# Boolean optimization

Queries can 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 sum 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 sum 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 queries consumes CPU time, so for simple queries or hand-optimized queries, you'll achieve better results with the default `boolean_simplify=0` value. Simplifications often benefit complex queries or algorithmically generated queries.

Queries like `-dog`, which could potentially include all documents from the collection are not allowed by default. To allow them, you must specify `not_terms_only_allowed=1` either as a global setting or as a search option.

# Search results

## SQL

When you run a query via SQL over the MySQL protocol, you receive the requested columns as a result or an empty result set if nothing is found.

‹›
• SQL
SQL
📋
``SELECT * FROM tbl;``
‹›
Response
``````+------+------+--------+
| id   | age  | name   |
+------+------+--------+
|    1 |   25 | joe    |
|    2 |   25 | mary   |
|    3 |   33 | albert |
+------+------+--------+
3 rows in set (0.00 sec)``````

Additionally, you can use the SHOW META call to see extra meta-information about the latest query.

‹›
• SQL
SQL
📋
``SELECT id,story_author,comment_author FROM hn_small WHERE story_author='joe' LIMIT 3; SHOW META;``
‹›
Response
``````++--------+--------------+----------------+
| 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, such as when performing a faceted search, you may receive multiple result sets as a response to your SQL query.

‹›
• SQL
SQL
📋
``SELECT * FROM tbl WHERE MATCH('joe') FACET age;``
‹›
Response
``````+------+------+
| 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
SQL
📋
``SELECT * from tbl where match('"joe"/3'); show warnings;``
‹›
Response
``````+------+------+------+
| 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)``````

‹›
• SQL
SQL
📋
``SELECT * from tbl where match('@surname joe');``
‹›
Response
``ERROR 1064 (42000): index idx: query error: no field 'surname' found in schema``

## HTTP

Via the HTTP JSON interface, the 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 search
• `timed_out`: whether the query timed out or not
• `hits`: search results, with the following properties:
• `total`: total number of matching documents
• `hits`: an array containing matches

The 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 the ranker
• `_source`: an array containing the attributes of this match

### Source selection

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 include in the result set. Example:

``````{
"index":"test",
"_source":"attr*",
"query": { "match_all": {} }
}``````

You can specify the attributes 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.

# Filters

## WHERE

`WHERE` is an SQL clause that works for both full-text matching and additional filtering. The following operators are available:

`MATCH('query')` is supported and maps to a full-text query.

The `{col_name | expr_alias} [NOT] IN @uservar` condition syntax is supported. Refer to the SET syntax for a description of global user variables.

## HTTP JSON

If you prefer the HTTP JSON interface, you can also apply filtering. It might seem more complex than SQL, but it is recommended for cases when you need to prepare a query programmatically, such as when a user fills out a form in your application.

Here's an example of several filters in a `bool` query.

This full-text query matches all documents containing `product` in any field. These documents must have a price greater than or equal to 500 (`gte`) and less than or equal to 1000 (`lte`). All of these documents must not have a revision less than 15 (`lt`).

‹›
• JSON
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

The `bool` query matches documents based on 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
JSON
📋
``````POST /search
{
"index":"test1",
"query": {
"bool": {
"must": [
{ "match": {"_all":"keyword"} },
{ "range": { "revision": { "gte": 14 } } }
]
}
}
}``````

### must

Queries and filters specified in the `must` section are required to match the documents. If multiple fulltext queries or filters are specified, all of them must match. This is the equivalent of `AND` queries in SQL. Note that if you want to match against an array (multi-value attribute), you can specify the attribute multiple times. The result will be positive only if all the queried values are found in the array, 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).

### should

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).

### must_not

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
JSON
📋
``````POST /search
{
"index":"t",
"query": {
"bool": {
"should": [
{
"equals": {
"b": 1
}
},
{
"equals": {
"b": 3
}
}
],
"must": [
{
"equals": {
"a": 1
}
}
],
"must_not": {
"equals": {
"b": 2
}
}
}
}
}``````

### Nested bool query

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
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
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

Queries in SQL format (`query_string`) can also be used in bool queries.

‹›
• JSON
JSON
📋
``````POST /search
{
"index": "test1",
"query": {
"bool": {
"must": [
{ "query_string" : "product" },
{ "query_string" : "good" }
]
}
}
}``````

## Various filters

### Equality filters

Equality filters are the simplest filters that work with integer, float and string attributes.

‹›
• JSON
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
JSON
📋
``````POST /search
{
"index":"test1",
"query": {
"equals": { "any(price)": 100 }
}
}``````

### Set filters

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
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
JSON
📋
``````POST /search
{
"index":"test1",
"query": {
"in": {
"all(price)": [1,10]
}
}
}``````

### Range filters

Range filters match documents that have attribute values within a specified range.

Range filters support the following properties:

• `gte`: greater than or equal to
• `gt`: greater than
• `lte`: less than or equal to
• `lt`: less than
‹›
• JSON
JSON
📋
``````POST /search
{
"index":"test1",
"query": {
"range": {
"price": {
"gte": 500,
"lte": 1000
}
}
}
}``````

### Geo distance filters

`geo_distance` filters are used to filter the documents that are within a specific distance from a geo location.

##### location_anchor

Specifies the pin location, in degrees. Distances are calculated from this point.

##### location_source

Specifies the attributes that contain latitude and longitude.

##### distance_type

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.

##### distance

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` or `meters`
• Kilometer: `km` or `kilometers`
• Centimeter: `cm` or `centimeters`
• Millimeter: `mm` or `millimeters`
• Mile: `mi` or `miles`
• Yard: `yd` or `yards`
• Feet: `ft` or `feet`
• Inch: `in` or `inch`
• Nautical mile: `NM`, `nmi` or `nauticalmiles`

`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
``````POST /search