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9. SQL FUNDAMENTALS What Is SQL?
ROHINI COLLEGE OF ENGINEERING & TECHNOLOGY 9. SQL FUNDAMENTALS What is SQL? • SQL stands for Structured Query Language • SQL allows you to access a database • SQL is an ANSI standard computer language • SQL can execute queries against a database • SQL can retrieve data from a database • SQL can insert new records in a database • SQL can delete records from a database • SQL can update records in a database • SQL is easy to learn SQL is an ANSI (American National Standards Institute) standard computer language for accessing and manipulating database systems. SQL statements are used to retrieve and update data in a database. • SQL works with database programs like MS Access, DB2, Informix, MS SQL Server, Oracle, Sybase, etc. There are many different versions of the SQL language, but to be in compliance with the ANSI standard, they must support the same major keywords in a similar manner (such as SELECT, UPDATE, DELETE, INSERT, WHERE, and others). SQL Database Tables • A database most often contains one or more tables. Each table is identified by a name (e.g. "Customers" or "Orders"). Tables contain records (rows) with data. Below is an example of a table called "Persons": CS8492-DATABASE MANAGEMENT SYSTEMS ROHINI COLLEGE OF ENGINEERING & TECHNOLOGY SQL Language types: Structured Query Language(SQL) as we all know is the database language by the use of which we can perform certain operations on the existing database and also we can use this language to create a database. SQL uses certain commands like Create, Drop, Insert, etc. to carry out the required tasks. These SQL commands are mainly categorized into four categories as: 1. -
Chapter 11 Querying
Oracle TIGHT / Oracle Database 11g & MySQL 5.6 Developer Handbook / Michael McLaughlin / 885-8 Blind folio: 273 CHAPTER 11 Querying 273 11-ch11.indd 273 9/5/11 4:23:56 PM Oracle TIGHT / Oracle Database 11g & MySQL 5.6 Developer Handbook / Michael McLaughlin / 885-8 Oracle TIGHT / Oracle Database 11g & MySQL 5.6 Developer Handbook / Michael McLaughlin / 885-8 274 Oracle Database 11g & MySQL 5.6 Developer Handbook Chapter 11: Querying 275 he SQL SELECT statement lets you query data from the database. In many of the previous chapters, you’ve seen examples of queries. Queries support several different types of subqueries, such as nested queries that run independently or T correlated nested queries. Correlated nested queries run with a dependency on the outer or containing query. This chapter shows you how to work with column returns from queries and how to join tables into multiple table result sets. Result sets are like tables because they’re two-dimensional data sets. The data sets can be a subset of one table or a set of values from two or more tables. The SELECT list determines what’s returned from a query into a result set. The SELECT list is the set of columns and expressions returned by a SELECT statement. The SELECT list defines the record structure of the result set, which is the result set’s first dimension. The number of rows returned from the query defines the elements of a record structure list, which is the result set’s second dimension. You filter single tables to get subsets of a table, and you join tables into a larger result set to get a superset of any one table by returning a result set of the join between two or more tables. -
Using the Set Operators Questions
UUSSIINNGG TTHHEE SSEETT OOPPEERRAATTOORRSS QQUUEESSTTIIOONNSS http://www.tutorialspoint.com/sql_certificate/using_the_set_operators_questions.htm Copyright © tutorialspoint.com 1.Which SET operator does the following figure indicate? A. UNION B. UNION ALL C. INTERSECT D. MINUS Answer: A. Set operators are used to combine the results of two ormore SELECT statements.Valid set operators in Oracle 11g are UNION, UNION ALL, INTERSECT, and MINUS. When used with two SELECT statements, the UNION set operator returns the results of both queries.However,if there are any duplicates, they are removed, and the duplicated record is listed only once.To include duplicates in the results,use the UNION ALL set operator.INTERSECT lists only records that are returned by both queries; the MINUS set operator removes the second query's results from the output if they are also found in the first query's results. INTERSECT and MINUS set operations produce unduplicated results. 2.Which SET operator does the following figure indicate? A. UNION B. UNION ALL C. INTERSECT D. MINUS Answer: B. UNION ALL Returns the combined rows from two queries without sorting or removing duplicates. sql_certificate 3.Which SET operator does the following figure indicate? A. UNION B. UNION ALL C. INTERSECT D. MINUS Answer: C. INTERSECT Returns only the rows that occur in both queries' result sets, sorting them and removing duplicates. 4.Which SET operator does the following figure indicate? A. UNION B. UNION ALL C. INTERSECT D. MINUS Answer: D. MINUS Returns only the rows in the first result set that do not appear in the second result set, sorting them and removing duplicates. -
SQL Version Analysis
