When you run a query via SQL over mysql protocol as a result you get the requested columns back or empty result set in case nothing is found.
- SQL
SELECT * FROM tbl;
+------+------+--------+
| id | age | name |
+------+------+--------+
| 1 | 25 | joe |
| 2 | 25 | mary |
| 3 | 33 | albert |
+------+------+--------+
3 rows in set (0.00 sec)
In addition to that you can use SHOW META call to see additional meta-information about the latest query.
- SQL
SELECT id,story_author,comment_author FROM hn_small WHERE story_author='joe' LIMIT 3; SHOW META;
++--------+--------------+----------------+
| id | story_author | comment_author |
+--------+--------------+----------------+
| 152841 | joe | SwellJoe |
| 161323 | joe | samb |
| 163735 | joe | jsjenkins168 |
+--------+--------------+----------------+
3 rows in set (0.01 sec)
+----------------+-------+
| Variable_name | Value |
+----------------+-------+
| total | 3 |
| total_found | 20 |
| total_relation | gte |
| time | 0.010 |
+----------------+-------+
4 rows in set (0.00 sec)
In some cases, e.g. when you do faceted search you can get multiple result sets as a response to your SQL query.
- SQL
SELECT * FROM tbl WHERE MATCH('joe') FACET age;
+------+------+
| id | age |
+------+------+
| 1 | 25 |
+------+------+
1 row in set (0.00 sec)
+------+----------+
| age | count(*) |
+------+----------+
| 25 | 1 |
+------+----------+
1 row in set (0.00 sec)
In case of a warning the result set will include a warning flag and you can see the warning using SHOW WARNINGS.
- SQL
SELECT * from tbl where match('"joe"/3'); show warnings;
+------+------+------+
| id | age | name |
+------+------+------+
| 1 | 25 | joe |
+------+------+------+
1 row in set, 1 warning (0.00 sec)
+---------+------+--------------------------------------------------------------------------------------------+
| Level | Code | Message |
+---------+------+--------------------------------------------------------------------------------------------+
| warning | 1000 | quorum threshold too high (words=1, thresh=3); replacing quorum operator with AND operator |
+---------+------+--------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)
If your query fails you will get an error:
- SQL
SELECT * from tbl where match('@surname joe');
ERROR 1064 (42000): index idx: query error: no field 'surname' found in schema
Via HTTP JSON iterface query result is sent as a JSON document. Example:
{
"took":10,
"timed_out": false,
"hits":
{
"total": 2,
"hits":
[
{
"_id": "1",
"_score": 1,
"_source": { "gid": 11 }
},
{
"_id": "2",
"_score": 1,
"_source": { "gid": 12 }
}
]
}
}
took
: time in milliseconds it took to execute the searchtimed_out
: if the query timed out or nothits
: search results. has the following properties:total
: total number of matching documentshits
: an array containing matches
Query result can also include query profile information, see Query profile.
Each match in the hits
array has the following properties:
_id
: match id_score
: match weight, calculated by ranker_source
: an array containing the attributes of this match
By default all attributes are returned in the _source
array. You can use the _source
property in the request payload to select the fields you want to be included in the result set. Example:
{
"index":"test",
"_source":"attr*",
"query": { "match_all": {} }
}
You can specify the attributes which you want to include in the query result as a string ("_source": "attr*"
) or as an array of strings ("_source": [ "attr1", "attri*" ]"
). Each entry can be an attribute name or a wildcard (*
, %
and ?
symbols are supported).
You can also explicitly specify which attributes you want to include and which to exclude from the result set using the includes
and excludes
properties:
"_source":
{
"includes": [ "attr1", "attri*" ],
"excludes": [ "*desc*" ]
}
An empty list of includes is interpreted as “include all attributes” while an empty list of excludes does not match anything. If an attribute matches both the includes and excludes, then the excludes win.
WHERE
is an SQL clause which works for both fulltext matching and additional filtering. The following operators are available:
- Comparison operators
<, > <=, >=, =, <>, BETWEEN, IN, IS NULL
- Boolean operators
AND, OR, NOT
MATCH('query')
is supported and maps to fulltext query.
