database.sarang.net
UserID
Passwd
Database
DBMS
MySQL
PostgreSQL
Firebird
ㆍOracle
Informix
Sybase
MS-SQL
DB2
Cache
CUBRID
LDAP
ALTIBASE
Tibero
DB 문서들
스터디
Community
공지사항
자유게시판
구인|구직
DSN 갤러리
도움주신분들
Admin
운영게시판
최근게시물
Oracle Files 15738 게시물 읽기
 News | Q&A | Columns | Tutorials | Devel | Files | Links
No. 15738
The Datacycle Architecture for Very High Throughput Database Systems
작성자
정재익(advance)
작성일
2003-09-29 07:42
조회수
7,316
첨부파일
파일이름크기Info 
The_Datacycle_Architecutre_for_Very_High_Throughput_Database_Systems.pdf979.01 KB  

The Datacycle Architecture for Very High Throughput Database Systems
Gary Herman, Gtta Gopal, K C Lee, and Abel Wemnb
Bell Commumcanons Research, Inc
435 South Street, Momstown, NJ 07960-1961

ABSTRACT

The evolunonary trend toward a database-drtven pubhc commumcanons
network has mottvated research mto database architectures
capable of executing thousands of transacnonsper
second In th paper we mtroa!uce the Datacycle archUecture,
an attempt to expht the enormous transmtsswn bandwuith of
optical systems to penmt the unplementatwn of lugh throughput
m&processor database systems The architecture has the
potent&for unlmuted query throughput, sunplzfied data management,
rapid execution of complex quenes, and t$ictent
concurrency control We a&r&e the logtcal operatron of the
architecture and discuss vnplementatton tssues tn the context
of a prototype system currently under constructaon

1 INTRODUCTION

In thts paper, we mtroduce the Datacycle architecture, a novel
system concept which we beheve can pemnt the Implementaaon
of very high transaction throughput database systems
Our research mto high throughput systems is monvated by the
srchltectural evolutton of the Umted States pubhc telephone
network toward a fully database-drwen network In such a
network, a smgle, log~ally mtegrated database would be. consulted
dunng call processmg to estabhsh caller percussions,
perform name-address lranslatlons, execute feature logX, establish
routes, etc In today’s network, centralized databases
are consulted only for a small fraction of calls, for example, to
seek authorzanon to complete the call by vahdatmg a cm&
card number or to obtam routmg mstruchons spectic to a g~ven
call, as m an “800” call attempt In the future, we foresee a
network where access to a global network database 1s the norm
m call processmg, rather than the exception
The database technology challenge posed by thts view of the
architecture of the public network 1s one of enormous transacnon
volume To promde 800 SeMce, each database node m
today’s pubhc network [She1821 receives approxnnately 100
sunple queues per second on its copy of a database of a few
hundred thousand records Each record 1s accessed by a
PermIssIon to copy wlthout fee all or part of this material IS granted
provided that the copies are not made or dlstrlbuted for direct
commercial advantage, the ACM copyrlght notlce and the title of
the pubhcatlon and its date appear, and notlce IS given that copymg
IS by permlsslon of the Assoclatlon for Computmg Machmery To
copy otherwlse, or to repubhsh, reqmres a fee and/or specfic
permission
@ 1987 ACM 0-89791-236-5/S7/~5/~g7 75~
smgle key, updates are batched and executed pencd~ally In
OUT mew of the future network archlttecture, processors m the
network execute tens of thousands of transactlOns per second,
some quite complex, accessmg databases contammg tens of
rmlhons of records, and accommodatmg unpmitctable quenes
and random updates while prov&ng consistent mews to all
users With the current throughput of general purpose
database systems hmtted to below 1000 transacnons per second
[Gray85], database systems with the performance charactermcs
reqmred by dus view of network a~httectme do not
appear achievable by convenhonal architectures
Our approach to actievmg the reqmred throughput seeks to
exploit opportumues created by advances m pmcessmg and
commurucattons technologes Other recent proposals for new
database machmes have taken a smnlar approach, e g ,
through dense, mexpensive sermconductor memory m the
Massive Memory Machme [Garc84] or through massive parallelism
m VLSI m NON-VON [Hill861 Whtle the Datacycle
architecture also depends on VLSI technolo@es, the pnmary
motwatton for our approach is the abundance of inexpensive
commumcattons bandwtdth wluch has become avadable
through optuzal communications systems The Datacycle architecture
is commumctions mtensive, shmulated by the hypothesis
that If costs for commumcauons bandmdth become
small, commumca~ons, pmcessmg and storage architectures
for database systems should be reassessed Bandmdth abundance
pemuts xepemve broadcast of the enare contents of the
database to many pmcessmg elements, avo&ng I/O bottlenecks,
sunphfymg data admuustration, and achlevmg efficient
concurrency control