Rory McGann SQL Version Analysis Structured Query Language, or SQL, is a powerful tool for interacting with and utilizing databases through the use of relational algebra and calculus, allowing for efficient and effective manipulation and analysis of data within databases. There have been many revisions of SQL, some minor and others major, since its standardization by ANSI in 1986, and in this paper I will discuss several of the changes that led to improved usefulness of the language. In 1970, Dr. E. F. Codd published a paper in the Association of Computer Machinery titled A Relational Model of Data for Large shared Data Banks, which detailed a model for Relational database Management systems (RDBMS) [1]. In order to make use of this model, a language was needed to manage the data stored in these RDBMSs. In the early 1970’s SQL was developed by Donald Chamberlin and Raymond Boyce at IBM, accomplishing this goal. In 1986 SQL was standardized by the American National Standards Institute as SQL-86 and also by The International Organization for Standardization in 1987. The structure of SQL-86 was largely similar to SQL as we know it today with functionality being implemented though Data Manipulation Language (DML), which defines verbs such as select, insert into, update, and delete that are used to query or change the contents of a database. SQL-86 defined two ways to process a DML, direct processing where actual SQL commands are used, and embedded SQL where SQL statements are embedded within programs written in other languages. SQL-86 supported Cobol, Fortran, Pascal and PL/1. -
“A Relational Model of Data for Large Shared Data Banks”
“A RELATIONAL MODEL OF DATA FOR LARGE SHARED DATA BANKS” Through the internet, I find more information about Edgar F. Codd. He is a mathematician and computer scientist who laid the theoretical foundation for relational databases--the standard method by which information is organized in and retrieved from computers. In 1981, he received the A. M. Turing Award, the highest honor in the computer science field for his fundamental and continuing contributions to the theory and practice of database management systems. This paper is concerned with the application of elementary relation theory to systems which provide shared access to large banks of formatted data. It is divided into two sections. In section 1, a relational model of data is proposed as a basis for protecting users of formatted data systems from the potentially disruptive changes in data representation caused by growth in the data bank and changes in traffic. A normal form for the time-varying collection of relationships is introduced. In Section 2, certain operations on relations are discussed and applied to the problems of redundancy and consistency in the user's model. Relational model provides a means of describing data with its natural structure only--that is, without superimposing any additional structure for machine representation purposes. Accordingly, it provides a basis for a high level data language which will yield maximal independence between programs on the one hand and machine representation and organization of data on the other. A further advantage of the relational view is that it forms a sound basis for treating derivability, redundancy, and consistency of relations. -
Relational Algebra and SQL Relational Query Languages
Relational Algebra and SQL Chapter 5 1 Relational Query Languages • Languages for describing queries on a relational database • Structured Query Language (SQL) – Predominant application-level query language – Declarative • Relational Algebra – Intermediate language used within DBMS – Procedural 2 1 What is an Algebra? · A language based on operators and a domain of values · Operators map values taken from the domain into other domain values · Hence, an expression involving operators and arguments produces a value in the domain · When the domain is a set of all relations (and the operators are as described later), we get the relational algebra · We refer to the expression as a query and the value produced as the query result 3 Relational Algebra · Domain: set of relations · Basic operators: select, project, union, set difference, Cartesian product · Derived operators: set intersection, division, join · Procedural: Relational expression specifies query by describing an algorithm (the sequence in which operators are applied) for determining the result of an expression 4 2 The Role of Relational Algebra in a DBMS 5 Select Operator • Produce table containing subset of rows of argument table satisfying condition σ condition (relation) • Example: σ Person Hobby=‘stamps’(Person) Id Name Address Hobby Id Name Address Hobby 1123 John 123 Main stamps 1123 John 123 Main stamps 1123 John 123 Main coins 9876 Bart 5 Pine St stamps 5556 Mary 7 Lake Dr hiking 9876 Bart 5 Pine St stamps 6 3 Selection Condition • Operators: <, ≤, ≥, >, =, ≠ • Simple selection -
Uniform Data Access Platform for SQL and Nosql Database Systems
