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ACS-3902 Ron Mcfadyen Slides Are Based on Chapter 5 (7Th Edition)
ACS-3902 Ron McFadyen Slides are based on chapter 5 (7th edition) (chapter 3 in 6th edition) ACS-3902 1 The Relational Data Model and Relational Database Constraints • Relational model – Ted Codd (IBM) 1970 – First commercial implementations available in early 1980s – Widely used ACS-3902 2 Relational Model Concepts • Database is a collection of relations • Implementation of relation: table comprising rows and columns • In practice a table/relation represents an entity type or relationship type (entity-relationship model … later) • At intersection of a row and column in a table there is a simple value • Row • Represents a collection of related data values • Formally called a tuple • Column names • Columns may be referred to as fields, or, formally as attributes • Values in a column are drawn from a domain of values associated with the column/field/attribute ACS-3902 3 Relational Model Concepts 7th edition Figure 5.1 ACS-3902 4 Domains • Domain – Atomic • A domain is a collection of values where each value is indivisible • Not meaningful to decompose further – Specifying a domain • Name, data type, rules – Examples • domain of department codes for UW is a list: {“ACS”, “MATH”, “ENGL”, “HIST”, etc} • domain of gender values for UW is the list (“male”, “female”) – Cardinality: number of values in a domain – Database implementation & support vary ACS-3902 5 Domain example - PostgreSQL CREATE DOMAIN posint AS integer CHECK (VALUE > 0); CREATE TABLE mytable (id posint); INSERT INTO mytable VALUES(1); -- works INSERT INTO mytable VALUES(-1); -- fails https://www.postgresql.org/docs/current/domains.html ACS-3902 6 Domain example - PostgreSQL CREATE DOMAIN domain_code_type AS character varying NOT NULL CONSTRAINT domain_code_type_check CHECK (VALUE IN ('ApprovedByAdmin', 'Unapproved', 'ApprovedByEmail')); CREATE TABLE codes__domain ( code_id integer NOT NULL, code_type domain_code_type NOT NULL, CONSTRAINT codes_domain_pk PRIMARY KEY (code_id) ) ACS-3902 7 Relation • Relation schema R – Name R and a list of attributes: • Denoted by R (A1, A2, ...,An) • E.g. -
Referential Integrity in Sqlite
CS 564: Database Management Systems University of Wisconsin - Madison, Fall 2017 Referential Integrity in SQLite Declaring Referential Integrity (Foreign Key) Constraints Foreign key constraints are used to check referential integrity between tables in a database. Consider, for example, the following two tables: create table Residence ( nameVARCHARPRIMARY KEY, capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR ); We can enforce the constraint that a Student’s residence actually exists by making Student.residence a foreign key that refers to Residence.name. SQLite lets you specify this relationship in several different ways: create table Residence ( nameVARCHARPRIMARY KEY, capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR, FOREIGNKEY(residence) REFERENCES Residence(name) ); or create table Residence ( nameVARCHARPRIMARY KEY, capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR REFERENCES Residence(name) ); or create table Residence ( nameVARCHARPRIMARY KEY, 1 capacityINT ); create table Student ( idINTPRIMARY KEY, firstNameVARCHAR, lastNameVARCHAR, residenceVARCHAR REFERENCES Residence-- Implicitly references the primary key of the Residence table. ); All three forms are valid syntax for specifying the same constraint. Constraint Enforcement There are a number of important things about how referential integrity and foreign keys are handled in SQLite: • The attribute(s) referenced by a foreign key constraint (i.e. Residence.name in the example above) must be declared UNIQUE or as the PRIMARY KEY within their table, but this requirement is checked at run-time, not when constraints are declared. For example, if Residence.name had not been declared as the PRIMARY KEY of its table (or as UNIQUE), the FOREIGN KEY declarations above would still be permitted, but inserting into the Student table would always yield an error. -
Let's Talk About Storage & Recovery Methods for Non-Volatile Memory
Let’s Talk About Storage & Recovery Methods for Non-Volatile Memory Database Systems Joy Arulraj Andrew Pavlo Subramanya R. Dulloor [email protected] [email protected] [email protected] Carnegie Mellon University Carnegie Mellon University Intel Labs ABSTRACT of power, the DBMS must write that data to a non-volatile device, The advent of non-volatile memory (NVM) will fundamentally such as a SSD or HDD. Such devices only support slow, bulk data change the dichotomy between memory and durable storage in transfers as blocks. Contrast this with volatile DRAM, where a database management systems (DBMSs). These new NVM devices DBMS can quickly read and write a single byte from these devices, are almost as fast as DRAM, but all writes to it are potentially but all data is lost once power is lost. persistent even after power loss. Existing DBMSs are unable to take In addition, there are inherent physical limitations that prevent full advantage of this technology because their internal architectures DRAM from scaling to capacities beyond today’s levels [46]. Using are predicated on the assumption that memory is volatile. With a large amount of DRAM also consumes a lot of energy since it NVM, many of the components of legacy DBMSs are unnecessary requires periodic refreshing to preserve data even if it is not actively and will degrade the performance of data intensive applications. used. Studies have shown that DRAM consumes about 40% of the To better understand these issues, we implemented three engines overall power consumed by a server [42]. in a modular DBMS testbed that are based on different storage Although flash-based SSDs have better storage capacities and use management architectures: (1) in-place updates, (2) copy-on-write less energy than DRAM, they have other issues that make them less updates, and (3) log-structured updates. -