2 OVERVIEW OF THE DATACYCLE

ARCHITECTURE

As m&cated, the strategy m the Datacycle arch&cture 1s to
broadcast database contents over a very high bandw&h me&-
urn to a mulmude of “hstemng” processors that observe the
stream m parallel and use haxdware filters to extract the mformanon
relevant to the transactions pendtng locally As flustrated
conceptually m Figure 1, the entne contents of the
database arc read sequentially from the storage pump,
broadcast repeatedly over the broadcast transmission
channel, and observed passively and mdependently by many
record access managers, each of which may copy records
of local mtetest Each access manager is associated wtth a
general purpose computmg system, or host, on which apphcanons
reside Transactions on a host request database operahens
through a well-defined mterface ~nth an associated access
manager The record access manager decomposes each
requested operation mto a set of speclficanons to be used to
identify relevant records when they appear on the broadcast
97
u Broadcast Trmsmlsslon Chantwl
Rword
storage
b
Pump
I I
Host Host
. . . Host
Flgure 1. The Datacycle Architecture I
channel, processes the records to complete the database operahon,
and returns the results to the host. To complete a transactton
and update the database, the host subnuts an update/
comnut request to the access manager Using the upstream
network, the access manager sends the update request
to the record update manager, which executes a nonconfhctmg
subset of the update requests received m a cycle
The access manager subsequently momtors the database to
determme If the update attempt was successful and noties the
host. In addmon, the access manager can utihze the hardware
IDONtOMg capatity to decentrahze much of the conflict detection
overhead 111 concurrency control For example, urlth
“optnms~c” concurrency control, the assoclated access
manager can momtor the transacQon’s read set to detect potent&
contkts due to transactions comuuttmg elsewhere m the system
The Datacycle archtectu~ has smnlanties with mformation
&stnbutton architectures hke teletext [Slge80] and the MlT
Community Information System [Gtif85], which employ
broadcast of small databases or database updates to many receivmg
stations However, these systems are text-onented,
typically &smbute relatively small amounts of data, and have
relatively large access ms to a gven data item Further, they
do not deal urlth the issues of updates mgmatmg at the receivmg
stations, transaction management, and query processmg


III the tradmonal database sense

In a database machme context, hardware filtermg and broadcamng
of data to allemate the I/O bottleneck and to pemnt parallel
access to data have been suggested before For example,
N [Le1178], the data stream IS searched “on the fly” as it is read
from &sks with parallel read heads In DIRECT @%Wl79]
selected pages of the database are bmadcast repetlttvely to
mulhple query processors This broadcast feature 1s uhhzed,
for example, m a nested-loop ~oln algorithm for query processing
In contrast to these systems, the hardware filtermg
capabtity and the repehhve broadcast of the entne database 111
the Datacycle archlttecture are mtegral to both query processmg
and transaction management functions such as concurrency
control

