Transcript of an Interview with Michael Stonebraker 2014 ACM Turing Award Recipient
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Ingres 9.3 Migration Guide
Ingres® 9.3 Migration Guide ING-93-MG-02 This Documentation is for the end user's informational purposes only and may be subject to change or withdrawal by Ingres Corporation ("Ingres") at any time. This Documentation is the proprietary information of Ingres and is protected by the copyright laws of the United States and international treaties. It is not distributed under a GPL license. You may make printed or electronic copies of this Documentation provided that such copies are for your own internal use and all Ingres copyright notices and legends are affixed to each reproduced copy. You may publish or distribute this document, in whole or in part, so long as the document remains unchanged and is disseminated with the applicable Ingres software. Any such publication or distribution must be in the same manner and medium as that used by Ingres, e.g., electronic download via website with the software or on a CD- ROM. Any other use, such as any dissemination of printed copies or use of this documentation, in whole or in part, in another publication, requires the prior written consent from an authorized representative of Ingres. To the extent permitted by applicable law, INGRES PROVIDES THIS DOCUMENTATION "AS IS" WITHOUT WARRANTY OF ANY KIND, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NONINFRINGEMENT. IN NO EVENT WILL INGRES BE LIABLE TO THE END USER OR ANY THIRD PARTY FOR ANY LOSS OR DAMAGE, DIRECT OR INDIRECT, FROM THE USER OF THIS DOCUMENTATION, INCLUDING WITHOUT LIMITATION, LOST PROFITS, BUSINESS INTERRUPTION, GOODWILL, OR LOST DATA, EVEN IF INGRES IS EXPRESSLY ADVISED OF SUCH LOSS OR DAMAGE. -
Oracle Vs. Nosql Vs. Newsql Comparing Database Technology
Oracle vs. NoSQL vs. NewSQL Comparing Database Technology John Ryan Senior Solution Architect, Snowflake Computing Table of Contents The World has Changed . 1 What’s Changed? . 2 What’s the Problem? . .. 3 Performance vs. Availability and Durability . 3 Consistecy vs. Availability . 4 Flexibility vs . Scalability . 5 ACID vs. Eventual Consistency . 6 The OLTP Database Reimagined . 7 Achieving the Impossible! . .. 8 NewSQL Database Technology . 9 VoltDB . 10 MemSQL . 11 Which Applications Need NewSQL Technology? . 12 Conclusion . 13 About the Author . 13 ii The World has Changed The world has changed massively in the past 20 years. Back in the year 2000, a few million users connected to the web using a 56k modem attached to a PC, and Amazon only sold books. Now billions of people are using to their smartphone or tablet 24x7 to buy just about everything, and they’re interacting with Facebook, Twitter and Instagram. The pace has been unstoppable . Expectations have also changed. If a web page doesn’t refresh within seconds we’re quickly frustrated, and go elsewhere. If a web site is down, we fear it’s the end of civilisation as we know it. If a major site is down, it makes global headlines. Instant gratification takes too long! — Ladawn Clare-Panton Aside: If you’re not a seasoned Database Architect, you may want to start with my previous articles on Scalability and Database Architecture. Oracle vs. NoSQL vs. NewSQL eBook 1 What’s Changed? The above leads to a few observations: • Scalability — With potentially explosive traffic growth, IT systems need to quickly grow to meet exponential numbers of transactions • High Availability — IT systems must run 24x7, and be resilient to failure. -
The Declarative Imperative Experiences and Conjectures in Distributed Logic
The Declarative Imperative Experiences and Conjectures in Distributed Logic Joseph M. Hellerstein University of California, Berkeley [email protected] ABSTRACT The juxtaposition of these trends presents stark alternatives. The rise of multicore processors and cloud computing is putting Will the forecasts of doom and gloom materialize in a storm enormous pressure on the software community to find solu- that drowns out progress in computing? Or is this the long- tions to the difficulty of parallel and distributed programming. delayed catharsis that will wash away today’s thicket of im- At the same time, there is more—and more varied—interest in perative languages, preparing the ground for a more fertile data-centric programming languages than at any time in com- declarative future? And what role might the database com- puting history, in part because these languages parallelize nat- munity play in shaping this future, having sowed the seeds of urally. This juxtaposition raises the possibility that the theory Datalog over the last quarter century? of declarative database query languages can provide a foun- Before addressing these issues directly, a few more words dation for the next generation of parallel and distributed pro- about both crisis and opportunity are in order. gramming languages. 1.1 Urgency: Parallelism In this paper I reflect on my group’s experience over seven years using Datalog extensions to build networking protocols I would be panicked if I were in industry. and distributed systems. Based on that experience, I present — John Hennessy, President, Stanford University [35] a number of theoretical conjectures that may both interest the database community, and clarify important practical issues in The need for parallelism is visible at micro and macro scales. -
