to check if it's a single term */
fts_query_can_optimize(&query, flags);
DBUG_EXECUTE_IF("fts_instrument_result_cache_limit",
fts_result_cache_limit = 2048;
);
/* Traverse the Abstract Syntax Tree (AST) and execute
the query. */
query.error = fts_ast_visit(
FTS_NONE, ast, fts_query_visitor,
&query, &will_be_ignored);
if (query.error == DB_INTERRUPTED) {
error = DB_INTERRUPTED;
ut_free(lc_query_str);
goto func_exit;
}
/* If query expansion is requested, extend the search
with first search pass result */
if (query.error == DB_SUCCESS && (flags & FTS_EXPAND)) {
query.error = fts_expand_query(index, &query);
}
/* Calculate the inverse document frequency of the terms. */
if (query.error == DB_SUCCESS
&& query.flags != FTS_OPT_RANKING) {
fts_query_calculate_idf(&query);
}
/* Copy the result from the query state, so that we can
return it to the caller. */
if (query.error == DB_SUCCESS) {
*result = fts_query_get_result(&query, *result);
}
error = query.error;
} else {
/* still return an empty result set */
*result = static_cast<fts_result_t*>(
ut_zalloc_nokey(sizeof(**result)));
}
if (trx_is_interrupted(trx)) {
error = DB_INTERRUPTED;
ut_free(lc_query_str);
if (*result) {
fts_query_free_result(*result);
}
goto func_exit;
}
ut_free(lc_query_str);
if (UNIV_UNLIKELY(fts_enable_diag_print) && (*result)) {
ulint diff_time = ut_time_ms() - start_time_ms;
ib::info() << "FTS Search Processing time: "
<< diff_time / 1000 << " secs: " << diff_time % 1000
<< " millisec: row(s) "
<< ((*result)->rankings_by_id
? lint(rbt_size((*result)->rankings_by_id))
: -1);
/* Log memory consumption & result size */
ib::info() << "Full Search Memory: " << query.total_size
<< " (bytes), Row: "
<< ((*result)->rankings_by_id
? rbt_size((*result)->rankings_by_id)
: 0)
<< ".";
}
func_exit:
fts_query_free(&query);
query_trx->free();
return(error);
}
/*****************************************************************//**
FTS Query free result, returned by fts_query(). */
void
fts_query_free_result(
/*==================*/
fts_result_t* result) /*!< in: result instance to free.*/
{
if (result) {
if (result->rankings_by_id != NULL) {
rbt_free(result->rankings_by_id);
result->rankings_by_id = NULL;
}
if (result->rankings_by_rank != NULL) {
rbt_free(result->rankings_by_rank);
result->rankings_by_rank = NULL;
}
ut_free(result);
result = NULL;
}
}
/*****************************************************************//**
FTS Query sort result, returned by fts_query() on fts_ranking_t::rank. */
void
fts_query_sort_result_on_rank(
/*==========================*/
fts_result_t* result) /*!< out: result instance to sort.*/
{
const ib_rbt_node_t* node;
ib_rbt_t* ranked;
ut_a(result->rankings_by_id != NULL);
if (result->rankings_by_rank) {
rbt_free(result->rankings_by_rank);
}
ranked = rbt_create(sizeof(fts_ranking_t), fts_query_compare_rank);
/* We need to free any instances of fts_doc_freq_t that we
may have allocated. */
for (node = rbt_first(result->rankings_by_id);
node;
node = rbt_next(result->rankings_by_id, node)) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, node);
ut_a(ranking->words == NULL);
rbt_insert(ranked, ranking, ranking);
}
/* Reset the current node too. */
result->current = NULL;
result->rankings_by_rank = ranked;
}
/*******************************************************************//**
A debug function to print result doc_id set. */
static
void
fts_print_doc_id(
/*=============*/
fts_query_t* query) /*!< in : tree that stores doc_ids.*/
{
const ib_rbt_node_t* node;
/* Iterate each member of the doc_id set */
for (node = rbt_first(query->doc_ids);
node;
node = rbt_next(query->doc_ids, node)) {
fts_ranking_t* ranking;
ranking = rbt_value(fts_ranking_t, node);
ib::info() << "doc_ids info, doc_id: " << ranking->doc_id;
ulint pos = 0;
fts_string_t word;
while (fts_ranking_words_get_next(query, ranking, &pos, &word)) {
ib::info() << "doc_ids info, value: " << word.f_str;
}
}
}
/*************************************************************//**
This function implements a simple "blind" query expansion search:
words in documents found in the first search pass will be used as
search arguments to search the document again, thus "expand"
the search result set.
