Let's Talk About Storage & Recovery Methods for Non-Volatile Memory
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Class Notes Class: IX Topic: INPUT, OUTPUT, MEMORY and STORAGE DEVICES of a COMPUTER SYSTEM Subject: INFORMATION TECHNOLOGY
Class Notes Class: IX Topic: INPUT, OUTPUT, MEMORY AND STORAGE DEVICES OF A COMPUTER SYSTEM Subject: INFORMATION TECHNOLOGY Q1. A collection of eight bits is called BYTE Q2. Which of the following is an example of non-volatile memory? a) ROM b)RAM c) LSI d) VLSI Q3. Which of the following is unit of measurement used with computer system? a) Byte b) Megabyte c) Gigabyte d) All of the above Q4. Which of the following statement is false? a) Secondary storage in non-volatile. b) Primary storage is volatile. c) When the computer is turned off, data and instructions stored in primary storage are erased. d) None of the above. Q5. The secondary storage devices can only store data but they cannot perform a) Arithmetic operation b) Logic operation c) Fetch operation d) Either of above Q6. Which of the following does not represent an I/O device a) Speaker which beep b) Plotter C) Joystick d) ALU Q7. Which of the following is a correct definition of volatile memory? a) It loses its content at high temperatures. b) It is to be kept in airtight boxes. c) It loses its contents on failure of power supply d) It does not lose its contents on failure of power supply Q8. One thousand byte represent a a) Megabyte b) Gigabyte c) Kilobyte d) None of these Q9.What does a storage unit provide? a) A place to show data b) A place to store currently worked on information b) A place to store information Q10. What are four basic components of a computer? a) Input devices, Output devices, printing and typing b) Input devices, processing unit, storage and Output devices c) Input devices, CPU, Output devices and RAM Q11. -
The Era of Expeditious Nanoram-Based Computers Enhancement of Operating System Performance in Nanotechnology Environment
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 1 (2018) pp. 375-384 © Research India Publications. http://www.ripublication.com The Era of Expeditious NanoRAM-Based Computers Enhancement of Operating System Performance in Nanotechnology Environment Mona Nabil ElGohary PH.D Student, Computer Science Department Faculty of Computers and Information, Helwan University, Cairo, Egypt. 1ORCID: 0000-0002-1996-4673 Dr. Wessam ElBehaidy Assistant Professor, Computer Science Department, Faculty of Computers and Information, Helwan University, Cairo, Egypt. Ass. Prof. Hala Abdel-Galil Associative Professor, Computer Science Department Faculty of Computers and Information, Helwan University, Cairo, Egypt. Prof. Dr. Mostafa-Sami M. Mostafa Professor of Computer Science Faculty of Computers and Information, Helwan University, Cairo, Egypt. Abstract They announced that by 2018 will produce the first NanoRAM. The availability of a new generation of memory that is 1000 times faster than traditional DDRAM which can deliver This new NanoRam has many excellent properties that would terabytes of storage capacity, and consumes very little power, make an excellent replacement for the current DDRAM: being has the potential to change the future of the computer’s non-volatile, its large capacity, high speed read / write cycles. operating system. This paper studies the different changes that All the properties are introduced in the next section. will arise on the operating system functions; memory By replacing this NanoRAM instead of DDRAM in the CPU, management and job scheduling (especially context switch) this will affect the functionality of the operating system; such when integrating NanoRAM into the computer system. It is as main memory management, virtual memory, job scheduling, also looking forward to evaluating the possible enhancements secondary storage management; and thus the efficiency of the of computer’s performance with NanoRAM. -
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. -
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 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. -
Computer Conservation Society
Issue Number 88 Winter 2019/20 Computer Conservation Society Aims and Objectives The Computer Conservation Society (CCS) is a co-operative venture between BCS, The Chartered Institute for IT; the Science Museum of London; and the Science and Industry Museum (SIM) in Manchester. The CCS was constituted in September 1989 as a Specialist Group of the British Computer Society. It is thus covered by the Royal Charter and charitable status of BCS. The objects of the Computer Conservation Society (“Society”) are: To promote the conservation, restoration and reconstruction of historic computing systems and to identify existing computing systems which may need to be archived in the future; To develop awareness of the importance of historic computing systems; To develop expertise in the conservation, restoration and reconstruction of historic computing systems; To represent the interests of the Society with other bodies; To promote the study of historic computing systems, their use and the history of the computer industry; To publish information of relevance to these objectives for the information of Society members and the wider public. Membership is open to anyone interested in computer conservation and the history of computing. The CCS is funded and supported by a grant from BCS and from donations. There are a number of active projects on specific computer restorations and early computer technologies and software. Younger people are especially encouraged to take part in order to achieve skills transfer. The CCS also enjoys a close relationship with the National Museum of Computing. Resurrection The Journal of the Computer Conservation Society ISSN 0958-7403 Number 88 Winter 2019/20 Contents Society Activity 2 News Round-Up 9 The Data Curator 10 Paul Cockshott From Tea Shops to Computer Company: The Improbable 15 Story of LEO John Aeberhard Book Review: Early Computing in Britain Ferranti Ltd. -
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. -
High Volume Transaction Processing Without Concurrency Control, Two Phase Commit, SQL Or