The Ingres Next Initiative Enabling the Cloud, Mobile, and Web Journeys for Our Actian X and Ingres Database Customers
The Ingres NeXt Initiative Enabling the Cloud, Mobile, and Web Journeys for our Actian X and Ingres Database Customers Any organization that has leveraged technology to help run their business Benefits knows that the costs associated with on-going maintenance and support for Accelerate Cost Savings legacy systems can often take the upwards of 50% of the budget. Analysts and • Seize near-term cost IT vendors tend to see these on-going investments as sub-optimum, but for reductions across your IT and mission critical systems that have served their organizations well for decades business operations and tight budgets, , the risk to operations and business continuity make • Leverage existing IT replacing these tried and tested mission critical systems impractical. In many investments and data sources cases, these essential systems contain thousands of hours of custom developed business logic investment. • Avoid new CAPEX cycles when Products such as Actian Ingres and, more recently Actian X Relational retiring legacy systems Database Management Systems (RDBMS), have proven Actian’s commitment to helping our customers maximize their existing investments without having Optimize Risk Mitigation to sacrifice modern functionality. Ultimately, this balance in preservation and • Preserve investments in existing business logic while innovation with Ingres has taken us to three areas of development and taking advantage of modern deployment: continuation of heritage UNIX variants on their associated capabilities hardware, current Linux and Windows for on-premise and virtualized environments and most importantly, enabling migration to the public cloud. • Same database across all platforms Based on a recent survey of our Actian X and Ingres customer base, we are seeing a growing desire to move database workloads to the Cloud. -
The Best Nurturers in Computer Science Research
The Best Nurturers in Computer Science Research Bharath Kumar M. Y. N. Srikant IISc-CSA-TR-2004-10 http://archive.csa.iisc.ernet.in/TR/2004/10/ Computer Science and Automation Indian Institute of Science, India October 2004 The Best Nurturers in Computer Science Research Bharath Kumar M.∗ Y. N. Srikant† Abstract The paper presents a heuristic for mining nurturers in temporally organized collaboration networks: people who facilitate the growth and success of the young ones. Specifically, this heuristic is applied to the computer science bibliographic data to find the best nurturers in computer science research. The measure of success is parameterized, and the paper demonstrates experiments and results with publication count and citations as success metrics. Rather than just the nurturer’s success, the heuristic captures the influence he has had in the indepen- dent success of the relatively young in the network. These results can hence be a useful resource to graduate students and post-doctoral can- didates. The heuristic is extended to accurately yield ranked nurturers inside a particular time period. Interestingly, there is a recognizable deviation between the rankings of the most successful researchers and the best nurturers, which although is obvious from a social perspective has not been statistically demonstrated. Keywords: Social Network Analysis, Bibliometrics, Temporal Data Mining. 1 Introduction Consider a student Arjun, who has finished his under-graduate degree in Computer Science, and is seeking a PhD degree followed by a successful career in Computer Science research. How does he choose his research advisor? He has the following options with him: 1. Look up the rankings of various universities [1], and apply to any “rea- sonably good” professor in any of the top universities. -
SQL Vs Nosql
SQL vs NoSQL By: Mohammed-Ali Khan Email: [email protected] Date: October 21, 2012 YORK UNIVERSITY Agenda ● History of DBMS – why relational is most popular? ● Types of DBMS – brief overview ● Main characteristics of RDBMS ● Main characteristics of NoSQL DBMS ● SQL vs NoSQL ● DB overview – Cassandra ● Criticism of NoSQL ● Some Predictions / Conclusions History of DBMS – why relational is most popular? ● 19th century: US Government needed reports from large datasets to conduct nation-wide census. ● 1890: Herman Hollerith creates the first automatic processing equipment which allowed American census to be conducted. ● 1911: IBM founded. ● 1960s: Efforts to standardize the database technology – US DoD: Conference on Data Systems Language (Codasyl). History of DBMS – why relational is most popular? ● 1968: IBM