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Future of Database Systems 2: XML Databases and Grid-based Digital Libraries. University of California, Berkeley School of Information Management and Systems SIMS 257: Database Management. Lecture Outline. Review Future of Database Systems XML and DBMS Grid-Based Digital Libraries

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Future of database systems 2 xml databases and grid based digital libraries

Future of Database Systems 2: XML Databases and Grid-based Digital Libraries

University of California, Berkeley

School of Information Management and Systems

SIMS 257: Database Management


Lecture outline

Lecture Outline

  • Review

    • Future of Database Systems

  • XML and DBMS

  • Grid-Based Digital Libraries

    • Data Grids

    • Grid-based IR

  • DBMS and usability


Lecture outline1

Lecture Outline

  • Review

    • Future of Database Systems

  • XML and DBMS

  • Grid-Based Digital Libraries

    • Data Grids

    • Grid-based IR

  • DBMS and usability


Future of database systems 2 xml databases and grid based digital libraries

  • Radio has no future, Heavier-than-air flying machines are impossible. X-rays will prove to be a hoax.

    • William Thompson (Lord Kelvin), 1899


Future of database systems 2 xml databases and grid based digital libraries

  • 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


Future of database systems 2 xml databases and grid based digital libraries

  • I think there is a world market for maybe five computers

    • Thomas Watson, Chair of IBM, 1943


Future of database systems 2 xml databases and grid based digital libraries

  • By the turn of this century, we will live in a paperless society.

    • Roger Smith, Chair of GM, 1986


Future of database systems 2 xml databases and grid based digital libraries

  • I predict the internet… will go spectacularly supernova and in 1996 catastrophically collapse.

    • Bob Metcalfe (3-Com founder and inventor of ethernet), 1995


Accomplishments of dbms research

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


Next generation database systems

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...


Examples

Examples

  • NASA EOSDIS

    • Estimated 1016 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


New features

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

  • Heterogeneous Databases

  • Memory Only DBMS


Coming to a database near you

Coming to a Database Near You…

  • Browsibility

  • User-defined access methods

  • Security

  • Steering Long processes

  • Federated Databases

  • IR capabilities

  • XML

  • The Semantic Web(?)


Some things to consider

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

  • 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

  • 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


Lecture outline2

Lecture Outline

  • Review

    • Future of Database Systems

  • XML and DBMS

  • Grid-Based Digital Libraries

    • Data Grids

    • Grid-based IR

  • DBMS and usability


Standards xml sql

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


Standards xml sql1

Standards: XML/SQL

  • That table can be mapped to: <EMPLOYEE> <row><EMPNO>000020</EMPNO> <FIRSTNAME>John</FIRSTNAME> <LASTNAME>Smith</LASTNAME> <BIRTHDATE>1955-08-21</BIRTHDATE> <SALARY>52300.00</SALARY> </row>

    <row> … etc. …


Standards xml sql2

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.

  • Don’t know whether this has actually been implemented by anyone

    • There is actually something very similar in the Cheshire II interface to RDBMS


Lecture outline3

Lecture Outline

  • Review

    • Future of Database Systems

  • XML and DBMS

  • Grid-Based Digital Libraries

    • Data Grids

    • Grid-based IR

  • DBMS and usability


Grid based digital libraries

Grid-based Digital Libraries

  • So what’s this Grid thing anyhow?

  • Data Grids and Distributed Storage

  • Grid-Based IR

  • Grid-Based Digital Libraries

    This lecture borrows heavily from presentations by Ian Foster (Argonne National Laboratory & University of Chicago), Reagan Moore and others from San Diego Supercomputer Center


The grid on demand access to electricity

The Grid: On-Demand Access to Electricity

Quality, economies of scale

Time

Source: Ian Foster


By analogy a computing grid

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


Not exactly a new idea

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


But things are different now

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


Computing isn t really like electricity

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


Why the grid 1 revolution in science

Why the Grid?(1) Revolution in Science

  • Pre-Internet

    • Theorize &/or experiment, aloneor 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