Failures in DBMS
Chapter 11 Database Recovery 1 Failures in DBMS Two common kinds of failures StSystem filfailure (t)(e.g. power outage) ‒ affects all transactions currently in progress but does not physically damage the data (soft crash) Media failures (e.g. Head crash on the disk) ‒ damagg()e to the database (hard crash) ‒ need backup data Recoveryyp scheme responsible for handling failures and restoring database to consistent state 2 Recovery Recovering the database itself Recovery algorithm has two parts ‒ Actions taken during normal operation to ensure system can recover from failure (e.g., backup, log file) ‒ Actions taken after a failure to restore database to consistent state We will discuss (briefly) ‒ Transactions/Transaction recovery ‒ System Recovery 3 Transactions A database is updated by processing transactions that result in changes to one or more records. A user’s program may carry out many operations on the data retrieved from the database, but the DBMS is only concerned with data read/written from/to the database. The DBMS’s abstract view of a user program is a sequence of transactions (reads and writes). To understand database recovery, we must first understand the concept of transaction integrity. 4 Transactions A transaction is considered a logical unit of work ‒ START Statement: BEGIN TRANSACTION ‒ END Statement: COMMIT ‒ Execution errors: ROLLBACK Assume we want to transfer $100 from one bank (A) account to another (B): UPDATE Account_A SET Balance= Balance -100; UPDATE Account_B SET Balance= Balance +100; We want these two operations to appear as a single atomic action 5 Transactions We want these two operations to appear as a single atomic action ‒ To avoid inconsistent states of the database in-between the two updates ‒ And obviously we cannot allow the first UPDATE to be executed and the second not or vice versa. -
Database Systems Administrator FLSA: Exempt
CLOVIS UNIFIED SCHOOL DISTRICT POSITION DESCRIPTION Position: Database Systems Administrator FLSA: Exempt Department/Site: Technology Services Salary Grade: 127 Reports to/Evaluated by: Chief Technology Officer Salary Schedule: Classified Management SUMMARY Gathers requirements and provisions servers to meet the district’s need for database storage. Installs and configures SQL Server according to the specifications of outside software vendors and/or the development group. Designs and executes a security scheme to assure safety of confidential data. Implements and manages a backup and disaster recovery plan. Monitors the health and performance of database servers and database applications. Troubleshoots database application performance issues. Automates monitoring and maintenance tasks. Maintains service pack deployment and upgrades servers in consultation with the developer group and outside vendors. Deploys and schedules SQL Server Agent tasks. Implements and manages replication topologies. Designs and deploys datamarts under the supervision of the developer group. Deploys and manages cubes for SSAS implementations. DISTINGUISHING CAREER FEATURES The Database Systems Administrator is a senior level analyst position requiring specialized education and training in the field of study typically resulting in a degree. Advancement to this position would require competency in the design and administration of relational databases designated for business, enterprise, and student information. Advancement from this position is limited to supervisory management positions. ESSENTIAL DUTIES AND RESPONSIBILITIES Implements, maintains and administers all district supported versions of Microsoft SQL as well as other DBMS as needed. Responsible for database capacity planning and involvement in server capacity planning. Responsible for verification of backups and restoration of production and test databases. Designs, implements and maintains a disaster recovery plan for critical data resources. -
What Is Nosql? the Only Thing That All Nosql Solutions Providers Generally Agree on Is That the Term “Nosql” Isn’T Perfect, but It Is Catchy
NoSQL GREG SYSADMINBURD Greg Burd is a Developer Choosing between databases used to boil down to examining the differences Advocate for Basho between the available commercial and open source relational databases . The term Technologies, makers of Riak. “database” had become synonymous with SQL, and for a while not much else came Before Basho, Greg spent close to being a viable solution for data storage . But recently there has been a shift nearly ten years as the product manager for in the database landscape . When considering options for data storage, there is a Berkeley DB at Sleepycat Software and then new game in town: NoSQL databases . In this article I’ll introduce this new cat- at Oracle. Previously, Greg worked for NeXT egory of databases, examine where they came from and what they are good for, and Computer, Sun Microsystems, and KnowNow. help you understand whether you, too, should be considering a NoSQL solution in Greg has long been an avid supporter of open place of, or in addition to, your RDBMS database . source software. [email protected] What Is NoSQL? The only thing that all NoSQL solutions providers generally agree on is that the term “NoSQL” isn’t perfect, but it is catchy . Most agree that the “no” stands for “not only”—an admission that the goal is not to reject SQL but, rather, to compensate for the technical limitations shared by the majority of relational database implemen- tations . In fact, NoSQL is more a rejection of a particular software and hardware architecture for databases than of any single technology, language, or product . -