introduced IMS DBMS (a hierarchical DBMS). ● IBM employee Edgar Codd not satisfied, quoted as saying: – “Taking the old line view, that the burden of finding information should be placed on users...” ● Edgar Codd publishes a paper “A relational Model of Data for large shared Data Banks” – Key points: Independence of data from hardware/storage implementation – High level non-procedural language for data access – Pointers/keys (primary/secondary) History of DBMS – why relational is most popular? ● 1970s: Two database projects launched based on relational model – Ingres (Department of Defence Initiative) – System R (IBM) ● Ingres had its own query language called QUEL whereas System R used SQL. ● Larry Ellison, who worked at IBM, read publications of the System R group and eventually founded ORACLE. History of DBMS – why relational is most popular? ● 1980: IBM introduced SQL for the mainframe market. ● In a nutshell, American Government's requirements had a strong role in development of the relational DBMS. -
Issue Purchase Order for Ingres Relational Database Management System Software Support
BOARD MEETING DATE: December 5, 2014 AGENDA NO. 11 PROPOSAL: Issue Purchase Order for Ingres Relational Database Management System Software Support SYNOPSIS: The Ingres Relational Database Management System is used for the implementation of the Central Information Repository database. This database is used by most enterprise-level software applications at the SCAQMD and currently supports a suite of client/server and web-based applications known collectively as the Clean Air Support System (CLASS). The CLASS applications are used to support all of the SCAQMD core activities. Maintenance support for this software expires November 29, 2014. This action is to issue a three-year purchase order with Actian Corporation for a total amount of $564,967. Funds for this expense are included in the FY 2014-15 Budget and will be included in subsequent fiscal year budget requests. COMMITTEE: Administrative, November 14, 2014, Recommended for Approval RECOMMENDED ACTION: Authorize the Procurement Manager to issue a three-year purchase order with Actian Corporation (formerly Ingres Corporation) for Ingres Relational Database Management System software maintenance support, for the period of November 30, 2014 through November 29, 2017, for a total amount not to exceed $564,967. Barry R. Wallerstein, D.Env. Executive Officer JCM: MH:ZT:agg Background In November 2006, the SCAQMD entered into an annual support and maintenance agreement for Ingres Relational Database Management System (RDBMS) software. The RDBMS software runs on three database servers for production, development, and ad hoc reporting. The production server hosts the Central Information Repository database (DBCIR). This database supports a collection of more than 30 client/server and web-based applications known as the Clean Air Support System (CLASS). -
Ingres 10.1 for Linux Quick Start Guide
Ingres 10S Quick Start Guide ING-1001-QSL-03 This Documentation is for the end user's informational purposes only and may be subject to change or withdrawal by Actian Corporation ("Actian") at any time. This Documentation is the proprietary information of Actian and is protected by the copyright laws of the United States and international treaties. It is not distributed under a GPL license. You may make printed or electronic copies of this Documentation provided that such copies are for your own internal use and all Actian copyright notices and legends are affixed to each reproduced copy. You may publish or distribute this document, in whole or in part, so long as the document remains unchanged and is disseminated with the applicable Actian software. Any such publication or distribution must be in the same manner and medium as that used by Actian, e.g., electronic download via website with the software or on a CD- ROM. Any other use, such as any dissemination of printed copies or use of this documentation, in whole or in part, in another publication, requires the prior written consent from an authorized representative of Actian. To the extent permitted by applicable law, ACTIAN PROVIDES THIS DOCUMENTATION "AS IS" WITHOUT WARRANTY OF ANY KIND, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NONINFRINGEMENT. IN NO EVENT WILL ACTIAN BE LIABLE TO THE END USER OR ANY THIRD PARTY FOR ANY LOSS OR DAMAGE, DIRECT OR INDIRECT, FROM THE USER OF THIS DOCUMENTATION, INCLUDING WITHOUT LIMITATION, LOST PROFITS, BUSINESS INTERRUPTION, GOODWILL, OR LOST DATA, EVEN IF ACTIAN IS EXPRESSLY ADVISED OF SUCH LOSS OR DAMAGE. -
Ingres R3 Opensql Reference Guide