High Volume Transaction Pro cessing Without Concurrency Control Two Phase Commit SQL or C Arthur Whitney Dennis Shasha Stevan Apter KX Systems Courant Institute NYU Union Bank of Switzerland Harker Avenue Mercer Street Park Avenue Palo Alto CA New York NY New York NY Abstract Imagine an application environment in which subsecond response to thousands of events gives the user a distinct competitive advantage yet transactional guarantees are important Imag ine also that the data ts comfortably into a few gigabytes of Random Access Memory These attributes characterize many nancial trading applications Which engine should one use in such a case IBM FastPath Sybase Oracle or Object Store We argue that an unconventional approach is cal led for we use a listbased language cal led K having optimized support for bulk array operators and that integrates networking and a graphical user interface Locking is unnecessary when singlethreading such applications because the data ts into memory obviating the need to go to disk except for logging purposes Multithreading can be hand led for OLTP applications by analyzing the arguments to transactions The result is a private sizereduced TPCB benchmark that achieves transactions per second with ful l recoverability and TCPIP overhead on an Megahertz UltraSparc I Further hot disaster recovery can be done with far less overhead than required by two phase commit by using a sequential state machine approach We show how to exploit multiple processors without complicating the language or our basic framework -
A Transaction Processing Method for Distributed Database
Advances in Computer Science Research, volume 87 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019) A Transaction Processing Method for Distributed Database Zhian Lin a, Chi Zhang b School of Computer and Cyberspace Security, Communication University of China, Beijing, China [email protected], [email protected] Abstract. This paper introduces the distributed transaction processing model and two-phase commit protocol, and analyses the shortcomings of the two-phase commit protocol. And then we proposed a new distributed transaction processing method which adds heartbeat mechanism into the two- phase commit protocol. Using the method can improve reliability and reduce blocking in distributed transaction processing. Keywords: distributed transaction, two-phase commit protocol, heartbeat mechanism. 1. Introduction Most database services of application systems will be distributed on several servers, especially in some large-scale systems. Distributed transaction processing will be involved in the execution of business logic. At present, two-phase commit protocol is one of the methods to distributed transaction processing in distributed database systems. The two-phase commit protocol includes coordinator (transaction manager) and several participants (databases). In the process of communication between the coordinator and the participants, if the participants without reply for fail, the coordinator can only wait all the time, which can easily cause system blocking. In this paper, heartbeat mechanism is introduced to monitor participants, which avoid the risk of blocking of two-phase commit protocol, and improve the reliability and efficiency of distributed database system. 2. Distributed Transactions 2.1 Distributed Transaction Processing Model In a distributed system, each node is physically independent and they communicates and coordinates each other through the network. -
Transaction Management in the R* Distributed Database Management System
Transaction Management in the R* Distributed Database Management System C. MOHAN, B. LINDSAY, and R. OBERMARCK IBM Almaden Research Center This paper deals with the transaction management aspects of the R* distributed database system. It concentrates primarily on the description of the R* commit protocols, Presumed Abort (PA) and Presumed Commit (PC). PA and PC are extensions of the well-known, two-phase (2P) commit protocol. PA is optimized for read-only transactions and a class of multisite update transactions, and PC is optimized for other classes of multisite update transactions. The optimizations result in reduced intersite message traffic and log writes, and, consequently, a better response time. The paper also discusses R*‘s approach toward distributed deadlock detection and resolution. Categories and Subject Descriptors: C.2.4 [Computer-Communication Networks]: Distributed Systems-distributed datahes; D.4.1 [Operating Systems]: Process Management-concurrency; deadlocks, syndvonization; D.4.7 [Operating Systems]: Organization and Design-distributed sys- tems; D.4.5 [Operating Systems]: Reliability--fault tolerance; H.2.0 [Database Management]: General-concurrency control; H.2.2 [Database Management]: ‘Physical Design-recouery and restart; H.2.4 [Database Management]: Systems-ditributed systems; transactionprocessing; H.2.7 [Database Management]: Database Administration-logging and recouery General Terms: Algorithms, Design, Reliability Additional Key Words and Phrases: Commit protocols, deadlock victim selection 1. INTRODUCTION R* is an experimental, distributed database management system (DDBMS) developed and operational at the IBM San Jose Research Laboratory (now renamed the IBM Almaden Research Center) 118, 201. In a distributed database system, the actions of a transaction (an atomic unit of consistency and recovery [13]) may occur at more than one site. -
A Simple Guide to Transaction Processing
@ WORK SERIES Hands-on OneWorld Documentation A Simple guide to Transaction Processing Technology Demographic Table Product OneWorld Version B733.x Platform/OS All Industry All Application All Database All Keywords Strategic, OneWorld, B9 Date July 2000 ? erpSourcing. All Rights Reserved October 2000 - A Simple Guide to Transaction Processing Disclaimer All information contained in this document should be treated as a hypothetical project plan. It is often the case that with upgrades to production and development objects, that there are issues that will be raised. This will therefore dramatically increase project timelines. None of the entries in this document are in any way a replacement for the JDEdwards OneWorld Xe Upgrade Guide – instead, this document should be treated as a complement. Overview This document is release independent - ie, I will attempt to describe Transaction Processing. The latter parts of this email are SAR posts directly affecting pre-B733 and post-B733 (including Xe) versions - and lastly I attach a list of applications in B7.3.3.1 that were Transaction Processing activated. Note that Transaction Processing is now called "Lock Manager" (since B7.3.3) and has absolutely NOTHING to do with row-level database locking ! Chapter 1 - What is it ? Definitions and Abbreviations used throughout this document ??TMS (Transaction Management Server) - the server that is used to serve as a central "checkpoint" for all database transactions. ??TP (Transaction Processing) Monitor - the process that runs on the TMS that is capable of timestamping database record changes and notifying the user if he/she has retrieved a record (and left it unchanged) that has since been changed by another user.