1. 2011-11-22 - SLIDE 1IS 257 – Fall 2011 New Generation Database Systems: The Grid/Cloud and The Future University of California, Berkeley School of Information IS 257: Database Management

2. 2011-11-22 - SLIDE 2IS 257 – Fall 2011 Final project Final project is the completed version of your personal project with an enhanced version of Assignment 4 AND an in-class presentation on the database design and interface Detailed description and elements to be considered in grading are available by following the links on the Assignments page or the main page of the class site

3. 2011-11-22 - SLIDE 3IS 257 – Fall 2011 Grid-based Digital Libraries So what’s this Grid thing anyhow? Data Grids and Distributed Storage Grid-Based IR Grid-Based Digital Libraries Grid vs “Cloud” This lecture borrows heavily from presentations by Ian Foster (Argonne National Laboratory & University of Chicago), Reagan Moore and others from San Diego Supercomputer Center

4. 2011-11-22 - SLIDE 4IS 257 – Fall 2011 The Grid: On-Demand Access to Electricity Time Quality, economies of scale Source: Ian Foster

5. 2011-11-22 - SLIDE 5IS 257 – Fall 2011 By Analogy, A Computing Grid Decouples production and consumption –Enable on-demand access –Achieve economies of scale –Enhance consumer flexibility –Enable new devices On a variety of scales –Department –Campus –Enterprise –Internet Source: Ian Foster

6. 2011-11-22 - SLIDE 6IS 257 – Fall 2011 What is the Grid? “The short answer is that, whereas the Web is a service for sharing information over the Internet, the Grid is a service for sharing computer power and data storage capacity over the Internet. The Grid goes well beyond simple communication between computers, and aims ultimately to turn the global network of computers into one vast computational resource.” Source: The Global Grid Forum

7. 2011-11-22 - SLIDE 7IS 257 – Fall 2011 Not Exactly a New Idea … “The time-sharing computer system can unite a group of investigators …. one can conceive of such a facility as an … intellectual public utility.” –Fernando Corbato and Robert Fano, 1966 “We will perhaps see the spread of ‘computer utilities’, which, like present electric and telephone utilities, will service individual homes and offices across the country.” Len Kleinrock, 1967 Source: Ian Foster

8. 2011-11-22 - SLIDE 8IS 257 – Fall 2011 But, Things are Different Now Networks are far faster (and cheaper) –Faster than computer backplanes “Computing” is very different than pre-Net –Our “computers” have already disintegrated –E-commerce increases size of demand peaks –Entirely new applications & social structures We’ve learned a few things about software Source: Ian Foster

9. 2011-11-22 - SLIDE 9IS 257 – Fall 2011 Computing isn’t Really Like Electricity I import electricity but must export data “Computing” is not interchangeable but highly heterogeneous: data, sensors, services, … This complicates things; but also means that the sum can be greater than the parts –Real opportunity: Construct new capabilities dynamically from distributed services Raises three fundamental questions –Can I really achieve economies of scale? –Can I achieve QoS across distributed services? –Can I identify apps that exploit synergies? Source: Ian Foster

10. 2011-11-22 - SLIDE 10IS 257 – Fall 2011 Why the Grid? (1) Revolution in Science Pre-Internet –Theorize &/or experiment, alone or in small teams; publish paper Post-Internet –Construct and mine large databases of observational or simulation data –Develop simulations & analyses –Access specialized devices remotely –Exchange information within distributed multidisciplinary teams Source: Ian Foster

11. 2011-11-22 - SLIDE 11IS 257 – Fall 2011 Why the Grid? (2) Revolution in Business Pre-Internet –Central data processing facility Post-Internet –Enterprise computing is highly distributed, heterogeneous, inter-enterprise (B2B) –Business processes increasingly computing- & data-rich –Outsourcing becomes feasible => service providers of various sorts Source: Ian Foster

12. 2011-11-22 - SLIDE 12IS 257 – Fall 2011 The Information Grid Imagine a web of data Machine Readable –Search, Aggregate, Transform, Report On, Mine Data – using more computers, and less humans Scalable –Machines are cheap – can buy 50 machines with 100Gb or memory and 100 TB disk for under $100K, and dropping –Network is now faster than disk Flexible –Move data around without breaking the apps Source: S. Banerjee, O. Alonso, M. Drake - ORACLE

13. 2011-11-22 - SLIDE 13IS 257 – Fall 2011 Tier0/1 facility Tier2 facility 10 Gbps link 2.5 Gbps link 622 Mbps link Other link Tier3 facility The Foundations are Being Laid Cambridge Newcastle Edinburgh Oxford Glasgow Manchester Cardiff Soton London Belfast DL RAL Hinxton

