As some characters are used as operators in the query string, they should be escaped to avoid query errors or unwanted matching conditions.
The following characters should be escaped using backslash (\):
! " $ ' ( ) - / < @ \ ^ | ~SELECT * FROM your_index WHERE MATCH('l\'italiano');Use double backslash to escape all other characters.
SELECT * FROM your_index WHERE MATCH('r\\&b | \\(official video\\)');Pay attention that in order to escape backslash character you should use "\\\\" syntax.
SELECT * FROM your_index WHERE MATCH('\\\\ABC');Also, if you run your queries using some programming language don't forget about a mysql escaping function (e.g., mysqli_real_escape_string in PHP or conn.escape_string in Python) to escape these characters the same way as described above.
Example of a complex query:
"hello world" @title "example program"~5 @body python -(php|perl) @* codeThe full meaning of this search is:
- Find the words 'hello' and 'world' adjacently in any field in a document;
- Additionally, the same document must also contain the words 'example' and 'program' in the title field, with up to, but not including, 5 words between the words in question; (E.g. "example PHP program" would be matched however "example script to introduce outside data into the correct context for your program" would not because two terms have 5 or more words between them)
- Additionally, the same document must contain the word 'python' in the body field, but not contain either 'php' or 'perl';
- Additionally, the same document must contain the word 'code' in any field.
OR operator precedence is higher than AND, so "looking for cat | dog | mouse" means "looking for ( cat | dog | mouse )" and not "(looking for cat) | dog | mouse".
To understand how a query will be executed, Manticore Search offer query profile tooling for viewing the query tree created by a query expression.
When using SQL statement the full-text query profiling needs to be enabled before running the desired query:
SET profiling =1;
SELECT * FROM test WHERE MATCH('@title abc* @body hey');To view the query tree, we must run SHOW PLAN right after the execution of the query:
SHOW PLAN;The command will return the structure of the executed query. Please note that the 3 statements - SET profiling, the query and SHOW - must run on the same session.
In HTTP, we can just enable "profile":true to get in response the full-text query tree structure.
{
"index":"test",
"profile":true,
"query":
{
"match_phrase": { "_all" : "had grown quite" }
}
}The response will contain a profile object in which we can find a member query.
query property contains the transformed full-text query tree. Each node contains:
type: node type. Can be AND, OR, PHRASE, KEYWORD etc.description: query subtree for this node shown as a string (inSHOW PLANformat)children: child nodes, if anymax_field_pos: maximum position within a field
A keyword node will also provide:
word: transformed keyword.querypos: position of this keyword in a query.excluded: keyword excluded from query.expanded: keyword added by prefix expansion.field_start: keyword must occur at the very start of the field.field_end: keyword must occur at the very end of the field.boost: keyword IDF will be multiplied by this.
- SQL
- HTTP
- PHP
SET profiling=1;
SELECT * FROM test WHERE MATCH('@title abc* @body hey');
SHOW PLAN \G*************************** 1\. row ***************************
Variable: transformed_tree
Value: AND(
OR(fields=(title), KEYWORD(abcx, querypos=1, expanded), KEYWORD(abcm, querypos=1, expanded)),
AND(fields=(body), KEYWORD(hey, querypos=2)))
1 row in set (0.00 sec)In some cases the evaluated query tree can be rather different from the original one because of expansions and other transformations.
- SQL
- HTTP
- PHP
SET profiling=1;
SELECT id FROM forum WHERE MATCH('@title way* @content hey') LIMIT 1;
SHOW PLAN;Query OK, 0 rows affected (0.00 sec)
+--------+
| id |
+--------+
| 711651 |
+--------+
1 row in set (0.04 sec)
+------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Variable | Value |
+------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| transformed_tree | AND(
OR(
OR(
AND(fields=(title), KEYWORD(wayne, querypos=1, expanded)),
OR(
AND(fields=(title), KEYWORD(ways, querypos=1, expanded)),
AND(fields=(title), KEYWORD(wayyy, querypos=1, expanded)))),
AND(fields=(title), KEYWORD(way, querypos=1, expanded)),
OR(fields=(title), KEYWORD(way*, querypos=1, expanded))),
AND(fields=(content), KEYWORD(hey, querypos=2))) |
+------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)The SQL statement EXPLAIN QUERY allows displaying the execution tree of a provided full-text query without running an actual search query on the index.
- SQL
EXPLAIN QUERY index_base '@title running @body dog'\G EXPLAIN QUERY index_base '@title running @body dog'\G
*************************** 1\. row ***************************
Variable: transformed_tree
Value: AND(
OR(
AND(fields=(title), KEYWORD(run, querypos=1, morphed)),
AND(fields=(title), KEYWORD(running, querypos=1, morphed))))
AND(fields=(body), KEYWORD(dog, querypos=2, morphed)))When expression ranker is used, it is possible to expose the values of the calculated factors using [PACKEDFACTORS()](Functions/Searching_and_ranking_functions#PACKEDFACTORS()).
The function returns:
- the values of document level factors
- list with each field that returned a hit
- list with each keyword from the query and their tf and idf values
The values can be used to understand why certain documents get scored lower or higher in a search or to improve the existing ranking expression.
Queries may be automatically optimized if OPTION boolean_simplify=1 is specified. Some transformations performed by this optimization include:
- Excess brackets: ((A | B) | C) becomes ( A | B | C ); ((A B) C) becomes ( A B C )
- Excess AND NOT: ((A !N1) !N2) becomes (A !(N1 | N2))
- Common NOT: ((A !N) | (B !N)) becomes ((A|B) !N)
- Common Compound NOT: ((A !(N AA)) | (B !(N BB))) becomes (((A|B) !N) | (A !AA) | (B !BB)) if the cost of evaluating N is greater than the added together costs of evaluating A and B
- Common subterm: ((A (N | AA)) | (B (N | BB))) becomes (((A|B) N) | (A AA) | (B BB)) if the cost of evaluating N is greater than the added together costs of evaluating A and B
- Common keywords: (A | "A B"~N) becomes A; ("A B" | "A B C") becomes "A B"; ("A B"~N | "A B C"~N) becomes ("A B"~N)
- Common phrase: ("X A B" | "Y A B") becomes ("("X"|"Y") A B")
- Common AND NOT: ((A !X) | (A !Y) | (A !Z)) becomes (A !(X Y Z))
- Common OR NOT: ((A !(N | N1)) | (B !(N | N2))) becomes (( (A !N1) | (B !N2) ) !N)
Note that optimizing the queries consumes CPU time, so for simple queries -or for hand-optimized queries- you'll do better with the default
boolean_simplify=0value. Simplifications are often better for complex queries, or algorithmically generated queries.
Queries like "-dog", which implicitly include all documents from the collection, can not be evaluated. This is both for technical and performance reasons. Technically, Manticore does not always keep a list of all IDs. Performance-wise, when the collection is huge (ie. 10-100M documents), evaluating such queries could take very long.