@return DB_SUCCESS if success, otherwise the error code */
static MY_ATTRIBUTE((nonnull, warn_unused_result))
dberr_t
fts_expand_query(
/*=============*/
dict_index_t* index, /*!< in: FTS index to search */
fts_query_t* query) /*!< in: FTS query instance */
{
const ib_rbt_node_t* node;
const ib_rbt_node_t* token_node;
fts_doc_t result_doc;
dberr_t error = DB_SUCCESS;
const fts_index_cache_t*index_cache;
/* If no doc is found in first search pass, return */
if (!rbt_size(query->doc_ids)) {
return(error);
}
/* Init "result_doc", to hold words from the first search pass */
fts_doc_init(&result_doc);
mysql_mutex_lock(&index->table->fts->cache->lock);
index_cache = fts_find_index_cache(index->table->fts->cache, index);
mysql_mutex_unlock(&index->table->fts->cache->lock);
ut_a(index_cache);
result_doc.tokens = rbt_create_arg_cmp(
sizeof(fts_token_t), innobase_fts_text_cmp,
(void*) index_cache->charset);
result_doc.charset = index_cache->charset;
result_doc.parser = index_cache->index->parser;
query->total_size += SIZEOF_RBT_CREATE;
if (UNIV_UNLIKELY(fts_enable_diag_print)) {
fts_print_doc_id(query);
}
for (node = rbt_first(query->doc_ids);
node;
node = rbt_next(query->doc_ids, node)) {
fts_ranking_t* ranking;
ulint prev_token_size;
ulint estimate_size;
prev_token_size = rbt_size(result_doc.tokens);
ranking = rbt_value(fts_ranking_t, node);
/* Fetch the documents with the doc_id from the
result of first seach pass. Since we do not
store document-to-word mapping, we need to
fetch the original document and parse them.
Future optimization could be done here if we
support some forms of document-to-word mapping */
fts_doc_fetch_by_doc_id(NULL, ranking->doc_id, index,
FTS_FETCH_DOC_BY_ID_EQUAL,
fts_query_expansion_fetch_doc,
&result_doc);
/* Estimate memory used, see fts_process_token and fts_token_t.
We ignore token size here. */
estimate_size = (rbt_size(result_doc.tokens) - prev_token_size)
* (SIZEOF_RBT_NODE_ADD + sizeof(fts_token_t)
+ sizeof(ib_vector_t) + sizeof(ulint) * 32);
query->total_size += estimate_size;
if (query->total_size > fts_result_cache_limit) {
error = DB_FTS_EXCEED_RESULT_CACHE_LIMIT;
goto func_exit;
}
}
/* Remove words that have already been searched in the first pass */
for (ulint i = 0; i < query->word_vector->size(); i++) {
fts_string_t word = query->word_vector->at(i);
ib_rbt_bound_t parent;
if (query->wildcard_words
&& rbt_search(query->wildcard_words, &parent, &word) == 0) {
/* If it's a wildcard word, remove words having
it as prefix. */
while (rbt_search_cmp(result_doc.tokens,
&parent, &word, NULL,
innobase_fts_text_cmp_prefix)
== 0) {
ut_free(rbt_remove_node(result_doc.tokens,
parent.last));
}
} else {
/* We don't check return value, because the word may
have been deleted by a previous wildcard word as its
prefix, e.g. ('g * good'). */
rbt_delete(result_doc.tokens, &word);
}
}
/* Search the table the second time with expanded search list */
for (token_node = rbt_first(result_doc.tokens);
token_node;
token_node = rbt_next(result_doc.tokens, token_node)) {
fts_token_t* mytoken;
mytoken = rbt_value(fts_token_t, token_node);
/* '%' in the end is treated as prefix search,
it can cause assert failure, so we skip it. */
if (mytoken->text.f_str[mytoken->text.f_len - 1] == '%') {
continue;
}
ut_ad(mytoken->text.f_str[mytoken->text.f_len] == 0);
fts_query_add_word_freq(query, &mytoken->text);
error = fts_query_union(query, &mytoken->text);
if (error != DB_SUCCESS) {
break;
}
}
func_exit:
fts_doc_free(&result_doc);
return(error);
}
/*************************************************************//**
This function finds documents that contain all words in a
phrase or proximity search. And if proximity search, verify
the words are close enough to each other, as in specified distance.
This function is called for phrase and proximity search.
@return TRUE if documents are found, FALSE if otherwise */
static
ibool
fts_phrase_or_proximity_search(
/*===========================*/
fts_query_t* query, /*!< in/out: query instance.
