Database Programming Languages 

Abstract: Gremlin is a graph traversal machine and language designed, developed, and distributed by the Apache TinkerPop project. Gremlin, as a graph traversal machine, is composed of three interacting components: a graph, a traversal, and a set of traversers. The traversers move about the graph according to the instructions specified in the traversal, where the result of the computation is the ultimate locations of all halted traversers. A Gremlin machine can be executed over any supporting graph computing system such as an OLTP graph database and/or an OLAP graph processor. Gremlin, as a graph traversal language, is a functional language implemented in the user's native programming language and is used to define the traversal of a Gremlin machine. This article provides a mathematical description of Gremlin and details its automaton and functional properties. These properties enable Gremlin to naturally support imperative and declarative querying, host language agnosticism, user-defined domain specific languages, an extensible compiler/optimizer, single- and multi-machine execution models, hybrid depth- and breadth-first evaluation, as well as the existence of a Universal Gremlin Machine and its respective entailments.

Abstract: Multidimensional databases are large collections of data, often historical, used for sophisticated analysis oriented to decision making. This activity is supported by an emerging category of software technology, called On-Line Analytical Processing (OLAP). In spite of a lot of commercial tools already available, a fundamental study for OLAP systems is still lacking. In this paper we introduce a model and a query language to establish a theoretical basis for multi-dimensional data. The model is based on the notions of dimension and f-table. Dimensions are linguistic categories corresponding to different ways of looking at the information. F-tables are the constructs used to represent factual data, and are the logical counterpart of multi-dimensional arrays, the way in which current analytical tools store data. The query language is a calculus for f-tables, and as such it offers a high-level support to multi-dimensional data analysis. Scalar and aggregate functions can be embedded in calculus expressions in a natural way. We discuss on conceptual problems related with the design of multidimensional query languages, and compare our model and language with other approaches.

Abstract: Many declarative query languages for object-oriented databases allow nested subqueries This paper contains the first (to our knowledge) proposal to optimize them A two-phase approach is used to optimize nested queries in the object-oriented context The first phase—called dependency-based optimization—transforms queries at the query language level in order to treat common subexpressions and independent subqueries more efficiently The transformed queries are translated to nested algebraic expressions These entail nested loop evaluation which may be very inefficient Hence, the second phase unnests nested algebraic expres­sions to allow for more efficient evaluation

Abstract: This paper shows how a semantic data model can be extended to become an object-oriented data model. The model is based on abstract entities, functions, types, and inheritance. The paper discusses issues that were considered in designing two query languages for this object-oriented model. Early languages for object-oriented data models were navigational and iterative, and did not support associative or set-oriented queries. Relational query languages, on the other hand, are purely associative and set-oriented. The languages we define here uniformly support the formulation of associative and navigational queries over objects, and also of queries that return individual objects as well as those that return aggregates (collections) of objects. One query language is an extension of DAPLEX; the other is algebraic. The algebra serves both to define the semantics of the higher level language, and also as the basis for query optimization. We illustrate how to map queries from the higher level language to the algebra. Finally, we discuss the special problems of defining views in object-oriented data models.