. , 46 3.5.2 SQL implementation for computing contingency table

. .. Prms,

. .. Conclusion,

. .. Experiments,

. .. Conclusion,

. .. Summary,

, A.3.1 Existing libraries

, Its implementation follows a generic programming principle and its source can be found as part of the Boost distribution 4. BGL is characterized by its easy of use and integration in any program: no need to be built to be used, wealth of documentation and multiple code examples. It consists of a set of core algorithm patterns, namely, Breadth First Search, Depth First Search and Uniform Cost Search, and a set set of graph algorithms, The Boost Graph Library (BGL): is a C++ open source library that provides a generic open interface for traversing graphs

, It also allows to perform more other requests such as creating schemas, tables, constraints, etc. dtl is well documented and a variety of examples are given and commented. Moreover, instructions for using the library are provided and precision on how to use it with each DBMS is given 5. Googletest: Released under the BSD 3-clause license 6 , Google Test presents a library for writing C++ unit tests. It works on a variety of platforms and can be easily integrated to any c++ program. The library allows several test types and several options for running the tests 7, Database Template Library (dtl): dtl is a C++ open source library. The specificity of this library is that it can run on multiple platforms and C++ compilers

, A.3.2 Additional libraries

. Cpprest and . Casablanca, This Microsoft open source project is evolving in CodePlex 8 and takes advantage of the new set of capabilities introduced in C++. Microsoft developed the C++ REST SDK on top of the Parallel Patterns Library (PPL), and leverages PPL's task-based programming model. It enables you to stay in C++ when consuming REST services or developing other code closely related to the cloud. Such as, making calls to a synchronous API to make an HTTP GET call

, a text file) is used. For relational probabilistic models, relational data representation is needed. For the second case, the PostgreSQL Relational database management system has been used. Accordingly, to our contribution; learning RBN from graph database so we added Neo4j as graph database management system to deal with. PostgreSQL: is an open-source object-relational database management system. Initially created at the University of California at Berkeley, PostgreSQL is now considered among the most advanced open-source database. It supports a large part of the SQL standard and provides the possibility to be used, modified, and distributed by anyone free of charge for any purpose, structure learning) involve datasets as input. For standard probabilistic models, flat data representation

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