query->doc_ids might be instantiated
with qualified doc IDs */
ib_vector_t* tokens) /*!< in: Tokens contain words */
{
ulint n_matched;
ulint i;
ibool matched = FALSE;
ulint num_token = ib_vector_size(tokens);
fts_match_t* match[MAX_PROXIMITY_ITEM];
ibool end_list = FALSE;
/* Number of matched documents for the first token */
n_matched = ib_vector_size(query->match_array[0]);
/* We have a set of match list for each word, we shall
walk through the list and find common documents that
contain all the matching words. */
for (i = 0; i < n_matched; i++) {
ulint j;
ulint k = 0;
fts_proximity_t qualified_pos;
match[0] = static_cast<fts_match_t*>(
ib_vector_get(query->match_array[0], i));
/* For remaining match list for the token(word), we
try to see if there is a document with the same
doc id */
for (j = 1; j < num_token; j++) {
match[j] = static_cast<fts_match_t*>(
ib_vector_get(query->match_array[j], k));
while (match[j]->doc_id < match[0]->doc_id
&& k < ib_vector_size(query->match_array[j])) {
match[j] = static_cast<fts_match_t*>(
ib_vector_get(
query->match_array[j], k));
k++;
}
if (match[j]->doc_id > match[0]->doc_id) {
/* no match */
if (query->flags & FTS_PHRASE) {
match[0]->doc_id = 0;
}
break;
}
if (k == ib_vector_size(query->match_array[j])) {
end_list = TRUE;
if (query->flags & FTS_PHRASE) {
ulint s;
/* Since i is the last doc id in the
match_array[j], remove all doc ids > i
from the match_array[0]. */
fts_match_t* match_temp;
for (s = i + 1; s < n_matched; s++) {
match_temp = static_cast<
fts_match_t*>(ib_vector_get(
query->match_array[0], s));
match_temp->doc_id = 0;
}
if (match[j]->doc_id !=
match[0]->doc_id) {
/* no match */
match[0]->doc_id = 0;
}
}
if (match[j]->doc_id != match[0]->doc_id) {
goto func_exit;
}
}
/* FIXME: A better solution will be a counter array
remember each run's last position. So we don't
reset it here very time */
k = 0;
}
if (j != num_token) {
continue;
}
/* For this matching doc, we need to further
verify whether the words in the doc are close
to each other, and within the distance specified
in the proximity search */
if (query->flags & FTS_PHRASE) {
matched = TRUE;
} else if (fts_proximity_get_positions(
match, num_token, ULINT_MAX, &qualified_pos)) {
/* Fetch the original documents and count the
words in between matching words to see that is in
specified distance */
if (fts_query_is_in_proximity_range(
query, match, &qualified_pos)) {
/* If so, mark we find a matching doc */
query->error = fts_query_process_doc_id(
query, match[0]->doc_id, 0);
if (query->error != DB_SUCCESS) {
matched = FALSE;
goto func_exit;
}
matched = TRUE;
for (ulint z = 0; z < num_token; z++) {
fts_string_t* token;
token = static_cast<fts_string_t*>(
ib_vector_get(tokens, z));
fts_query_add_word_to_document(
query, match[0]->doc_id, token);
}
}
}
if (end_list) {
break;
}
}
func_exit:
return(matched);
}
/*************************************************************//**
This function checks whether words in result documents are close to
each other (within proximity range as specified by "distance").
If "distance" is MAX_ULINT, then it will find all combinations of
positions of matching words and store min and max positions
in the "qualified_pos" for later verification.
@return true if words are close to each other, false if otherwise */
static
bool
fts_proximity_get_positions(
/*========================*/
fts_match_t** match, /*!< in: query instance */
ulint num_match, /*!< in: number of matching
items */
ulint distance, /*!< in: distance value
for proximity search */
fts_proximity_t* qualified_pos) /*!< out: the position info
records ranges containing
all matching words. */
{
ulint i;
ulint idx[MAX_PROXIMITY_ITEM];
ulint num_pos[MAX_PROXIMITY_ITEM];
ulint min_idx;
qualified_pos->n_pos = 0;
ut_a(num_match <= MAX_PROXIMITY_ITEM);
/* Each word could appear multiple times in a doc. So
we need to walk through each word's position list, and find
closest distance between different words to see if
they are in the proximity distance. */
/* Assume each word's position list is sorted, we
will just do a walk through to all words' lists
similar to a the merge phase of a merge sort */
for (i = 0; i < num_match; i++) {
/* idx is the current position we are checking
for a particular word */
idx[i] = 0;
/* Number of positions for this word */
num_pos[i] = ib_vector_size(match[i]->positions);
}
/* Start with the first word */
min_idx = 0;
while (idx[min_idx] < num_pos[min_idx]) {
ulint position[MAX_PROXIMITY_ITEM];
ulint min_pos = ULINT_MAX;
ulint max_pos = 0;
/* Check positions in each word position list, and
record the max/min position */
for (i = 0; i < num_match; i++) {
position[i] = *(ulint*) ib_vector_get_const(
match[i]->positions, idx[i]);
if (position[i] == ULINT_UNDEFINED) {
break;
}
if (position[i] < min_pos) {
min_pos = position[i];
min_idx = i;
}
if (position[i] > max_pos) {
max_pos = position[i];
}
}
/* If max and min position are within range, we
find a good match */
if (max_pos - min_pos <= distance
&& (i >= num_match || position[i] != ULINT_UNDEFINED)) {
/* The charset has variable character
length encoding, record the min_pos and
max_pos, we will need to verify the actual
number of characters */
qualified_pos->min_pos.push_back(min_pos);
qualified_pos->max_pos.push_back(max_pos);
qualified_pos->n_pos++;
}
/* Otherwise, move to the next position is the
list for the word with the smallest position */
idx[min_idx]++;
}
return(qualified_pos->n_pos != 0);
}
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