{col_name | expr_alias} [NOT] IN @uservar
condition syntax is supported. Refer to SET syntax for a description of global user variables.
If you prefer HTTP JSON interface you can also do filtering. It looks more complex that in SQL, but can be recommended for the cases when you need to prepare a query in a programmatic manner, for example as a result of a form in your application filled out by the user.
Here's an example of several filters in a bool
query.
This is a fulltext query that matches all the documents containing product
in any field. These documents must have a price greater or equal than 500 (gte
) and less or equal than 1000 (lte
). All of these documents must not have a revision less than 15 (lt
).
- JSON
POST /search
{
"index": "test1",
"query": {
"bool": {
"must": [
{ "match" : { "_all" : "product" } },
{ "range": { "price": { "gte": 500, "lte": 1000 } } }
],
"must_not": {
"range": { "revision": { "lt": 15 } }
}
}
}
}
bool
query matches documents matching boolean combinations of other queries and/or filters. Queries and filters must be specified in must
, should
or must_not
sections and can be nested.
- JSON
POST /search
{
"index":"test1",
"query": {
"bool": {
"must": [
{ "match": {"_all":"keyword"} },
{ "range": { "revision": { "gte": 14 } } }
]
}
}
}
Queries and filters specified in the must
section must match the documents. If several fulltext queries or filters are specified, all of them. This is the equivalent of AND
queries in SQL. Note, if you want to match against an array (multi-value attribute) you can specify the attribute multiple times and if only all the queried values are found in the array the result will be positive, e.g.:
"must": [
{"equals" : { "product_codes": 5 }},
{"equals" : { "product_codes": 6 }}
]
Note also, it may be better in terms of performance to use:
{"in" : { "all(product_codes)": [5,6] }}
(see details below).
Queries and filters specified in the should
section should match the documents. If some queries are specified in must
or must_not
, should
queries are ignored. On the other hand, if there are no queries other than should
, then at least one of these queries must match a document for it to match the bool query. This is the equivalent of OR
queries. Note, if you want to match against an array (multi-value attribute) you can specify the attribute multiple times, e.g.:
"should": [
{"equals" : { "product_codes": 7 }},
{"equals" : { "product_codes": 8 }}
]
Note also, it may be better in terms of performance to use:
{"in" : { "any(product_codes)": [7,8] }}
(see details below).
Queries and filters specified in the must_not
section must not match the documents. If several queries are specified under must_not
, the document matches if none of them match.
- JSON
POST /search
{
"index":"t",
"query": {
"bool": {
"should": [
{
"equals": {
"b": 1
}
},
{
"equals": {
"b": 3
}
}
],
"must": [
{
"equals": {
"a": 1
}
}
],
"must_not": {
"equals": {
"b": 2
}
}
}
}
}
A bool query can be nested inside another bool so you can make more complex queries. To make a nested boolean query just use another bool
instead of must
, should
or must_not
. Here is how this query:
a = 2 and (a = 10 or b = 0)
should be presented in JSON.
- JSON
a = 2 and (a = 10 or b = 0)
POST /search
{
"index":"t",
"query": {
"bool": {
"must": [
{
"equals": {
"a": 2
}
},
{
"bool": {
"should": [
{
"equals": {
"a": 10
}
},
{
"equals": {
"b": 0
}
}
]
}
}
]
}
}
}
More complex query:
(a = 1 and b = 1) or (a = 10 and b = 2) or (b = 0)
- JSON
(a = 1 and b = 1) or (a = 10 and b = 2) or (b = 0)
POST /search
{
"index":"t",
"query": {
"bool": {
"should": [
{
"bool": {
"must": [
{
"equals": {
"a": 1
}
},
{
"equals": {
"b": 1
}
}
]
}
},
{
"bool": {
"must": [
{
"equals": {
"a": 10
}
},
{
"equals": {
"b": 2
}
}
]
}
},
{
"bool": {
"must": [
{
"equals": {
"b": 0
}
}
]
}
}
]
}
}
}
Queries in SQL format (query_string
) can also be used in bool queries.