14. 2011-11-22 - SLIDE 14IS 257 – Fall 2011 Data Grid Problem “Enable a geographically distributed community [of thousands] to pool their resources in order to perform sophisticated, computationally intensive analyses on Petabytes of data” Note that this problem: –Is common to many areas of science –Overlaps strongly with other Grid problems

15. 2011-11-22 - SLIDE 15IS 257 – Fall 2011 Data Grids for High Energy Physics Tier2 Centre ~1 TIPS Online System Offline Processor Farm ~20 TIPS CERN Computer Centre FermiLab ~4 TIPS France Regional Centre Italy Regional Centre Germany Regional Centre Institute Institute ~0.25TIPS Physicist workstations ~100 MBytes/sec ~622 Mbits/sec ~1 MBytes/sec There is a “bunch crossing” every 25 nsecs. There are 100 “triggers” per second Each triggered event is ~1 MByte in size Physicists work on analysis “channels”. Each institute will have ~10 physicists working on one or more channels; data for these channels should be cached by the institute server Physics data cache ~PBytes/sec ~622 Mbits/sec or Air Freight (deprecated) Tier2 Centre ~1 TIPS Caltech ~1 TIPS ~622 Mbits/sec Tier 0 Tier 1 Tier 2 Tier 4 1 TIPS is approximately 25,000 SpecInt95 equivalents Image courtesy Harvey Newman, Caltech

16. 2011-11-22 - SLIDE 16IS 257 – Fall 2011 Not only Science… The Database world is moving to the Grid for large-scale applications Oracle 10g is specifically designed to exploit clustered/grid computing using RACs (Real Application Clusters) An example from the Information/Publishing world… –Presentation from Oracle about Thomson Legal’s use of Oracle 10g and RACs

17. 2011-11-22 - SLIDE 17IS 257 – Fall 2011 ORACLE Grid-Based DBMS Example Oracle presentation of solutions for a large firm…

18. 2011-11-22 - SLIDE 18IS 257 – Fall 2011 Future of Database Systems University of California, Berkeley School of Information IS 257: Database Management

19. 2011-11-22 - SLIDE 19IS 257 – Fall 2011 Lecture Outline Future of Database Systems Predicting the future… Quotes from Leon Kappelman “The future is ours” CACM, March 2001 Accomplishments of database research over the past 30 years Next-Generation Databases and the Future

20. 2011-11-22 - SLIDE 20IS 257 – Fall 2011 Radio has no future, Heavier-than-air flying machines are impossible. X-rays will prove to be a hoax. –William Thompson (Lord Kelvin), 1899

21. 2011-11-22 - SLIDE 21IS 257 – Fall 2011 This “Telephone” has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us. –Western Union, Internal Memo, 1876

22. 2011-11-22 - SLIDE 22IS 257 – Fall 2011 I think there is a world market for maybe five computers –Thomas Watson, Chair of IBM, 1943

23. 2011-11-22 - SLIDE 23IS 257 – Fall 2011 The problem with television is that the people must sit and keep their eyes glued on the screen; the average American family hasn’t time for it. –New York Times, 1949

24. 2011-11-22 - SLIDE 24IS 257 – Fall 2011 Where … the ENIAC is equipped with 18,000 vacuum tubes and weighs 30 tons, computers in the future may have only 1000 vacuum tubes and weigh only 1.5 tons –Popular Mechanics, 1949

25. 2011-11-22 - SLIDE 25IS 257 – Fall 2011 There is no reason anyone would want a computer in their home. –Ken Olson, president and chair of Digital Equipment Corp., 1977.

26. 2011-11-22 - SLIDE 26IS 257 – Fall 2011 640K ought to be enough for anybody. –Attributed to Bill Gates, 1981

27. 2011-11-22 - SLIDE 27IS 257 – Fall 2011 By the turn of this century, we will live in a paperless society. –Roger Smith, Chair of GM, 1986

28. 2011-11-22 - SLIDE 28IS 257 – Fall 2011 I predict the internet… will go spectacularly supernova and in 1996 catastrophically collapse. –Bob Metcalfe (3-Com founder and inventor of ethernet), 1995

29. 2011-11-22 - SLIDE 29IS 257 – Fall 2011 Lecture Outline Review –Object-Oriented Database Development Future of Database Systems Predicting the future… Quotes from Leon Kappelman “The future is ours” CACM, March 2001 Accomplishments of database research over the past 30 years Next-Generation Databases and the Future

30. 2011-11-22 - SLIDE 30IS 257 – Fall 2011 Database Research Database research community less than 40 years old Has been concerned with business type applications that have the following demands: –Efficiency in access and modification of very large amounts of data –Resilience in surviving hardware and software errors without losing data –Access control to support simultaneous access by multiple users and ensure consistency –Persistence of the data over long time periods regardless of the programs that access the data Research has centered on methods for designing systems with efficiency, resilience, access control, and persistence and on the languages and conceptual tools to help users to access, manipulate and design databases.