Why the grid 2 revolution in business

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


New opportunities demand new technology

“Resource sharing & coordinated problem solving in dynamic, multi-institutional virtual organizations”

New OpportunitiesDemand New Technology

Source: Ian Foster


Building an open grid

Building an Open Grid


Building an open grid1

Building an Open Grid

Open

Standards


Building an open grid2

Building an Open Grid

Open

Standards

Open

Source


Building an open grid3

Building an Open Grid

Open

Standards

Open

Source

Open

Infrastructure


Building an open grid4

Building an Open Grid

Open

Standards

Open

Grid

Open

Source

Open

Infrastructure


Building an open grid5

Building an Open Grid

Open

Standards

Open

Grid

Open

Source

Open

Infrastructure


Grids and open standards

Grids and Open Standards

Open Grid

Services Arch

Web services

GGF: OGSI, …

(+ OASIS, W3C)

Multiple implementations,

including Globus Toolkit

X.509,

LDAP,

FTP, …

Globus Toolkit

Defacto standards

GGF: GridFTP, GSI

App-specific

Services

Increased functionality,

standardization

Custom

solutions

Time


Open grid services architecture

Open Grid Services Architecture

  • Service-oriented architecture

    • Key to virtualization, discovery, composition, local-remote transparency

  • Leverage industry standards

    • Internet, Web services

  • Distributed service management

    • A “component model for Web services”

  • A framework for the definition of composable, interoperable services

“The Physiology of the Grid: An Open Grid Services Architecture for Distributed Systems Integration”, Foster, Kesselman, Nick, Tuecke, 2002


Realizing a service oriented architecture how do i

Realizing a Service-Oriented Architecture: How Do I

  • Create, name, manage, discover services?

  • Render resources, data, sensors as services?

  • Negotiate service level agreements?

  • Express & negotiate policy?

  • Organize & manage service collections?

  • Establish identity, negotiate authentication?

  • Manage VO membership & communication?

  • Compose services efficiently?

  • Achieve interoperability?


Web services

Web Services

  • XML-based distributed computing technology

  • Web service = a server process that exposes typed ports to the network

  • Described by the Web Services Definition Language, an XML document that contains

    • Type of message(s) the service understands & types of responses & exceptions it returns

    • “Methods” bound together as “port types”

    • Port types bound to protocols as “ports”

  • A WSDL document completely defines a service and how to access it


Open grid services infrastructure

Open Grid Services Infrastructure

Client

  • Introspection:

  • What port types?

  • What policy?

  • What state?

GridService

(required)

Other standard interfaces:

factory,

notification,

collections

Grid Service

Handle

Service

data

element

Service

data

element

Service

data

element

handle

resolution

Grid Service

Reference

  • Lifetime management

  • Explicit destruction

  • Soft-state lifetime

Data

access

Implementation

Hosting environment/runtime

(“C”, J2EE, .NET, …)


The grid as enabler of 21st century science

The Gridas Enabler of 21st Century Science

  • Entirely new approaches to enquiry based on

    • Deep analysis of huge quantities of data

    • Interdisciplinary collaboration

    • Large-scale simulation

    • Smart instrumentation

  • Enabled by an infrastructure that enables access to, and integration of, resources & services without regard for location


Grid infrastructure

Grid Infrastructure

  • Broadly deployed services in support of fundamental collaborative activities

    • Formation & operation of virtual organizations

    • Authentication, authorization, discovery, …

  • Services, software, and policies enabling on-demand access to critical resources

    • Computers, databases, networks, storage, software services,…

  • Operational support for 24x7 availability

  • Integration with campus and commercial infrastructures


The foundations are being laid

The Foundations are Being Laid

Edinburgh

Glasgow

DL

Newcastle

Belfast

Manchester

Cambridge

Oxford

Hinxton

RAL

Cardiff

London

Soton

Tier0/1 facility

Tier2 facility

Tier3 facility

10 Gbps link

2.5 Gbps link

622 Mbps link

Other link


Data grid problem

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


Data grids for high energy physics

Data Grids forHigh Energy Physics

~PBytes/sec

~100 MBytes/sec

Offline Processor Farm

~20 TIPS

There is a “bunch crossing” every 25 nsecs.

