Development of Engineering Material and Heat Treatment Inquiry System based on VBA

Using VBA secondary development of AutoCAD,a kind of common engineering materials and heat treatment query system is designed,in which more than 400 kinds of commonly used materials were established based on the Access type of application and heat treatment database,recommend suitable material to designers to design and manufacture of a particular components.The system interface is concise,can be continuous,over and over again,no order query,can query to the characteristics of material usage and heat treatment process,as a CAD aided design software has positive design reference.

Word Segmentation Based on Database Semantics in NChiql

In this paper a novel word-segmentation algorithm is presented todelimit words in Chinese natural language queries in NChiql system, a Chinese natural language query interface to databases. Although there are sizable literatureson Chinese segmentation, they cannot satisfy particular requirements in this system. The novel word-segmentation algorithm is based on the database semantics,namely Semantic Conceptual Model (SCM) for specific domain knowledge. Basedon SCM, the segmenter labels the database semantics to words directly, which easesthe disambiguation and translation (from natural language to database query) inNChiql.

Banian: A Cross-Platform Interactive Query System for Structured Big Data

The rapid growth of structured data has presented new technological challenges in the research fields of big data and relational database. In this paper, we present an efficient system for managing and analyzing PB level structured data called Banian. Banian overcomes the storage structure limitation of relational database and effectively integrates interactive query with large-scale storage management. It provides a uniform query interface for cross-platform datasets and thus shows favorable compatibility and scalability. Banian＇s system architecture mainly includes three layers：（1） a storage layer using HDFS for the distributed storage of massive data;（2） a scheduling and execution layer employing the splitting and scheduling technology of parallel database; and（3）an application layer providing a cross-platform query interface and supporting standard SQL. We evaluate Banian using PB level Internet data and the TPC-H benchmark. The results show that when compared with Hive, Banian improves the query performance to a maximum of 30 times and achieves better scalability and concurrency.

An Efficient Algorithm for Processing Multi-Relation Queries in Relational Databases

After a relation scheme R is decomposed into the set of schemes ρ={R_1,...,R_n},we may pose queries as if R existed in the database,taking a join of R_i's,when it is necessary to implement the query.Suppose a query involves a set of attributes S(?)R,we want to find the smallest subset of ρ whose union includes S.We prove that the problem is NP-complete and present a polynomial-bounded approximation algorithm.A subset of ρ whose union includes S and has a decomposition into 3NF with a lossless join and preservation of dependencies is given in the paper.

Lom： Discovering Logic Flaws Within MongoDB-based Web Applications

Logic flaws within web applications will allow malicious operations to be triggered towards back-end database. Existing approaches to identifying logic flaws of database accesses are strongly tied to structured query language （SQL） statement construction and cannot be applied to the new generation of web applications that use not only structured query language （NoSQL） databases as the storage tier. In this paper, we present Lom, a black-box approach for discovering many categories of logic flaws within MongoDB- based web applications. Our approach introduces a MongoDB operation model to support new features of MongoDB and models the application logic as a mealy finite state machine. During the testing phase, test inputs which emulate state violation attacks are constructed for identifying logic flaws at each application state. We apply Lom to several MongoDB-based web applications and demonstrate its effectiveness.

Efficient Relational Techniques for Processing Graph Queries

Graphs are widely used for modeling complicated data such as social networks,chemical compounds,protein interactions and semantic web.To effiectively understand and utilize any collection of graphs,a graph database that efficiently supports elementary querying mechanisms is crucially required.For example,Subgraph and Supergraph queries are important types of graph queries which have many applications in practice.A primary challenge in computing the answers of graph queries is that pair-wise comparisons of graphs are usually hard problems.Relational database management systems（RDBMSs） have repeatedly been shown to be able to efficiently host different types of data such as complex objects and XML data.RDBMSs derive much of their performance from sophisticated optimizer components which make use of physical properties that are specific to the relational model such as sortedness,proper join ordering and powerful indexing mechanisms.In this article,we study the problem of indexing and querying graph databases using the relational infrastructure.We present a purely relational framework for processing graph queries.This framework relies on building a layer of graph features knowledge which capture metadata and summary features of the underlying graph database.We describe different querying mechanisms which make use of the layer of graph features knowledge to achieve scalable performance for processing graph queries.Finally,we conduct an extensive set of experiments on real and synthetic datasets to demonstrate the efficiency and the scalability of our techniques.