31. 2011-11-22 - SLIDE 31IS 257 – Fall 2011 Accomplishments of DBMS Research DBMS are now used in almost every computing environment to create, organize and maintain large collections of information, and this is largely due to the results of the DBMS research community’s efforts, in particular: –Relational DBMS –Transaction management –Distributed DBMS

32. 2011-11-22 - SLIDE 32IS 257 – Fall 2011 Relational DBMS The relational data model proposed by E.F. Codd in papers (1970-1972) was a breakthrough for simplicity in the conceptual model of DBMS. However, it took much research to actually turn RDBMS into realities.

33. 2011-11-22 - SLIDE 33IS 257 – Fall 2011 Relational DBMS During the 1970’s database researchers: –Invented high-level relational query languages to ease the use of the DBMS for end users and applications programmers. –Developed Theory and algorithms needed to optimize queries into execution plans as efficient and sophisticated as a programmer might have custom designed for an earlier DBMS

34. 2011-11-22 - SLIDE 34IS 257 – Fall 2011 Relational DBMS –Developed Normalization theory to help with database design by eliminating redundancy –Developed clustering algorithms to improve retrieval efficiency. –Developed buffer management algorithms to exploit knowledge of access patterns –Constructed indexing methods for fast access to single records or sets of records by values –Implemented prototype RDBMS that formed the core of many current commercial RDBMS

35. 2011-11-22 - SLIDE 35IS 257 – Fall 2011 Relational DBMS The result of this DBMS research was the development of commercial RDBMS in the 1980’s When Codd first proposed RDBMS it was considered theoretically elegant, but it was assumed only toy RDBMS could ever be implemented due to the problems and complexities involved. Research changed that.

36. 2011-11-22 - SLIDE 36IS 257 – Fall 2011 Transaction Management Research on transaction management has dealt with the basic problems of maintaining consistency in multi-user high transaction database systems

37. 2011-11-22 - SLIDE 37IS 257 – Fall 2011 No Transactions : Lost updates Read account balance (balance = $1000) Transfer $100 to Mel Debits $100 SYSTEM CRASH Read account balance (balance = $900) Read account balance (balance = $1000) SYSTEM CRASH Read account balance (balance = $1000) John Mel ERROR!

38. 2011-11-22 - SLIDE 38IS 257 – Fall 2011 No Concurrency Control: Lost updates Read account balance (balance = $1000) Withdraw $200 (balance = $800) Write account balance (balance = $800) Read account balance (balance = $1000) Withdraw $300 (balance = $700) Write account balance (balance = $700) John Marsha ERROR!

39. 2011-11-22 - SLIDE 39IS 257 – Fall 2011 Transaction Management To guarantee that a transaction transforms the database from one consistent state to another requires: –The concurrent execution of transactions must be such that they appear to execute in isolation. –System failures must not result in inconsistent database states. Recovery is the technique used to provide this.

40. 2011-11-22 - SLIDE 40IS 257 – Fall 2011 Distributed Databases The ability to have a single “logical database” reside in two or more locations on different computers, yet to keep querying, updates and transactions all working as if it were a single database on a single machine How do you manage such a system?

41. 2011-11-22 - SLIDE 41IS 257 – Fall 2011 Lecture Outline Review –Object-Oriented Database Development Future of Database Systems Predicting the future… Quotes from Leon Kappelman “The future is ours” CACM, March 2001 Accomplishments of database research over the past 30 years “Next-Generation Databases” and the Future

42. 2011-11-22 - SLIDE 42IS 257 – Fall 2011 Next Generation Database Systems Where are we going from here? –Hardware is getting faster and cheaper –DBMS technology continues to improve and change OODBMS ORDBMS –Bigger challenges for DBMS technology Medicine, design, manufacturing, digital libraries, sciences, environment, planning, etc... Sensor networks, streams, etc… The Claremont Report on DB Research –Sigmod Record, v. 37, no. 3 (Sept 2008)

