2.2. RQL syntax#

2.2.1. Reserved keywords#


The keywords are not case sensitive. You should not use them when defining your schema, or as RQL variable names.

2.2.2. Case#

  • Variables should be all upper-cased.

  • Relation should be all lower-cased and match exactly names of relations defined in the schema.

  • Entity types should start with an upper cased letter and be followed by at least a lower cased latter.

2.2.3. Variables and typing#

Entities and values to browse and/or select are represented in the query by variables that must be written in capital letters.

With RQL, we do not distinguish between entities and attributes. The value of an attribute is considered as an entity of a particular type (see below), linked to one (real) entity by a relation called the name of the attribute, where the entity is the subject and the attribute the object.

The possible type(s) for each variable is derived from the schema according to the constraints expressed above and thanks to the relations between each variable.

We can restrict the possible types for a variable using the special relation is in the restrictions.

2.2.4. Virtual relations#

Those relations may only be used in RQL query but are not actual attributes of your entities.

  • has_text: relation to use to query the full text index (only for entities having fulltextindexed attributes).

  • identity: relation to use to tell that a RQL variable is the same as another when you’ve to use two different variables for querying purpose. On the opposite it’s also useful together with the NOT operator to tell that two variables should not identify the same entity

2.2.5. Literal expressions#

Bases types supported by RQL are those supported by yams schema. Literal values are expressed as explained below:

  • string should be between double or single quotes. If the value contains a quote, it should be preceded by a backslash ‘\’

  • floats separator is dot ‘.’

  • boolean values are TRUE and FALSE keywords

  • date and time should be expressed as a string with ISO notation : YYYY/MM/DD [hh:mm], or using keywords TODAY and NOW

You may also use the NULL keyword, meaning ‘unspecified’.

2.2.6. Operators# Logical operators#

AND, OR, NOT, ','

‘,’ is equivalent to ‘AND’ but with the smallest among the priority of logical operators (see Operators priority). Mathematical operators#







2 + 3




2 - 3




2 * 3




4 / 2



modulo (remainder)

5 % 4




2.0 ^ 3.0



bitwise AND

91 & 15



bitwise OR

32 | 3



bitwise XOR

17 # 5



bitwise NOT




bitwise shift left

1 << 4



bitwise shift right

8 >> 2


Notice integer division truncates results depending on the backend behaviour. For instance, postgresql does. Comparison operators#

=, !=, <, <=, >=, >, IN

The syntax to use comparison operators is:

VARIABLE attribute <operator> VALUE

The = operator is the default operator and can be omitted, i.e. :

VARIABLE attribute = VALUE

is equivalent to


The operator IN provides a list of possible values:

Any X WHERE X name IN ('chauvat', 'fayolle', 'di mascio', 'thenault') String operators#


The LIKE string operator can be used with the special character % in a string as wild-card:

-- match every entity whose name starts with 'Th'
Any X WHERE X name ~= 'Th%'
-- match every entity whose name endswith 'lt'
Any X WHERE X name LIKE '%lt'
-- match every entity whose name contains a 'l' and a 't'
Any X WHERE X name LIKE '%l%t%'

ILIKE is the case insensitive version of LIKE. It’s not available on all backend (e.g. sqlite doesn’t support it). If not available for your backend, ILIKE will behave like LIKE.

~= is a shortcut version of ILIKE, or of LIKE when the former is not available on the back-end.

The REGEXP is an alternative to LIKE that supports POSIX regular expressions:

-- match entities whose title starts with a digit
Any X WHERE X title REGEXP "^[0-9].*"

The underlying SQL operator used is back-end-dependent :

  • the ~ operator is used for postgresql,

  • the REGEXP operator for mysql and sqlite.

Other back-ends are not supported yet. Operators priority#

  1. (, )

  2. ^, <<, >>

  3. *, /, %, &

  4. +, -, |, #

  5. NOT

  6. AND

  7. OR

  8. ,

2.2.7. Search Query#

Simplified grammar of search query:

[ `DISTINCT`] `Any` V1 (, V2) \*
[ `GROUPBY` V1 (, V2) \*] [ `ORDERBY` <orderterms>]
[ `LIMIT` <value>] [ `OFFSET` <value>]
[ `WHERE` <triplet restrictions>]
[ `WITH` V1 (, V2)\* BEING (<query>)]
[ `HAVING` <other restrictions>]
[ `UNION` <query>] Selection#

The fist occuring clause is the selection of terms that should be in the result set. Terms may be variable, literals, function calls, arithmetic, etc. and each term is separated by a comma.

There will be as much column in the result set as term in this clause, respecting order.

Syntax for function call is somewhat intuitive, for instance:

Any UPPER(N) WHERE P firstname N Grouping and aggregating#

The GROUPBY keyword is followed by a list of terms on which results should be grouped. They are usually used with aggregate functions, responsible to aggregate values for each group (see Aggregate functions).

For grouped queries, all selected variables must be either aggregated (i.e. used by an aggregate function) or grouped (i.e. listed in the GROUPBY clause). Sorting#

The ORDERBY keyword if followed by the definition of the selection order: variable or column number followed by sorting method (ASC, DESC), ASC being the default. If the sorting method is not specified, then the sorting is ascendant (ASC).

It is also possible to precise a specific ordering for NULL values. The NULLSFIRST and NULLSLAST options can be used to determine whether nulls appear before or after non-null values in the sort ordering. By default, null values sort as if larger than any non-null value; that is, NULLSFIRST is the default for DESC order, and NULLSLAST otherwise. These options are written after the sorting method when it is specified. For instance, this request will return all projects ordered by creation date in descending order, with projects with no date in last position.

Any X ORDERBY Y DESC NULLSLAST WHERE X creation_date Y Pagination#

The LIMIT and OFFSET keywords may be respectively used to limit the number of results and to tell from which result line to start (for instance, use LIMIT 20 to get the first 20 results, then LIMIT 20 OFFSET 20 to get the next 20. Restrictions#

The WHERE keyword introduce one of the “main” part of the query, where you “define” variables and add some restrictions telling what you’re interested in.

It’s a list of triplets “subject relation object”, e.g. V1 relation (V2 | <static value>). Triplets are separated using Logical operators.


About the negation operator (NOT):

  • NOT X relation Y is equivalent to NOT EXISTS(X relation Y)

  • Any X WHERE NOT X owned_by U means “entities that have no relation owned_by”.

  • Any X WHERE NOT X owned_by U, U login "syt" means “the entity have no relation owned_by with the user syt”. They may have a relation “owned_by” with another user.

In this clause, you can also use EXISTS when you want to know if some expression is true and do not need the complete set of elements that make it true. Testing for existence is much faster than fetching the complete set of results, especially when you think about using OR against several expressions. For instance if you want to retrieve versions which are in state “ready” or tagged by “priority”, you should write :

WHERE X num N, X version_of P, P name PN,
      EXISTS(X in_state S, S name "ready")
      OR EXISTS(T tags X, T name "priority")


WHERE X num N, X version_of P, P name PN,
      (X in_state S, S name "ready")
      OR (T tags X, T name "priority")

Both queries aren’t at all equivalent :

  • the former will retrieve all versions, then check for each one which are in the matching state of or tagged by the expected tag,

  • the later will retrieve all versions, state and tags (cartesian product!), compute join and then exclude each row which are in the matching state or tagged by the expected tag. This implies that you won’t get any result if the in_state or tag tables are empty (ie there is no such relation in the application). This is usually NOT what you want.

Another common case where you may want to use EXISTS is when you find yourself using DISTINCT at the beginning of your query to remove duplicate results. The typical case is when you have a multivalued relation such as Version version_of Project and you want to retrieve projects which have a version:

Any P WHERE V version_of P

will return each project number of versions times. So you may be tempted to use:

DISTINCT Any P WHERE V version_of P

This will work, but is not efficient, as it will use the SELECT DISTINCT SQL predicate, which needs to retrieve all projects, then sort them and discard duplicates, which can have a very high cost for large result sets. So the best way to write this is:

Any P WHERE EXISTS(V version_of P)

You can also use the question mark (?) to mark optional relations. This allows you to select entities related or not to another. It is a similar concept to Left outer join:

the result of a left outer join (or simply left join) for table A and B always contains all records of the “left” table (A), even if the join-condition does not find any matching record in the “right” table (B).

You must use the ? behind a variable to specify that the relation to that variable is optional. For instance:

  • Bugs of a project attached or not to a version

    Any X, V WHERE X concerns P, P eid 42, X corrected_in V?

    You will get a result set containing all the project’s tickets, with either the version in which it’s fixed or None for tickets not related to a version.

  • All cards and the project they document if any

    Any C, P WHERE C is Card, P? documented_by C

Notice you may also use outer join:

  • on the RHS of attribute relation, e.g.

    Any X WHERE X ref XR, Y name XR?

    so that Y is outer joined on X by ref/name attributes comparison

  • on any side of an HAVING expression, e.g.

    Any X WHERE X creation_date XC, Y creation_date YC

    so that Y is outer joined on X by comparison of the year extracted from their creation date.

    Any X WHERE X creation_date XC, Y creation_date YC

    would outer join X on Y instead. Having restrictions#

The HAVING clause, as in SQL, may be used to restrict a query according to value returned by an aggregate function, e.g.


It may however be used for something else: In the WHERE clause, we are limited to triplet expressions, so some things may not be expressed there. Let’s take an example : if you want to get people whose upper-cased first name equals to another person upper-cased first name. There is no proper way to express this using triplet, so you should use something like:

Any X WHERE X firstname XFN, Y firstname YFN, NOT X identity Y HAVING UPPER(XFN) = UPPER(YFN)

Another example: imagine you want person born in 2000:

Any X WHERE X birthday XB HAVING YEAR(XB) = 2000

Notice that while we would like this to work without the HAVING clause, this can’t be currently be done because it introduces an ambiguity in RQL’s grammar that can’t be handled by Yapps, the parser’s generator we’re using. Sub-queries#

The WITH keyword introduce sub-queries clause. Each sub-query has the form:

V1(,V2) BEING (rql query)

Variables at the left of the BEING keyword defines into which variables results from the sub-query will be mapped to into the outer query. Sub-queries are separated from each other using a comma.

Let’s say we want to retrieve for each project its number of versions and its number of tickets. Due to the nature of relational algebra behind the scene, this can’t be achieved using a single query. You have to write something along the line of:

Any X, VC, TC WHERE X identity XX
     XX, TC BEING (Any X, COUNT(T) GROUPBY X WHERE T ticket_of X)

Notice that we can’t reuse a same variable name as alias for two different sub-queries, hence the usage of ‘X’ and ‘XX’ in this example, which are then unified using the special identity relation (see Virtual relations).


Sub-queries define a new variable scope, so even if a variable has the same name in the outer query and in the sub-query, they technically aren’t the same variable. So:

    (Any W, REF WHERE W is Workcase, W ref REF,
                      W concerned_by D, D name "Logilab")

could be written:

   (Any W1, REF1 WHERE W1 is Workcase, W1 ref REF1,
                       W1 concerned_by D, D name "Logilab")

Also, when a variable is coming from a sub-query, you currently can’t reference its attribute or inlined relations in the outer query, you’ve to fetch them in the sub-query. For instance, let’s say we want to sort by project name in our first example, we would have to write:

WITH X, XN, VC BEING (Any X, COUNT(V) GROUPBY X,XN WHERE V version_of X, X name XN),
     XX, TC BEING (Any X, COUNT(T) GROUPBY X WHERE T ticket_of X)

instead of:

Any X, VC, TC ORDERBY XN WHERE X identity XX, X name XN,
     XX, TC BEING (Any X, COUNT(T) GROUPBY X WHERE T ticket_of X)

which would result in a SQL execution error. Union#

You may get a result set containing the concatenation of several queries using the UNION. The selection of each query should have the same number of columns.

(Any X, XN WHERE X is Person, X surname XN) UNION (Any X,XN WHERE X is Company, X name XN)

2.2.8. Available functions#

Below is the list of aggregate and transformation functions that are supported natively by the framework. Notice that cubes may define additional functions. Aggregate functions#


return the number of rows


return the minimum value


return the maximum value


return the average value


return the sum of values


return each unique value separated by a comma (for string only)

All aggregate functions above take a single argument. Take care some aggregate functions (e.g. MAX, MIN) may return None if there is no result row. String transformation functions#


upper case the string


lower case the string


return the length of the string

SUBSTRING(String, start, length)

extract from the string a string starting at given index and of given length

TEXT_LIMIT_SIZE(String, max size)

if the length of the string is greater than given max size, strip it and add ellipsis (”…”). The resulting string will hence have max size + 3 characters

LIMIT_SIZE(String, format, max size)

similar to the above, but allow to specify the MIME type of the text contained by the string. Supported formats are text/html, text/xhtml and text/xml. All others will be considered as plain text. For non plain text format, sgml tags will be first removed before limiting the string. Date extraction functions#


return the year of a date or datetime


return the month of a date or datetime


return the day of a date or datetime


return the hours of a datetime


return the minutes of a datetime


return the seconds of a datetime


return the day of week of a date or datetime. Sunday == 1, Saturday == 7. Other functions#


return the absolute value of a number


return a pseudo-random value from 0.0 to 1.0


expect X to be an attribute whose value is stored in a BFSStorage and return its path on the file system


expect X to be an entity used in a has_text relation, and return a number corresponding to the rank order of each resulting entity

CAST(Type, X)

expect X to be an attribute and return it casted into the given final type

2.2.9. Examples#

  • Search for the object of identifier 53

    Any X WHERE X eid 53
  • Search material such as comics, owned by syt and available

    Any X WHERE X is Document,
                X occurence_of F, F class C, C name 'Comics',
                X owned_by U, U login 'syt',
                X available TRUE
  • Looking for people working for eurocopter interested in training

    Any P WHERE P is Person, P work_for S, S name 'Eurocopter',
                P interested_by T, T name 'training'
  • Search note less than 10 days old written by jphc or ocy

    Any N WHERE N is Note, N written_on D, D day> (today -10),
                N written_by P, P name 'jphc' or P name 'ocy'
  • Looking for people interested in training or living in Paris

    Any P WHERE P is Person, EXISTS(P interested_by T, T name 'training') OR
                (P city 'Paris')
  • The surname and firstname of all people

    Any N, P WHERE X is Person, X name N, X firstname P

    Note that the selection of several entities generally force the use of “Any” because the type specification applies otherwise to all the selected variables. We could write here

    String N, P WHERE X is Person, X name N, X first_name P

    Note: You can not specify several types with * … where X is FirstType or X is SecondType*. To specify several types explicitly, you have to do

    Any X WHERE X is IN (FirstType, SecondType)

2.2.10. Insertion query#

INSERT <entity type> V1 (, <entity type> V2) * : <assignments> [ WHERE <restriction>]


list of relations to assign in the form V1 relationship V2 | <static value>

The restriction can define variables used in assignments.

Caution, if a restriction is specified, the insertion is done for each line result returned by the restriction.

  • Insert a new person named ‘foo’

    INSERT Person X: X name 'foo'
  • Insert a new person named ‘foo’, another called ‘nice’ and a ‘friend’ relation between them

    INSERT Person X, Person Y: X name 'foo', Y name 'nice', X friend Y
  • Insert a new person named ‘foo’ and a ‘friend’ relation with an existing person called ‘nice’

    INSERT Person X: X name 'foo', X friend  Y WHERE Y name 'nice'

2.2.11. Update and relation creation queries#

SET <assignements> [ WHERE <restriction>]

Caution, if a restriction is specified, the update is done for each result line returned by the restriction.

  • Renaming of the person named ‘foo’ to ‘bar’ with the first name changed

    SET X name 'bar', X firstname 'original' WHERE X is Person, X name 'foo'
  • Insert a relation of type ‘know’ between objects linked by the relation of type ‘friend’

    SET X know Y  WHERE X friend Y

2.2.12. Deletion query#

DELETE (<entity type> V) | (V1 relation v2 ),… [ WHERE <restriction>]

Caution, if a restriction is specified, the deletion is made for each line result returned by the restriction.

  • Deletion of the person named ‘foo’

    DELETE Person X WHERE X name 'foo'
  • Removal of all relations of type ‘friend’ from the person named ‘foo’

    DELETE X friend Y WHERE X is Person, X name 'foo'