Information Systems 69 (2017) 93–105 Contents lists available at ScienceDirect Information Systems journal homepage: www.elsevier.com/locate/is Uniform data access platform for SQL and NoSQL database systems ∗ Ágnes Vathy-Fogarassy , Tamás Hugyák University of Pannonia, Department of Computer Science and Systems Technology, P.O.Box 158, Veszprém, H-8201 Hungary a r t i c l e i n f o a b s t r a c t Article history: Integration of data stored in heterogeneous database systems is a very challenging task and it may hide Received 8 August 2016 several difficulties. As NoSQL databases are growing in popularity, integration of different NoSQL systems Revised 1 March 2017 and interoperability of NoSQL systems with SQL databases become an increasingly important issue. In Accepted 18 April 2017 this paper, we propose a novel data integration methodology to query data individually from different Available online 4 May 2017 relational and NoSQL database systems. The suggested solution does not support joins and aggregates Keywords: across data sources; it only collects data from different separated database management systems accord- Uniform data access ing to the filtering options and migrates them. The proposed method is based on a metamodel approach Relational database management systems and it covers the structural, semantic and syntactic heterogeneities of source systems. To introduce the NoSQL database management systems applicability of the proposed methodology, we developed a web-based application, which convincingly MongoDB confirms the usefulness of the novel method. Data integration JSON ©2017 Elsevier Ltd. All rights reserved. 1. Introduction solution to retrieve data from heterogeneous source systems and to deliver them to the user. -
IEEE Paper Template in A4 (V1)
International Journal of Electrical Electronics & Computer Science Engineering Special Issue - NCSCT-2018 | E-ISSN : 2348-2273 | P-ISSN : 2454-1222 March, 2018 | Available Online at www.ijeecse.com Structural and Non-Structural Query Language Vinayak Sharma1, Saurav Kumar Jha2, Shaurya Ranjan3 CSE Department, Poornima Institute of Engineering and Technology, Jaipur, Rajasthan, India [email protected], [email protected], [email protected] Abstract: The Database system is rapidly increasing and it The most important categories are play an important role in all commercial-scientific software. In the current scenario every field work is related to DDL (Data Definition Language) computer they store their data in the database. Using DML (Data Manipulation Language) database helps to maintain the large records. This paper aims to summarize the different database and their usage in DQL (Data Query Language) IT field. In company database is more appropriate or more 1. Data Definition Language: Data Definition suitable to store the data. Language, DDL, is the subset of SQL that are used by a Keywords: DBS, Database Management Systems-DBMS, database user to create and built the database objects, Database-DB, Programming Language, Object-Oriented examples are deletion or the creation of a table. Some of System. the most Properties of DDL commands discussed I. INTRODUCTION below: CREATE TABLE The database system is used to develop the commercial- scientific application with database. The application DROP INDEX requires set of element for collection transmission, ALTER INDEX storage and processing of data with computer. Database CREATE VIEW system allow the database develop application. This ALTER TABLE paper deal with the features of Nosql and need of Nosql in the market. -
Best Practices Managing XML Data
® IBM® DB2® for Linux®, UNIX®, and Windows® Best Practices Managing XML Data Matthias Nicola IBM Silicon Valley Lab Susanne Englert IBM Silicon Valley Lab Last updated: January 2011 Managing XML Data Page 2 Executive summary ............................................................................................. 4 Why XML .............................................................................................................. 5 Pros and cons of XML and relational data ................................................. 5 XML solutions to relational data model problems.................................... 6 Benefits of DB2 pureXML over alternative storage options .................... 8 Best practices for DB2 pureXML: Overview .................................................. 10 Sample scenario: derivative trades in FpML format............................... 11 Sample data and tables................................................................................ 11 Choosing the right storage options for XML data......................................... 16 Selecting table space type and page size for XML data.......................... 16 Different table spaces and page size for XML and relational data ....... 16 Inlining and compression of XML data .................................................... 17 Guidelines for adding XML data to a DB2 database .................................... 20 Inserting XML documents with high performance ................................ 20 Splitting large XML documents into smaller pieces .............................. -
Chapter 2 – Object-Relational Views and Composite Types Outline