43. 2011-11-22 - SLIDE 43IS 257 – Fall 2011 Examples NASA EOSDIS –Estimated 10 16 Bytes (Exabyte) Computer-Aided design The Human Genome Department Store tracking –Mining non-transactional data (e.g. Scientific data, text data?) Insurance Company –Multimedia DBMS support

44. 2011-11-22 - SLIDE 44IS 257 – Fall 2011 New Features New Data types Rule Processing New concepts and data models Problems of Scale Parallelism/Grid-based DB Tertiary Storage vs Very Large-Scale Disk Storage vs Large-Scale semiconductor Storage Heterogeneous Databases Memory Only DBMS

45. 2011-11-22 - SLIDE 45IS 257 – Fall 2011 Coming to a Database Near You… Browsibility User-defined access methods Security Steering Long processes Federated Databases IR capabilities XML The Semantic Web(?)

46. 2011-11-22 - SLIDE 46IS 257 – Fall 2011 Standards: XML/SQL As part of SQL3 an extension providing a mapping from XML to DBMS is being created called XML/SQL The (draft) standard is very complex, but the ideas are actually pretty simple Suppose we have a table called EMPLOYEE that has columns EMPNO, FIRSTNAME, LASTNAME, BIRTHDATE, SALARY

47. 2011-11-22 - SLIDE 47IS 257 – Fall 2011 Standards: XML/SQL That table can be mapped to: 000020 John Smith 1955-08-21 52300.00 … etc. …

48. 2011-11-22 - SLIDE 48IS 257 – Fall 2011 Standards: XML/SQL In addition the standard says that XMLSchemas must be generated for each table, and also allows relations to be managed by nesting records from tables in the XML. Variants of this are incorporated into the latest versions of ORACLE (Slides from Oracle Web Site on ORACLE XML)

49. 2011-11-22 - SLIDE 49IS 257 – Fall 2011 The Semantic Web The basic structure of the Semantic Web is based on RDF triples (as XML or some other form) Conventional DBMS are very bad at doing some of the things that the Semantic Web is supposed to do… (.e.g., spreading activation searching) “Triple Stores” are being developed that are intended to optimize for the types of search and access needed for the Semantic Web

50. 2011-11-22 - SLIDE 50IS 257 – Fall 2011 The next-generation DBMS What can we expect for a next generation of DBMS? Look at the DB research community – their research leads to the “new features” in DBMS The “Claremont Report” on DB research is the report of meeting of top researchers and what they think are the interesting and fruitful research topics for the future

51. 2011-11-22 - SLIDE 51IS 257 – Fall 2011 But will it be a RDBMS? Recently, Mike Stonebraker (one of the people who helped invent Relational DBMS) has suggested that the “One Size Fits All” model for DBMS is an idea whose time has come – and gone –This was also a theme of the Claremont Report RDBMS technology, as noted previously, has optimized on transactional business type processing But many other applications do not follow that model

52. 2011-11-22 - SLIDE 52IS 257 – Fall 2011 Will it be an RDBMS? Stonebraker predicts that the DBMS market will fracture into many more specialized database engines –Although some may have a shared common frontend Examples are Data Warehouses, Stream processing engines, Text and unstructured data processing systems

53. 2011-11-22 - SLIDE 53IS 257 – Fall 2011 Will it be an RDBMS? Data Warehouses currently use (mostly) conventional DBMS technology –But they are NOT the type of data those are optimized for –Storage usually puts all elements of a row together, but that is an optimization for updating and not searching, summarizing, and reading individual attributes –A better solution is to store the data by column instead of by row – vastly more efficient for typical Data Warehouse Applications

54. 2011-11-22 - SLIDE 54IS 257 – Fall 2011 Will it be an RDBMS? Streaming data, such as Wall St. stock trade information is badly suited to conventional RDBMS (other than as historical data) –The data arrives in a continuous real-time stream –But, data in RDBMS has to be stored before it can be read and actions taken on it This is too slow for real-time actions on that data –Stream processors function by running “queries” on the live data stream instead May be orders of magnitude faster

55. 2011-11-22 - SLIDE 55IS 257 – Fall 2011 Will it be an RDBMS? Sensor networks provide another massive stream input and analysis problem Text Search: No current text search engines use RDBMS, they too need to be optimized for searching, and tend to use inverted file structures instead of RDBMS storage Scientific databases are another typical example of streamed data from sensor networks or instruments XML data is still not a first-class citizen of RDBMS, and there are reasons to believe that specialized database engines are needed