- JSON
POST /search
{
"index": "test1",
"query": {
"bool": {
"must": [
{ "query_string" : "product" },
{ "query_string" : "good" }
]
}
}
}
Equality filters are the simplest filters that work with integer, float and string attributes.
- JSON
POST /search
{
"index":"test1",
"query": {
"equals": { "price": 500 }
}
}
Filter equals
can be applied to a multi-value attribute and you can use:
any()
which will be positive if the attribute has at least one value which equals to the queried value;all()
which will be positive if the attribute has a single value and it equals to the queried value
- JSON
POST /search
{
"index":"test1",
"query": {
"equals": { "any(price)": 100 }
}
}
Set filters check if attribute value is equal to any of the values in the specified set.
Set filters support integer, string and multi-value attributes.
- JSON
POST /search
{
"index":"test1",
"query": {
"in": {
"price": [1,10,100]
}
}
}
When applied to a multi-value attribute you can use:
any()
(equivalent to no function) which will be positive if there's at least one match between the attribute values and the queried values;all()
which will be positive if all the attribute values are in the queried set
- JSON
POST /search
{
"index":"test1",
"query": {
"in": {
"all(price)": [1,10]
}
}
}
Range filters match documents that have attribute values within a specified range.
Range filters support the following properties:
gte
: greater than or equal togt
: greater thanlte
: less than or equal tolt
: less than
- JSON
POST /search
{
"index":"test1",
"query": {
"range": {
"price": {
"gte": 500,
"lte": 1000
}
}
}
}
geo_distance
filters are used to filter the documents that are within a specific distance from a geo location.
Specifies the pin location, in degrees. Distances are calculated from this point.
Specifies the attributes that contain latitude and longitude.
Specifies distance calculation function. Can be either adaptive or haversine. adaptive is faster and more precise, for more details see GEODIST()
. Optional, defaults to adaptive.
Specifies the maximum distance from the pin locations. All documents within this distance match. The distance can be specified in various units. If no unit is specified, the distance is assumed to be in meters. Here is a list of supported distance units:
- Meter:
m
ormeters
- Kilometer:
km
orkilometers
- Centimeter:
cm
orcentimeters
- Millimeter:
mm
ormillimeters
- Mile:
mi
ormiles
- Yard:
yd
oryards
- Feet:
ft
orfeet
- Inch:
in
orinch
- Nautical mile:
NM
,nmi
ornauticalmiles
location_anchor
and location_source
properties accept the following latitude/longitude formats:
- an object with lat and lon keys:
{ "lat": "attr_lat", "lon": "attr_lon" }
- a string of the following structure:
"attr_lat, attr_lon"
- an array with the latitude and longitude in the following order:
[attr_lon, attr_lat]
Latitude and longitude are specified in degrees.
- Basic example
- Advanced example
POST /search
{
"index":"test",
"query": {
"geo_distance": {
"location_anchor": {"lat":49, "lon":15},
"location_source": {"attr_lat, attr_lon"},
"distance_type": "adaptive",
"distance":"100 km"
}
}
}
Manticore lets you use arbitrary arithmetic expressions both via SQL and HTTP, involving attribute values, internal attributes (document ID and relevance weight), arithmetic operations, a number of built-in functions, and user-defined functions. Here’s the complete reference list for quick access.
+, -, *, /, %, DIV, MOD
The standard arithmetic operators. Arithmetic calculations involving those can be performed in three different modes:
- using single-precision, 32-bit IEEE 754 floating point values (the default),
- using signed 32-bit integers
- using 64-bit signed integers
The expression parser will automatically switch to integer mode if there are no operations the result in a floating point value. Otherwise, it will use the default floating point mode. For instance, a+b will be computed using 32-bit integers if both arguments are 32-bit integers; or using 64-bit integers if both arguments are integers but one of them is 64-bit; or in floats otherwise. However, a/b
or sqrt(a)
will always be computed in floats, because these operations return a result of non-integer type. To avoid the first, you can either use IDIV(a,b)
or a DIV b
form. Also, a*b
will not be automatically promoted to 64-bit when the arguments are 32-bit. To enforce 64-bit results, you can use BIGINT(), but note that if there are non-integer operations, BIGINT() will simply be ignored.