There are 100 “triggers” per second

Each triggered event is ~1 MByte in size

~100 MBytes/sec

Online System

Tier 0

CERN Computer Centre

~622 Mbits/sec or Air Freight (deprecated)

Tier 1

FermiLab ~4 TIPS

France Regional Centre

Germany Regional Centre

Italy Regional Centre

~622 Mbits/sec

Tier 2

Tier2 Centre ~1 TIPS

Tier2 Centre ~1 TIPS

Caltech ~1 TIPS

Tier2 Centre ~1 TIPS

Tier2 Centre ~1 TIPS

HPSS

HPSS

HPSS

HPSS

HPSS

~622 Mbits/sec

Institute ~0.25TIPS

Institute

Institute

Institute

Physics data cache

~1 MBytes/sec

1 TIPS is approximately 25,000

SpecInt95 equivalents

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

Pentium II 300 MHz

Pentium II 300 MHz

Pentium II 300 MHz

Pentium II 300 MHz

Tier 4

Physicist workstations

Image courtesy Harvey Newman, Caltech


Data intensive issues include

Data Intensive Issues Include …

  • Harness [potentially large numbers of] data, storage, network resources located in distinct administrative domains

  • Respect local and global policies governing what can be used for what

  • Schedule resources efficiently, again subject to local and global constraints

  • Achieve high performance, with respect to both speed and reliability

  • Catalog software and virtual data


Data intensive computing and grids

Data Intensive Computing and Grids

  • The term “Data Grid” is often used

    • Implies a distinct infrastructure, which it isn’t; but easy to say

  • Data-intensive computing shares numerous requirements with collaboration, instrumentation, computation, …

    • Security, resource mgt, info services, etc.

  • Important to exploit commonalities as very unlikely that multiple infrastructures can be maintained

  • Fortunately this seems easy to do!


Examples of desired data grid functionality

Examples ofDesired Data Grid Functionality

  • High-speed, reliable access to remote data

  • Automated discovery of “best” copy of data

  • Manage replication to improve performance

  • Co-schedule compute, storage, network

  • “Transparency” wrt delivered performance

  • Enforce access control on data

  • Allow representation of “global” resource allocation policies


A model architecture for data grids

A Model Architecture for Data Grids

Attribute Specification

Replica Catalog

Metadata Catalog

Application

Multiple Locations

Logical Collection and Logical File Name

MDS

Selected

Replica

Replica

Selection

Performance

Information &

Predictions

NWS

GridFTP Control Channel

Disk Cache

GridFTPDataChannel

TapeLibrary

Disk Array

Disk Cache

Replica Location 1

Replica Location 2

Replica Location 3

Source: Arcot Rajasekar (SDSC)


Data grid requirements

Data Grid Requirements

  • Seamless access to data and information stored at local and remote sites

  • Virtualization of data, collection and meta information

  • Handle Dataset Scaling – size & number

  • Integrate Data Collections & Associated Metadata

  • Handle Multiplicity of Platforms, Resource & Data Types

  • Handle Seamless Authentication

  • Handle Access Control

  • Provide Auditing Facilities

  • Handle Legacy Data & Methods

Source: Arcot Rajasekar (SDSC)


Srb as a solution

SRB as a Solution

Distributed Storage Resources

(database systems, archival storage systems, file systems, ftp, http, …)

  • The Storage Resource Broker is a middleware

  • It virtualizes resource access

  • It mediates access to distributed heterogeneous resources

  • It uses a MetaCATalog to facilitate the brokering

  • It integrates data and metadata

MCAT

Application

SRB Server

HRM DB2, Oracle, Illustra, ObjectStore

HPSS, ADSM, UniTree

UNIX, NTFS, HTTP, FTP

Source: Arcot Rajasekar (SDSC)