Oracle Nosql Database
An Oracle White Paper November 2012 Oracle NoSQL Database Oracle NoSQL Database Table of Contents Introduction ........................................................................................ 2 Technical Overview ............................................................................ 4 Data Model ..................................................................................... 4 API ................................................................................................. 5 Create, Remove, Update, and Delete..................................................... 5 Iteration ................................................................................................... 6 Bulk Operation API ................................................................................. 7 Administration .................................................................................... 7 Architecture ........................................................................................ 8 Implementation ................................................................................... 9 Storage Nodes ............................................................................... 9 Client Driver ................................................................................. 10 Performance ..................................................................................... 11 Conclusion ....................................................................................... 12 1 Oracle NoSQL Database Introduction NoSQL databases -
The Relational Data Model and Relational Database Constraints
chapter 33 The Relational Data Model and Relational Database Constraints his chapter opens Part 2 of the book, which covers Trelational databases. The relational data model was first introduced by Ted Codd of IBM Research in 1970 in a classic paper (Codd 1970), and it attracted immediate attention due to its simplicity and mathematical foundation. The model uses the concept of a mathematical relation—which looks somewhat like a table of values—as its basic building block, and has its theoretical basis in set theory and first-order predicate logic. In this chapter we discuss the basic characteristics of the model and its constraints. The first commercial implementations of the relational model became available in the early 1980s, such as the SQL/DS system on the MVS operating system by IBM and the Oracle DBMS. Since then, the model has been implemented in a large num- ber of commercial systems. Current popular relational DBMSs (RDBMSs) include DB2 and Informix Dynamic Server (from IBM), Oracle and Rdb (from Oracle), Sybase DBMS (from Sybase) and SQLServer and Access (from Microsoft). In addi- tion, several open source systems, such as MySQL and PostgreSQL, are available. Because of the importance of the relational model, all of Part 2 is devoted to this model and some of the languages associated with it. In Chapters 4 and 5, we describe the SQL query language, which is the standard for commercial relational DBMSs. Chapter 6 covers the operations of the relational algebra and introduces the relational calculus—these are two formal languages associated with the relational model. -
The Integration of Database Systems
Purdue University Purdue e-Pubs Department of Computer Science Technical Reports Department of Computer Science 1993 The Integration of Database Systems Tony Schaller Omran A. Bukhres Ahmed K. Elmagarmid Purdue University, [email protected] Xiangning Liu Report Number: 93-046 Schaller, Tony; Bukhres, Omran A.; Elmagarmid, Ahmed K.; and Liu, Xiangning, "The Integration of Database Systems" (1993). Department of Computer Science Technical Reports. Paper 1061. https://docs.lib.purdue.edu/cstech/1061 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. The Integration of Database Systems Tony Schaller, Omran A. Bukhres, Ahmed K. Elmagarmid and Xiangning Liu CSD-TR-93-046 July 1993 I I The Integration of Database Systems Tony Schaller Molecular Design Ltd. 2132 Farallon Drive San Leandro, CA 94577 Omran A. Bukhres, Ahmed K. Elmagarmid and Xiangning Liu DeparLment of Computer Sciences Purdue University West Lafayette, IN 47907 eJIlail: {bukhres,ake,xl} .es.purdue.edu 1 Introduction A database system is composed of two elements: a software program, called a database management system, and a set of data, called a database. The data in a database is organized according to some data model, such as the relational model used in a DB2 database [DW88] or the hierarchical model found with IMS databases [Dat77] . Users access the data through an interface (the query language) provided by the database management system. A schema describes the actual data structures and organization within the system. During the decade ofthe nineteen-seventies, centralized databases were predominant, but recent innovations in communications and database technologies have engendered a revolution in data processing, giving rlse to a new generation of decentralized database systems. -
