数据库架构的革命.pdf

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The Revolution in Database Architecture

Jim Gray

Microsoft Research

March 2004

Technical Report

MSR-TR-2004-31

Microsoft Research

Microsoft Corporation

One Microsoft Way

Redmond, WA 98052

The Revolution in Database Architecture

Jim Gray

Microsoft

455 Market St. #1650

San Francisco, CA, 94105 USA

http://research.microsoft.com/~Gray

Gray@Microsoft.com

ABSTRACT

Database system architectures are undergoing revolutionary

changes. Most importantly, algorithms and data are being unified

by integrating programming languages with the database system.

This gives an extensible object-relational system where non-

procedural relational operators manipulate object sets. Coupled

with this, each DBMS is now a web service. This has huge impli-

cations for how we structure applications. DBMSs are now object

containers. Queues are the first objects to be added. These queues

are the basis for transaction processing and workflow applica-

tions. Future workflow systems are likely to be built on this core.

Data cubes and online analytic processing are now baked into

most DBMSs. Beyond that, DBMSs have a framework for data

mining and machine learning algorithms. Decision trees, Bayes

nets, clustering, and time series analysis are built in; new algo-

rithms can be added. There is a rebirth of column stores for sparse

tables and to optimize bandwidth. Text, temporal, and spatial

data access methods, along with their probabilistic reasoning have

been added to database systems. Allowing approximate and prob-

abilistic answers is essential for many applications. Many believe

that XML and xQuery will be the main data structure and access

pattern. Database systems must accommodate that perspective.

External data increasingly arrives as streams to be compared to

historical data; so stream-processing operators are being added to

the DBMS. Publish-subscribe systems invert the data-query ra-

tios; incoming data is compared against millions of queries rather

than queries searching millions of records. Meanwhile, disk and

memory capacities are growing much faster than their bandwidth

and latency, so the database systems increasingly use huge main

memories and sequential disk access. These changes mandate a

much more dynamic query optimization strategy – one that adapts

to current conditions and selectivities rather than having a static

plan. Intelligence is moving to the periphery of the network.

Each disk and each sensor will be a competent database machine.

Relational algebra is a convenient way to program these systems.

Database systems are now expected to be self-managing, self-

healing, and always-up. We researchers and developers have our

work cut out for us in delivering all these features.

1. INTRODUCTION

This is an extended abstract for a SIGMOD 2004 keynote address.

It argues that databases are emerging from a period of relative

stasis where the agenda was “implement SQL better.” Now data-

base architectures are in the punctuated stage of punctuated-

equilibrium. They have become the vehicles to deliver an inte-

grated application development environment, to be data-rich

nodes of the Internet, to do data discovery, and to be self-

managing. They are also our main hope to deal with the informa-

tion avalanche hitting individuals, organizations, and all aspects

of human organization. It is an exciting time! There are many

exciting new research problems and many challenging implemen-

tation problems. This talk highlights some of them.

2. THE REVOLUTIONS

2.1 Object Relational Arrives

We be data. But, you cannot separate data and algorithms. Un-

fortunately, Cobol has a data division and a procedure division

and so it had separate committees to define each one. The data-

base community inherited that artificial division from the Cobol

Data Base Task Group (DBTG). We were separated from our

procedural twin at birth. We have been trying to reunite with it

for 40 years now. In the mid-eighties stored procedures were

added to SQL (thank you Sybase), and there was a proliferation of

object-relational database systems. In the mid-nineties many SQL

vendors added objects to their own systems. Although these were

each good efforts, they were fundamentally flawed because de

novo language designs are very high risk.

The object-oriented language community has been refining its

ideas since Simula67. There are now several good OO languages

with excellent implementations and development environments

(Java and C# for example.) There is a common language runtime

that supports nearly all languages with good performance.

The big news now is the marriage of databases and these lan-

guages. The runtimes are being added to the database engine so

that now one can write database stored-procedures (modules) in

these languages and can define database objects as classes in these

languages. Database data can be encapsulated in classes and the

language development environment allows you to program and

debug SQL seamlessly mixing Java or C# with SQL, doing ver-

sion control on the programs, and generally providing a very pro-

ductive programming environment. SQLJ is a very nice integra-

tion of SQL and Java, but there are even better ideas in the pipe-

line.

This integration of languages with databases eliminates the inside-

the-database outside-the-database dichotomy that we have lived

with for the last 40 years. Now fields are objects (values or refer-

ences); records are vectors of objects (fields); and tables are se-

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SIGMOD 2004, June 13–18, 2004, Paris, France.