Sdsc storage resource broker meta data catalog

SDSC Storage Resource Broker & Meta-data Catalog

Application

Resource,

User

Java, NT

Browsers

Prolog

Python

C, C++,

Linux I/O

Unix

Shell

Third-party

copy

Web

User

Defined

SRB

Remote

Proxies

MCAT

Databases

DB2, Oracle,

Sybase

Archives

HPSS, ADSM,

UniTree, DMF

File Systems

Unix, NT,

Mac OSX

HRM

Dublin

Core

DataCutter

Application

Meta-data

Source: Arcot Rajasekar (SDSC)


Srb single signon

SRB Single SignOn

Authentication

Secure Password, GSI or SEA

Application

Session Established

1

(Host,port)

Identification & Initialization

SRB

Master

(port)

2

4

Server spawned

3

MCAT

SRB agents

3

CA

Source: Arcot Rajasekar (SDSC)


Federated srb operation

Federated SRB Operation

Peer-to-peer Brokering

Read Application

Parallel Data Access

Logical Name

Or

Attribute Condition

1

6

5/6

SRB

server

SRB

server

3

4

5

SRB agent

SRB agent

2

Server(s) Spawning

R1

MCAT

1.Logical-to-Physical mapping

2. Identification of Replicas

3.Access & Audit Control

R2

Data Access

Source: Arcot Rajasekar (SDSC)


Srb concepts

SRB Concepts

  • Abstraction of User Space

    • Single sign-on

    • Multiple authentication schemes

      • certificates, (secure) passwords, tickets, group permissions, roles

  • Virtualization of Resources

    • Resource Location, Type & Access transparency

    • Logical Resource Definitions - bundling

  • Abstraction of Data and Collections

    • Virtual Collections: Persistent Identifier and Global Name Space

    • Replication & Segmentation

  • Data Discovery – system & application metadata

    • User-defined Metadata – Structural & Descriptive

    • Attribute-based Access (path names become irrelevant)

  • Uniform Access Methods

    • APIs, Command Line, GUI Browsers, Web-Access (Portal,WSDL, CGI)

    • Parallel Access with both Client and Server-driven strategies

Source: Arcot Rajasekar (SDSC)


Oceanstore everyone s data one big utility

OceanStore:Everyone’s data, One big Utility

OStore

“The data is just out there”

  • Separate information from location

    • Locality is an only an optimization (an important one!)

    • Wide-scale coding and replication for durability

  • All information is globally identified

    • Unique identifiers are hashes over names & keys

    • Single uniform lookup interface replaces: DNS, server location, data location

    • No centralized namespace required (such as SDSI)

Source: John Kubiatowicz (UCB)


Basic structure irregular mesh of pools

Basic Structure:Irregular Mesh of “Pools”

OStore

Source: John Kubiatowicz (UCB)


Amusing back of the envelope calculation

Amusing back of the envelope calculation

OStore

  • How many files in the OceanStore?

    • Assume 1010 people in world

    • Say 10,000 files/person (very conservative?)

    • So 1014 files in OceanStore!

    • If 1 gig files (not likely), get 1 mole of files!

  • Truly impressive number of elements…

  • … but small relative to physical constants

    • (courtesy Bill Bolotsky, Microsoft)

Source: John Kubiatowicz (UCB)


Utility based infrastructure

Utility-based Infrastructure

OStore

Canadian

OceanStore

  • Service provided by confederation of companies

    • Monthly fee paid to one service provider

    • Companies buy and sell capacity from each other

Sprint

AT&T

IBM

Pac

Bell

IBM

Source: John Kubiatowicz (UCB)


Lecture outline4

Lecture Outline

  • Review

    • Future of Database Systems

  • Grid-Based Digital Libraries

    • Data Grids

    • Grid-based IR

  • DBMS and usability


Dbms and usability

DBMS and Usability

  • What features would you like to see in DBMS?


Dbms and usability1

DBMS and Usability

  • What do you hate about Database Management Systems?

    • From your experiences

    • In general

  • What do you like about Database Management Systems?

    • From your experience

    • In general


Next week

Next Week

  • Workshops to help you develop the final reports and presentations.


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