The Datacycle architecture has several strengths No central
I/O bottleneck eusts for record remeval, regardless of the
number of processmg elements re+nred to handle the transacnon
load. Since the enme database can be searched on the fly,
a pmn knowledge of the precise location of each record m the
database should not be necessary Therefore, the overhead
nqnrcd for mamtanung a -tory can be ehmmated, the
system 1s potentially fully content-addressable Further, the
content-addressab&y and repetmve broadcast charactensucs
of the architecture lend themselves to effiaent execution of
complex quenes, such as JOIIIS These same archItectural features
perrmt efficient concurrency control mechamsms when
transactions ullsh to mod& the contents of the database Because
record access mana@ read data and attempt wntes
(updates) w&out exuhat commumca~ons among themselves,
i&cur&c y control bverhead depends only on the volume of
transachons and does not depend on the number of access
managers (and hosts) provided to handle the transactton volume
The Datacycle approach provides an opportu~ty to
achieve high throughput, efficient execution of complex
quenes, and efficient concurrency contml m a system with
many dlsmbuted processors
An assessment of avadable commumcanons, storage, and
processmg technolo@es mdcates that the Datacycle archltecture
1s techmcally plausible Transnusslon systems employmg
electromc mcdulahon of sermconductor lasers at rates m excess
of one glgabt per second are avadable commercially today
Wavelength &-Ion mulhplexors which can multiplex
thi outputs of &teen such laseri onto a smgle optical fiber are
also avtiable Thus, with current technoloav. several glgabytes
of data can be &ansm~tted over a smgl~&trcal fiber m
l&s than a second Transnusslon technol;gy & advancmg
ramdlv, and, ~rlth the uronuse of future coherent opt& techm&
e&the iforrnatioi capacity of a smgle fiber w-dl be measured
in terabits per second
Smce storage access to support the broadcast funchon 1s sequenhal
and synchronous, smular to the output of a v&o
frame buffer, creation of the appropnate read and wnte band-
Hrldths to storage should be prunanly an engmeenng problem
For example, 111 the case of senuconductor memmes, word
Hndth, bank mterleavmg schemes, parallel to senal conversion,
and multlplexmg technologes can be chosen to acheve
the desmA broadcast data rate With the avadablllty of 16
megabit memory parts, one ggabyte of memory will occupy
less than a smgle shelf
Finally, at each hstenmg pomt, the contents of the broadcast
stream must be exammed to ident@, and copy, data items relevant
to local transactions Because 111 the Datacycle archltecture
the hardware pattern comparison funcuon is mtegral to
both query processmg and concurrency control, Its efficient
lmplementanon is cntical to the prachcal apphcatity of the archltecture
Studies of VLSI nnnlementauon of selection hardware
[Faud85] are prormsmg, &Jectmg that VLSI technology
m the 1990’s wdl pernut implementahon of 200 to 500 comparators
per mtegrated cncmt, wth each comparator capable of
searching for a d&rent 256 byte pattern
In the remamder of dus paper, we descnbe the logical operahon
of the Datacycle architecture and &scuss unplementauon
issues m the context of an archrtecture prototype being built m
our laboratory Specifically, Sechon 3 provides an overview
of query handhng N the Datacycle archlttecture, with concurrency
control and recovery discussed m Sections 4 and 5
Section 6 describes our design for a prototype system. Fmally,
we conclude wtth a dlscusslon of the domam of apphcabillty
of the arclutectuxe and descnbe ongomg research on the
Datacycle approach to high throughput database systems
98

3. QUERY PROCESSING

Quenes are presented to a record access manager m a highlevel
database language such as SQL [Date861 W&m the
record access manager are many hardware pattern comparators
managed by a supervisory subsystem, compnsmg pmcessmg
elements, buffers, and an mterconnectlon network The supeMSOry
subsystem translates quenes mto selechon pntrntlves
that can be processed m the pattern comparator hardware The
pattern comparator accepts commands of the form
Select (data type) From (segment) For (request ld)
Where (expression)
The data type can be a record, or some fragment of a record,
the segment defines the subset of the broadcast channel (e g ,
subchannel or a fragment of a subchannel) to be searched, the
request Id associates the mstruaon with a specific query, the
expression defines the pattern to be matched and comists of
snnple boolean expressions relatmg the fields of a record and
constants through operations such as equals, greater than, etc
Using the select command to retum a field or a set of fields
from all records 111 a relahon nnplements a proJect capab&y
(without duphcate ehmmatlon) m hardware Duphcates must
be detected and removed at a higher level to complete the project
operahon To remeve d data items that satisfy some expression,
select commands reqmre up to one full cycle tnne of
the database to complete
The architecture penmts an efficient Join algomhm To perform
a Jam, m the first broadcast cycle of the database one
pattern comparator performs a hardware proJect over the JOUP
mg atmbute on the two relations to be ~olned The proJected
values are sent to the supe~sory subsystem where a data
structure 1s bmlt to mamtam a count of the number of tunes
each value appears m each of the two relations The data
structure can be an array If the domam of the JOUI atmbute is
known m advance and 1s relatively small Othemse, a hash
table can be used. Every value winch has non-zero count for
both relanons wfi take part in theJom, the count gves the Size
of the result exactly If enough pattern comparators are avadable,
the supervmxy subsystem loads pattern comparators
wth each value that wdl take part m the Join, and III the next
cycle all the desired records are retneved. The actual Join 1s
then performed III the supemsory subsystem If fewer pattern
comparators are aviulable, more cycles may be reqmred This
JOUI operahon resembles the ht array technique m [Babb79]
and the hardware-assisted semJom approach 111 [Faud85]
However, the hardware proJect capatity, the cychc nature of
data presentahon, and the content-addressable feature of the
Datacycle architecture penmt a pamcularly efficient nnplementahon
The algorithm has the potential to re.meve all the
records requred for a JOT in only two broadcast cycles