56. 2011-11-22 - SLIDE 56IS 257 – Fall 2011 Will it be an RDBMS RDBMS will still be used for what they are best at – business-type high transaction data But specialized DBMS will be used for many other applications Consider Oracle’s recent acquisions of SleepyCat (BerkeleyDB) embedded database engine, and TimesTen main memory database engine –specialized database engines for specific applications

57. 2011-11-22 - SLIDE 57IS 257 – Fall 2011 Some things to consider Bandwidth will keep increasing and getting cheaper (and go wireless) Processing power will keep increasing –Moore’s law: Number of circuits on the most advanced semiconductors doubling every 18 months –With multicore chips, all computing is becoming parallel computing Memory and Storage will keep getting cheaper (and probably smaller) –“Storage law”: Worldwide digital data storage capacity has doubled every 9 months for the past decade

58. 2011-11-22 - SLIDE 58IS 257 – Fall 2011 Put it all together and what do you have? –“The ideal database machine would have a single infinitely fast processor with infinite memory with infinite bandwidth – and it would be infinitely cheap (free)” : David DeWitt and Jim Gray, 1992 Today it is more likely to be thousands of commodity machines running in parallel (using Hadoop, for example) with very fast networking between them (but it is definitely not free)

59. 2011-11-22 - SLIDE 59IS 257 – Fall 2011 The Claremont Report 2008 The group sees a “Turning Point in Database Research” –Current Environment –Research Opportunities –Moving Forward

60. 2011-11-22 - SLIDE 60IS 257 – Fall 2011 Current Environment “Big Data” is becoming ubiquitous in many fields –enterprise applications –Web tasks –E-Science –Digital entertainment –Natural Language Processing (esp. for Humanities applications) –Social Network analysis –Etc.

61. 2011-11-22 - SLIDE 61IS 257 – Fall 2011 Current Environment Data Analysis as a profit center –No longer just a cost – may be the entire business as in Business Intelligence

62. 2011-11-22 - SLIDE 62IS 257 – Fall 2011 Current Environment Ubiquity of Structured and Unstructured data –Text –XML –Web Data –Crawling the Deep Web How to extract useful information from “noisy” text and structured corpora?

63. 2011-11-22 - SLIDE 63IS 257 – Fall 2011 Current Environment Expanded developer demands –Wider use means broader requirements, and less interest from developers in the details of traditional DBMS interactions Architectural Shifts in Computing –The move to parallel architectures both internally (on individual chips) –And externally – Cloud Computing/Grid Computing

64. 2011-11-22 - SLIDE 64IS 257 – Fall 2011 Research Opportunities Revisiting Database Engines –Do DBMS need a redesign from the ground up to accommodate the new demands of the current environment?

65. 2011-11-22 - SLIDE 65IS 257 – Fall 2011 Research Opportunities-DB engines Designing systems for clusters of many- core processors Exploiting RAM and Flash as persistent media, rather than relying on magnetic disk Continuous self-tuning of DBMS systems Encryption and Compression Supporting non-relation data models –instead of “shoe-horning” them into tables

66. 2011-11-22 - SLIDE 66IS 257 – Fall 2011 Research Opportunities-DB engines Trading off consistency and availability for better performance and scaleout to thousands of machines Designing power-aware DBMS that limit energy costs without sacrificing scalability

67. 2011-11-22 - SLIDE 67IS 257 – Fall 2011 Research Opportunities-Programming Declarative Programming for Emerging Platforms –MapReduce –Ruby on Rails –Workflows

68. 2011-11-22 - SLIDE 68IS 257 – Fall 2011 Research Opportunities-Data The Interplay of Structured and Unstructured Data –Extracting Structure automatically –Contextual awareness –Combining with IR research and Machine Learning

69. 2011-11-22 - SLIDE 69IS 257 – Fall 2011 Research Opportunities - Cloud Cloud Data Services –New models for “shared data” servers –Learning from Grid Computing SRB/IRODS, etc. –Hadoop - as mentioned earlier - is open source and freely available software from Apache for running massively parallel computation (and distributed storage)

70. 2011-11-22 - SLIDE 70IS 257 – Fall 2011 Research Opportunities - Mobile Mobile Applications and Virtual Worlds –Need for real-time services combining massive amounts of user-generated data

71. 2011-11-22 - SLIDE 71IS 257 – Fall 2011 Moving forward Establishing large-scale collaborative projects to address these research opportunities What will be the result?

72. 2011-11-22 - SLIDE 72IS 257 – Fall 2011 ?