<, > <=, >=, =, <>
Comparison operators return 1.0 when the condition is true and 0.0 otherwise. For instance, (a=b)+3
will evaluate to 4 when attribute a
is equal to attribute b
, and to 3 when a
is not. Unlike MySQL, the equality comparisons (ie. =
and <>
operators) introduce a small equality threshold (1e-6 by default). If the difference between compared values is within the threshold, they will be considered equal. BETWEEN
and IN
operators in case of multi-value attribute return true if at least one value matches the condition(same as ANY()). IN
doesn't support JSON attributes. IS (NOT) NULL
is supported only for JSON attributes.
AND, OR, NOT
Boolean operators (AND, OR, NOT) behave as usual. They are left-associative and have the least priority compared to other operators. NOT has more priority than AND and OR but nevertheless less than any other operator. AND and OR have the same priority so brackets use is recommended to avoid confusion in complex expressions.
&, |
These operators perform bitwise AND and OR respectively. The operands must be of an integer types.
- ABS()
- ALL()
- ANY()
- ATAN2()
- BIGINT()
- BITDOT()
- BM25F()
- CEIL()
- CONCAT()
- CONTAINS()
- COS()
- CRC32()
- DAY()
- DOUBLE()
- EXP()
- FIBONACCI()
- FLOOR()
- GEODIST()
- GEOPOLY2D()
- GREATEST()
- HOUR()
- IDIV()
- IF()
- IN()
- INDEXOF()
- INTEGER()
- INTERVAL()
- LAST_INSERT_ID()
- LEAST()
- LENGTH()
- LN()
- LOG10()
- LOG2()
- MAX()
- MIN()
- MINUTE()
- MIN_TOP_SORTVAL()
- MIN_TOP_WEIGHT()
- MONTH()
- NOW()
- PACKEDFACTORS()
- POLY2D()
- POW()
- RAND()
- REGEX()
- REMAP()
- SECOND()
- SIN()
- SINT()
- SQRT()
- SUBSTRING_INDEX()
- TO_STRING()
- UINT()
- YEAR()
- YEARMONTH()
- YEARMONTHDAY()
- WEIGHT()
In HTTP JSON interface expressions are supported via script_fields
and expressions
{
"index": "test",
"query": {
"match_all": {}
}, "script_fields": {
"add_all": {
"script": {
"inline": "( gid * 10 ) | crc32(title)"
}
},
"title_len": {
"script": {
"inline": "crc32(title)"
}
}
}
}
In this example two expressions are created: add_all
and title_len
. First expression calculates ( gid * 10 ) | crc32(title)
and stores the result in the add_all
attribute. Second expression calculates crc32(title)
and stores the result in the title_len
attribute.
Only inline
expressions are supported for now. The value of inline
property (the expression to compute) has the same syntax as SQL expressions.
The expression name can be used in filtering or sorting.
- script_fields
{
"index":"movies_rt",
"script_fields":{
"cond1":{
"script":{
"inline":"actor_2_facebook_likes =296 OR movie_facebook_likes =37000"
}
},
"cond2":{
"script":{
"inline":"IF (IN (content_rating,'TV-PG','PG'),2, IF(IN(content_rating,'TV-14','PG-13'),1,0))"
}
}
},
"limit":10,
"sort":[
{
"cond2":"desc"
},
{
"actor_1_name":"asc"
},
{
"actor_2_name":"desc"
}
],
"profile":true,
"query":{
"bool":{
"must":[
{
"match":{
"*":"star"
}
},
{
"equals":{
"cond1":1
}
}
],
"must_not":[
{
"equals":{
"content_rating":"R"
}
}
]
}
}
}
The expression values are by default included in the _source
array of the result set. If the source is selective (see Source selection) the expressions name can be added to the _source
parameter in the request.
expressions
is an alternative to script_fields
with a simpler syntax. Example request adds two expressions and stores the results into add_all
and title_len
attributes.
- expressions
{
"index": "test",
"query": { "match_all": {} },
"expressions":
{
"add_all": "( gid * 10 ) | crc32(title)",
"title_len": "crc32(title)"
}
}