SQL language

The data model is highly normalised, which suits data integrity and manipulation via the SQL language, but creates difficulties for the end-user in terms of accessing the data. Straightforward queries may involve numerous tables which have to be joined together. As a practical work-around, the database includes several very large denormalized tables. 

Data Cartridge. A popular term for user-customizable search "operators" that can be added to the SQL language of a relational database system. An example in chemical information is the addition of a substructure search (SSS) operator to integrate this type of search directly into a relational database search. One advantage of this approach is that the search "strategy" that the relational search program applies can take the complexity of the custom operator into account (the "cost") when performing the various search operations. 

Schema evolution primitives in the SQL language and in commercial DBMS are atomic in nature. Unless there is a proprietary extension to the language, each statement describes a simple change to a schema. For instance, individual tables may be added or dropped, individual columns may be added or dropped from a table, and individual constraints may be added or dropped. Additionally, individual properties of a single object may be changed so, one can rename a column, table, or constraint one can change individual properties of columns, such as their maximum length or precision and one can change the data type of a column under the condition that the conversion of data from the old type to the new type can be done implicitly.

The tables are formally called relations, referring to the mathematical set theory used in the original work on relational databases.1 In database theory, rows are called tuples and columns are called attributes of a tuple. The focus of this book is practical, so the common terms table, row, and column are used. The detail of using the SQL language to perform these operations is left to a later chapter of this book. 

In Chapter 2, the concept of relational tables was introduced. In this chapter, the most common way of working with tables in an RDBMS is introduced. The SQL language provides ways to create tables, insert data, select data, delete data, update data, join tables, create table schemas, define functions, etc. SQL has many other features, not all of which are covered here. 

Many other uses of the xform function are possible. Because the function is an extension of SQL, it can be easily used with all the other features of the SQL language and capabilities of an RDBMS. 

Creating a function in plpgsql is done in a way similar to the previous examples using the SQL language. The following function creation shows some of the useful features of plpgsql and differences from the SQL language. 

Another important aspect of objects is the methods that operate on them. An ORDBMS calls these functions, but the effect is the same. As shown in this chapter, the functions defined for new data types enable them to be integrated in the SQL language and handled just like standard SQL data types. This can be by casting the data type, for example, to allow range data to be treated as float. New functions that operate exclusively on range data can be defined, such as range cmp. The ability to define operators of new data types enhances their usability and integration into SQL even more. 

In this paper, we advocate an approach to the integration problem in which an RDBMS based on the SQL language is extended to encompass chemical structure and other complex data types. This approach integrates all data normally stored separately in a CDBMS and RDBMS into a single extended RDBMS. The resulting system provides a single uniform data model and data manipulation language that can be applied to chemical structures and associated data simultaneously. The... 

Among many approaches to manipulating a relational database, the most prevalent one is a language called SQL (Structured Query Language) [2]. 

Another important feature of a LIMS DBMS is the abiUty to perform ad hoc database queries. It is impossible to predict all the forms in which LIMS users will want to display their data while the LIMS is being designed. As a result, it is desirable to select a LIMS which allows users to define their own reports. Most commercial DBMS have a standard query language (SQL) interface. SQL is a simple database query tool which is based on... 

English-language commands. This sample SQL query says, "Give me all sample request data containing John Smith as the customer."... 

Most clinical data management systems used for clinical trials today store their data in relational database software such as Oracle or Microsoft SQL Server. A relational database is composed of a set of rectangular data matrices called tables that relate or associate with one another by certain key fields. The language most often used to work with relational databases is structured query language (SQL). The SAS/ACCESS SQL Pass-Through Facility and the SAS/ACCESS LIBNAME engine are the two methods that SAS provides for extracting data from relational databases. 

The examples in this book focus primarily on the tools within SAS/GRAPH, SAS/STAT, and Base SAS, including the SAS macro language and PROC SQL. The examples were developed using SAS 9.1.3, but the vast majority of the examples will run with other versions of SAS as well. Please note that the data that drive the examples in this book are obtained through INPUT statements with DATALINES data. This is done only for illustrative purposes and does not mean that you should expect to obtain your clinical data in this fashion. 

Query languages include declarative access and querying using SQL. 

Both the nucleic acid sequences and the protein sequences derived from the biological information are collected in most such databases. Large amounts of data in these databases need to be sorted, stored, retrieved, and analyzed. Selection of subsets of data for particular analysis should also be done. IT providers designed such a data warehouse and developed an interface that provides an important benefit to researchers by making it easy to access the existing information and also to submit new entries (i.e., datamining) (Table 5.6). Middlewares and structured query language (SQL) softwares were developed for this purposes. The former one is used... 

The Microsoft Access database (http //www.microsoft.com/) is a collection of data and objects related to a particular topic (Hutchinson and Giddeon, 2000). The data represent the information stored in the database, and the objects help users define the structure of that information and automate the data manipulating tasks. Access supports SQL (Structured Query Language) to create, modify, and manipulate records in the table to facilitate the process. It is a table-oriented processing. The user is referred to the Microsoft Access User s Guide or online Help for information. 

There is no limit on the size of XML data. Many database vendors have implemented XML support to their products. A new and very powerful language for querying XML databases—XQuery (Boag et al. 2007)—has been adopted and for many tasks, and this language can be more expressive than SQL. XML databases are often implemented on top of established relational ones, so performance is not a problem. 

Traditionally data, properties, information etc has been stored in files on computer disks. More recently, it has become common practice on Macintosh computers, when using Microsoft software or some UNIX applications, to use either extensions to the file name or the first few bytes in the file (or another file) to indicate some aspects of the data, for example that it is suitable for Microsoft Excel. While this approach is practical to indicate something about files containing columns of data, it is not appropriate to store information about the values in cells in spreadsheet or how it relates to data in other columns. This requires a relational database such as ORACLE, and for performance reasons the values in the cells may only be accessed via the ORACLE API (Application Programming Interface) or SQL (Standard Query Language), in other words, it is suggested that relational databases such as ORACLE should be viewed as sophisticated file systems which allow the values to be organised, efficiently stored, rapidly retrieved etc. 

---