Ingres OpenSQL Reference Guide r3 P00283-1E This documentation and related computer software program (hereinafter referred to as the “Documentation”) is for the end user’s informational purposes only and is subject to change or withdrawal by Computer Associates International, Inc. (“CA”) at any time. This documentation may not be copied, transferred, reproduced, disclosed or duplicated, in whole or in part, without the prior written consent of CA. This documentation is proprietary information of CA and protected by the copyright laws of the United States and international treaties. Notwithstanding the foregoing, licensed users may print a reasonable number of copies of this documentation for their own internal use, provided that all CA copyright notices and legends are affixed to each reproduced copy. Only authorized employees, consultants, or agents of the user who are bound by the confidentiality provisions of the license for the software are permitted to have access to such copies. This right to print copies is limited to the period during which the license for the product remains in full force and effect. Should the license terminate for any reason, it shall be the user’s responsibility to return to CA the reproduced copies or to certify to CA that same have been destroyed. To the extent permitted by applicable law, CA provides this documentation “as is” without warranty of any kind, including without limitation, any implied warranties of merchantability, fitness for a particular purpose or noninfringement. In no event will CA be liable to the end user or any third party for any loss or damage, direct or indirect, from the use of this documentation, including without limitation, lost profits, business interruption, goodwill, or lost data, even if CA is expressly advised of such loss or damage. -
DATA BASE RESEARCH at BERKELEY Michael Stonebraker
DATA BASE RESEARCH AT BERKELEY Michael Stonebraker Department of Electrical Engineering and Computer Science University of California, Berkeley 1. INTRODUCTION the performance of the prototype, finishing the imple- Data base research at Berkeley can be decom- mentation of promised function, and on integrating ter- posed into four categories. First there is the POSTGRES tiary memory into the POSTGRES environment in a project led by Michael Stonebraker, which is building a more flexible way. next-generation DBMS with novel object management, General POSTGRES information can be obtained knowledge management and time travel capabilities. from the following references. Second, Larry Rowe leads the PICASSO project which [MOSH90] Mosher, C. (ed.), "The POSTGRES Ref- is constructing an advanced application development erence Manual, Version 2," University of tool kit for use with POSTGRES and other DBMSs. California, Electronics Research Labora- Third, there is the XPRS project (eXtended Postgres on tory, Technical Report UCB/ERL Raid and Sprite) which is led by four Berkeley faculty, M90-60, Berkeley, Ca., August 1990. Randy Katz, John Ousterhout, Dave Patterson and Michael Stonebraker. XPRS is exploring high perfor- [STON86] Stonebraker M. and Rowe, L., "The mance I/O systems and their efficient utilization by oper- Design of POSTGRES," Proc. 1986 ating systems and data managers. The last project is one ACM-SIGMOD Conference on Manage- aimed at improving the reliability of DBMS software by ment of Data, Washington, D.C., June dealing more effectively with software errors that is also 1986. led by Michael Stonebraker. [STON90] Stonebraker, M. et. al., "The Implementa- In this short paper we summarize work on POST- tion of POSTGRES," IEEE Transactions GRES, PICASSO, and software reliability and report on on Knowledge and Data Engineering, the XPRS work that is relevant to data management. -
Pydal Documentation Release 15.03
pyDAL Documentation Release 15.03 web2py-developers May 25, 2015 Contents 1 Indices and tables 3 1.1 Subpackages...............................................3 1.2 Submodules............................................... 28 1.3 pydal.base module............................................ 28 1.4 pydal.connection module......................................... 35 1.5 pydal.objects module........................................... 36 1.6 Module contents............................................. 44 Python Module Index 45 i ii pyDAL Documentation, Release 15.03 Contents: Contents 1 pyDAL Documentation, Release 15.03 2 Contents CHAPTER 1 Indices and tables • genindex • modindex • search 1.1 Subpackages 1.1.1 pydal.adapters package Submodules pydal.adapters.base module class pydal.adapters.base.AdapterMeta Bases: type Metaclass to support manipulation of adapter classes. At the moment is used to intercept entity_quoting argument passed to DAL. class pydal.adapters.base.BaseAdapter(db, uri, pool_size=0, folder=None, db_codec=’UTF- 8’, credential_decoder=<function IDENTITY at 0x7f781c8f6500>, driver_args={}, adapter_args={}, do_connect=True, after_connection=None) Bases: pydal.connection.ConnectionPool ADD(first, second) AGGREGATE(first, what) ALLOW_NULL() AND(first, second) AS(first, second) BELONGS(first, second) CASE(query, t, f ) CAST(first, second) COALESCE(first, second) 3 pyDAL Documentation, Release 15.03 COALESCE_ZERO(first) COMMA(first, second) CONCAT(*items) CONTAINS(first, second, case_sensitive=True) COUNT(first, distinct=None) DIV(first, -
Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration.