doc/book/annexes/rql/intro.rst
author Philippe Pepiot <philippe.pepiot@logilab.fr>
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.. _rql_intro:
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Introduction
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------------
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Goals of RQL
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~~~~~~~~~~~~
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The goal is to have a semantic language in order to:
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- query relations in a clear syntax
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- empowers access to data repository manipulation
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- making attributes/relations browsing easy
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As such, attributes will be regarded as cases of special relations (in
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terms of usage, the user should see no syntactic difference between an
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attribute and a relation).
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Comparison with existing languages
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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SQL
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```
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RQL may remind of SQL but works at a higher abstraction level (the *CubicWeb*
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framework generates SQL from RQL to fetch data from relation databases). RQL is
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focused on browsing relations. The user needs only to know about the *CubicWeb*
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data model he is querying, but not about the underlying SQL model.
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Sparql
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``````
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The query language most similar to RQL is SPARQL_, defined by the W3C to serve
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for the semantic web.
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Versa
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`````
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We should look in more detail, but here are already some ideas for the moment
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... Versa_ is the language most similar to what we wanted to do, but the model
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underlying data being RDF, there are some things such as namespaces or
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handling of the RDF types which does not interest us. On the functionality
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level, Versa_ is very comprehensive including through many functions of
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conversion and basic types manipulation, which we may want to look at one time
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or another.  Finally, the syntax is a little esoteric.
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Datalog
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```````
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Datalog_ is a prolog derived query langage which applies to relational
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databases. It is more expressive than RQL in that it accepts either
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extensional_ and intensional_ predicates (or relations). As of now,
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RQL only deals with intensional relations.
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The different types of queries
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Search (`Any`)
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   Extract entities and attributes of entities.
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Insert entities (`INSERT`)
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   Insert new entities or relations in the database.
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   It can also directly create relationships for the newly created entities.
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Update entities, create relations (`SET`)
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   Update existing entities in the database,
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   or create relations between existing entities.
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Delete entities or relationship (`DELETE`)
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   Remove entities or relations existing in the database.
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RQL relation expressions
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~~~~~~~~~~~~~~~~~~~~~~~~
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RQL expressions apply to a live database defined by a
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:ref:`datamodel_definition`. Apart from the main type, or head, of the
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expression (search, insert, etc.) the most common constituent of an
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RQL expression is a (set of) relation expression(s).
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An RQL relation expression contains three components:
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* the subject, which is an entity type
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* the predicate, which is a relation definition (an arc of the schema)
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* the object, which is either an attribute or a relation to another entity
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.. image:: Graph-ex.gif
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    :alt: <subject> <predicate> <object>
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    :align: center
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.. warning::
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 A relation is always expressed in the order: ``subject``,
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 ``predicate``, ``object``.
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 It is important to determine if the entity type is subject or object
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 to construct a valid expression. Inverting the subject/object is an
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 error since the relation cannot be found in the schema.
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 If one does not have access to the code, one can find the order by
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 looking at the schema image in manager views (the subject is located
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 at the beginning of the arrow).
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An example of two related relation expressions::
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  P works_for C, P name N
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RQL variables represent typed entities. The type of entities is
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either automatically inferred (by looking at the possible relation
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definitions, see :ref:`RelationDefinition`) or explicitely constrained
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using the ``is`` meta relation.
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In the example above, we barely need to look at the schema. If
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variable names (in the RQL expression) and relation type names (in the
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schema) are expresssively designed, the human reader can infer as much
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as the |cubicweb| querier.
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The ``P`` variable is used twice but it always represent the same set
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of entities. Hence ``P works_for C`` and ``P name N`` must be
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compatible in the sense that all the Ps (which *can* refer to
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different entity types) must accept the ``works_for`` and ``name``
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relation types. This does restrict the set of possible values of P.
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Adding another relation expression::
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  P works_for C, P name N, C name "logilab"
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This further restricts the possible values of P through an indirect
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constraint on the possible values of ``C``. The RQL-level unification_
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happening there is translated to one (or several) joins_ at the
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database level.
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.. note::
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 In |cubicweb|, the term `relation` is often found without ambiguity
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 instead of `predicate`.  This predicate is also known as the
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 `property` of the triple in `RDF concepts`_
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RQL Operators
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~~~~~~~~~~~~~
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An RQL expression's head can be completed using various operators such
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as ``ORDERBY``, ``GROUPBY``, ``HAVING``, ``LIMIT`` etc.
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RQL relation expressions can be grouped with ``UNION`` or
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``WITH``. Predicate oriented keywords such as ``EXISTS``, ``OR``,
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``NOT`` are available.
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The complete zoo of RQL operators is described extensively in the
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following chapter (:ref:`RQL`).
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.. _RDF concepts: http://www.w3.org/TR/rdf-concepts/
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.. _Versa: http://wiki.xml3k.org/Versa
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.. _SPARQL: http://www.w3.org/TR/rdf-sparql-query/
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.. _unification: http://en.wikipedia.org/wiki/Unification_(computing)
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.. _joins: http://en.wikipedia.org/wiki/Join_(SQL)
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.. _Datalog: http://en.wikipedia.org/wiki/Datalog
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.. _intensional: http://en.wikipedia.org/wiki/Intensional_definition
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.. _extensional: http://en.wikipedia.org/wiki/Extension_(predicate_logic)
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