4. CONCURRENCY CONTROL

An effiiclent concurrency control mechamsm is cnncal to
achlevmg high throughput The concurrency control mechamsm
m the Datacycle architecture ensures database connstency,
pernuts record access managers to read and wnte the
database Hrlthout explicit cornmumcations among themselves,
and decentrahzes much of the confhct detecuon for update
transacnons
Concurrency control 1s precllcated on the assumptions that each
broadcast cycle of the database has a &stmct begmmng and
end and that the contents of the database w&m a smgle cycle
are guaranteed to be consistent That is, the record update
manager provides atomrc record updates for the writes of a
transacnon, no parhally completed updates are perrmtted m a
cycle Thus, an access manager can execute a read-only
minsacnon Hrlthout any concurrency control overhead at all, so
long as It reads all records withm a single cycle
However, some scheme must be used to control the concurrent
attempts of the various access managers to update the database
m the storage pump Most of the techmques to control snnultaneous,
mulhuser access to a smgle database fall mto three
categones - lockmg, tunestamps and cemfication [Bern811
Each of the three techmques has a domam of apphcab~lty. 1 e ,
there are transactton enwonments for which each techmque 1s
best smted. In envnonments where the number of data items
1s large compared to the number of transactions runnmg concurrently
and the probabtity of overlappmg transactions 1s
small (network apphcanons may fall mto dus category), the
overhead of grantmg locks or mamtammg tunestamps does not
seem Jumfiable In these cases cemfication schemes are expected
to pexform well The Datacycle arch&cttne pernuts an
efficient nnplementatlon of such a scheme, which 1s described
here
In general, update transactions include a read phase, an execubon
phase, and a comnut phase For the present, we consider
only transachons which complete their read phase w&m a
smgle cycle and, therefore, obtam a consistent read set In the
read phase of a transaction, the access manager mdependently
extracts remrds from the broadcast stream and mamtams Its
own hst of records 111 use, based on the records reqmred locally
Durmg the execuaon phase of a transation, the access
manager momtors the transachon’s read set For each record
on the local hst of records m use, the supemsory system in
the access manager mstructs the pattern comparator hardware
toscanthebroadcaststreamto&terrmneIftherecordhasbeen
changed (updated) smce it was ongmally read for the assocated
transaction With dus hardware testmg capahhty and the
RpetihVe broadcast of the database, the access manager can
detect any mod&ahon to a pendmg lransachon’s read set,
nonfy the host, and pass the new record values to the transacbon
Based on these new values, the transachon can abort,
back up, or contmue The declslon is smctly local Unhke
most cemfication schemes, the “cemficahon urlth momtormg”
scheme m the Datacycle arclntecture pernuts transactions to
abort as soon as a conflict 1s detected, reducmg processmg
wasted on already doomed transachons
An access manager has respon&hty for detectmg mterference
with a transachon’s read set from the begmnmg of the transacaon
through the cycle m winch a transac~on reaches its commt
phase and wshes to wnte to the database This cycle de
fines a local comnut tnnestamp Then, the access manager
sends an update request, mcludmg the new record values, the
idenhaes of records 111 the read set, and the comrmt tunestamp,
to the update manager
The update manager performs two types of central cemficahon
on the update requests it recewes Fast, it vahdates each request
agamst update requests gmnted m the recent past Some
latency wdl exist between the tune a locally cemfied transachon
generates an update request and the tune the results of the
update, If granted, actually appear m the database Consequently,
the update manager 1s responsible for detectmg update
attempts mvahdated by previously granted updates whose effects
appear m the database after the local comt hmestamp,
escapmg detecnon at the access manager Second, the update
manager also detects update requests that conflict with other
requests subnntted wrth the same tnnestamp The update
manager accepts a senahzable subset of attempts and mtcoduces
the changed records mto pump storage Fa&d attempts
are sunply &scarded by the update manager
Each access manager subsequently detemnn es whether the
tmnsactlons mth subnutted update requests have cormrutted
successfully by elthez mommrmg the actual data values or
examuung a porhon of the bandwidth used to broadcast a log
of commmed transactions Cornnut authorzitlon is then
retumed to the host
Extensions to this basic scheme for concurrency control are
described m [Gopa871 For example, multiversion optmusac
techmques for concurrency control can be apphed m the Datacycle
archtecture to pemut transactions to read over multiple
database cycles and to protie greater overall concurrency, as
well As ~nth the snnple optnmsac techmque described here,
the mulnversion approach decentrahzes much of the concurrency
control overhead and allows read-only transactions to
complete locally