High-Performance Transaction Processing in SAP HANA
High-Performance Transaction Processing in SAP HANA Juchang Lee1, Michael Muehle1, Norman May1, Franz Faerber1, Vishal Sikka1, Hasso Plattner2, Jens Krueger2, Martin Grund3 1SAP AG 2Hasso Plattner Insitute, Potsdam, Germany, 3eXascale Infolab, University of Fribourg, Switzerland Abstract Modern enterprise applications are currently undergoing a complete paradigm shift away from tradi- tional transactional processing to combined analytical and transactional processing. This challenge of combining two opposing query types in a single database management system results in additional re- quirements for transaction management as well. In this paper, we discuss our approach to achieve high throughput for transactional query processing while allowing concurrent analytical queries. We present our approach to distributed snapshot isolation and optimized two-phase commit protocols. 1 Introduction An efficient and holistic data management infrastructure is one of the key requirements for making the right deci- sions at an operational, tactical, and strategic level and is core to support all kinds of enterprise applications[12]. In contrast to traditional architectures of database systems, the SAP HANA database takes a different approach to provide support for a wide range of data management tasks. The system is organized in a main-memory centric fashion to reflect the shift within the memory hierarchy[2] and to consistently provide high perfor- mance without prohibitively slow disk interactions. Completely transparent for the application, data is orga- nized along its life cycle either in column or row format, providing the best performance for different workload characteristics[11, 1]. Transactional workloads with a high update rate and point queries can be routed against a row store; analytical workloads with range scans over large datasets are supported by column oriented data struc- tures. -
Clarion & ANSI SQL Standard Referential Integrity and Referential
Clarion & ANSI SQL Standard Referential Integrity and Referential Actions November 12, 2018 Whitemarsh Information Systems Corporation 2008 Althea Lane Bowie, Maryland 20716 Tele: 301-249-1142 Email: [email protected] Web: www.wiscorp.com Referential Integrity and Referential Actions Fundamental Definition: Actions resulting from instruction to the database engine created in the dictionary (i.e., schema) associated with “Relationship” specifications. For SQL-engine DBMSs, these relationship-specifications and actions relate to value congruence between the value-set of a primary key’s column(s) and the value-set of a Foreign key’s column(s). When either a Update or Delete action occurs that violates the value congruence, a Referential Action occurs. The actions depend on whether the Referential Action is specified. In ANSI SQL Standards, the four referential integrity actions: No Action, Cascade, or Set Null or Set Default. In Clarion, the five referential integrity actions are: None, Restrict, Cascade, Clear, Cascade Server, ClearServer and Restrict Server. Copyright 2018, Whitemarsh Information Systems Corporation Proprietary Data, All Rights Reserved 2 Referential Integrity and Referential Actions Referential Integrity and Actions Referential Action taken when violation occurs On Update On Delete Referential Action Parent Child Parent Child Function ANSI Clarion Table Table Table Table Parent Table No equivalent None: Instructs the Primary No change Row is Nothing. Primary Key Application Generator not key in the deleted Effect is to Column value can to generate any code to column foreign key make the change. Foreign maintain referential value can value child table Key Column value integrity between any change row an does not change. -
SQL Vs Nosql: a Performance Comparison
SQL vs NoSQL: A Performance Comparison Ruihan Wang Zongyan Yang University of Rochester University of Rochester [email protected] [email protected] Abstract 2. ACID Properties and CAP Theorem We always hear some statements like ‘SQL is outdated’, 2.1. ACID Properties ‘This is the world of NoSQL’, ‘SQL is still used a lot by We need to refer the ACID properties[12]: most of companies.’ Which one is accurate? Has NoSQL completely replace SQL? Or is NoSQL just a hype? SQL Atomicity (Structured Query Language) is a standard query language A transaction is an atomic unit of processing; it should for relational database management system. The most popu- either be performed in its entirety or not performed at lar types of RDBMS(Relational Database Management Sys- all. tems) like Oracle, MySQL, SQL Server, uses SQL as their Consistency preservation standard database query language.[3] NoSQL means Not A transaction should be consistency preserving, meaning Only SQL, which is a collection of non-relational data stor- that if it is completely executed from beginning to end age systems. The important character of NoSQL is that it re- without interference from other transactions, it should laxes one or more of the ACID properties for a better perfor- take the database from one consistent state to another. mance in desired fields. Some of the NOSQL databases most Isolation companies using are Cassandra, CouchDB, Hadoop Hbase, A transaction should appear as though it is being exe- MongoDB. In this paper, we’ll outline the general differences cuted in iso- lation from other transactions, even though between the SQL and NoSQL, discuss if Relational Database many transactions are execut- ing concurrently.