Prof. Dr.-Ing. Stefan Deßloch AG Heterogene Informationssysteme Geb. 36, Raum 329 Tel. 0631/205 3275 [email protected] Chapter 2 – Object-Relational Views and Composite Types Recent Developments for Data Models Outline Overview I. Object-Relational Database Concepts 1. User-defined Data Types and Typed Tables 2. Object-relational Views and Composite Types 3. User-defined Routines and Object Behavior 4. Application Programs and Object-relational Capabilities 5. Object-relational SQL and Java II. Online Analytic Processing 6. Data Analysis in SQL 7. Windows and Query Functions in SQL III. XML 8. XML and Databases 9. SQL/XML 10. XQuery IV. More Developments (if there is time left) temporal data models, data streams, databases and uncertainty, … 2 © Prof.Dr.-Ing. Stefan Deßloch Recent Developments for Data Models 1 The "Big Picture" Client DB Server Server-side dynamic SQL Logic SQL99/2003 JDBC 2.0 SQL92 static SQL SQL OLB stored procedures ANSI SQLJ Part 1 user-defined functions SQL Routines ISO advanced datatypes PSM structured types External Routines subtyping methods SQLJ Part 2 3 © Prof.Dr.-Ing. Stefan Deßloch Recent Developments for Data Models Objects Meet Databases (Atkinson et. al.) Object-oriented features to be supported by an (OO)DBMS ; Extensibility user-defined types (structure and operations) as first class citizens strengthens some capabilities defined above (encapsulation, types) ; Object identity object exists independent of its value (i.e., identical ≠ equal) ; Types and classes "abstract data types", static type checking class as an "object factory", extension (i.e., set of "instances") ? Type or class and view hierarchies inheritance, specialization ? Complex objects type constructors: tuple, set, list, array, … Encapsulation separate specification (interface) from implementation Overloading, overriding, late binding same name for different operations or implementations Computational completeness use DML to express any computable function (-> method implementation) 4 © Prof.Dr.-Ing. -
IVOA Astronomical Data Query Language Version
International Virtual Observatory Alliance IVOA Astronomical Data Query Language Version 2.0 IVOA Recommendation 30 Oct 2008 This version: 2.0 Latest version: http://www.ivoa.net/Documents/latest/ADQL.html Previous version(s): 2.0-20081028 Editor(s): Pedro Osuna and Inaki Ortiz Author(s): Inaki Ortiz, Jeff Lusted, Pat Dowler, Alexander Szalay, Yuji Shirasaki, Maria A. Nieto- Santisteban, Masatoshi Ohishi, William O’Mullane, Pedro Osuna, the VOQL-TEG and the VOQL Working Group. Abstract This document describes the Astronomical Data Query Language (ADQL). ADQL has been developed based on SQL92. This document describes the subset of the SQL grammar supported by ADQL. Special restrictions and extensions to SQL92 have been defined in order to support generic and astronomy specific operations. 1 Status of This Document This document has been produced by the VO Query Language Working Group. It has been reviewed by IVOA Members and other interested parties, and has been endorsed by the IVOA Executive Committee as an IVOA Recommendation. It is a stable document and may be used as reference material or cited as a normative reference from another document. IVOA's role in making the Recommendation is to draw attention to the specification and to promote its widespread deployment. This enhances the functionality and interoperability inside the Astronomical Community. Please note that version 1.0 was never promoted to Proposed Recommendation. A list of current IVOA Recommendations and other technical documents can be found at http://www.ivoa.net/Documents/. -
On the Logic of SQL Nulls
On the Logic of SQL Nulls Enrico Franconi and Sergio Tessaris Free University of Bozen-Bolzano, Italy lastname @inf.unibz.it Abstract The logic of nulls in databases has been subject of invest- igation since their introduction in Codd's Relational Model, which is the foundation of the SQL standard. In the logic based approaches to modelling relational databases proposed so far, nulls are considered as representing unknown values. Such existential semantics fails to capture the behaviour of the SQL standard. We show that, according to Codd's Relational Model, a SQL null value represents a non-existing value; as a consequence no indeterminacy is introduced by SQL null values. In this paper we introduce an extension of first-order logic accounting for predicates with missing arguments. We show that the domain inde- pendent fragment of this logic is equivalent to Codd's relational algebra with SQL nulls. Moreover, we prove a faithful encoding of the logic into standard first-order logic, so that we can employ classical deduction ma- chinery. 1 Relational Databases and SQL Null Values Consider a database instance with null values over the relational schema fR=2g, and a SQL query asking for the tuples in R being equal to themselves: 1 2 1 | 2 SELECT * FROM R ---+--- R : a b WHERE R.1 = R.1 AND R.2 = R.2 ; ) a | b b N (1 row) Figure 1. In SQL, the query above returns the table R if and only if the table R does not have any null value, otherwise it returns just the tuples not containing a null value, i.e., in this case only the first tuple ha; bi.