5 FAILURE RECOVERY

Graceful and rapid recovery from subsystem fiulure 1s a reqmrement
for a practical database machme archtecture The
novel charactenstlcs of the Datacycle architecture provide conceptually
sunple mechanisms for recovery to a known consistent
state If component fdm occurs The update manager
and storage pump manage the enme database and must, therefore,
be made very xehable Because the costs of these central
subsystems are shared over the many record access managers,
tradmonal approaches to rehab&ty through redundancy should
be econormcal Redundancy can lead to qmck recovery, as
well For example, smce the database 1s consistent w&m a
cycle, the last complete cycle of the database (essenhally, a full
database checkpoint) nught be kept by a redundant “shadow”
pump Thus, while the Bctlve pump 1s transrmttmg cycle K+l,
the shadow pump retams the database of cycle K If the acnve
pump fds dunng cycle K+l. the “shadow” pump becomes
actwe, and the system “nzcovers” to the cycle K state If access
managers waUto see that the full broadcast cycle is completed
before authmg transachons to comnut, fa&ue of the
pump or transnussion channel dunng cycle K+l results m the
set of pendmg transactions rolhng back to the state exlstmg
followmg complehon of cycle K If cycle K+l completes
successfully, the shadow copy must then be updated to reflect
state K+l
Recovery from access manager fa&ue can also be relaavely
snnple Record access managers operate completely mdependently
of one anotheG even then connaon to the shared opocal
broadcast medmm 1s through passive taps Hence, the
fatlure of one access manager can have no effect on the others
Also, If one of these subsystems fads, requests whch would
normally be served by the faded access manager can be r&-
rected to other access managers, and the system as a whole
wll expenence httle degradation To recover from fadure of
an access manager ~rlth transactions m the phase between
comrmt request and cormmt authonzahon, the update manager
must mamtam a log of comrmtted transactions to be accessed
when the access manager recovers or the host 1s rehomed to a
new access manager

6 IMPLEMENTING THE DATACYCLE

ARCHITECTURE
We are currently constructmg a prototype of the Datacycle archltecture,
both to demonstrate technical feaslbdlty and to
serve as a vehicle for further research on the architecture Our
efforts m the first version of the prototype focus on the record
access manager, which we consider to be the crmcal subsystem
m the architecture, both m terms of functionahty and cost
Our strategy for the prototype emphasm% flexlbtity and ease
of Implementation over efficiency Nevertheless, the prototype
deslgu 1s mtended to consider the srgnlficant arc~tectural
issues to be addressed m Implementing a full scale system To
prowde an overview of the structure and scale of the Datacycle
prototype, we first bnefly descnbe the design of the transrmssion
channels, storage pump, and record update manager We
then descnbe our rationale and design for the record access
manager
Transmission Channels To allow for flexlhhty m the
total size of the database, Implementation of the pump and the
record access manager must be mdependent of the total transnussion
capacity pmwded m the broadcast channel The approach,
as dustrated m Figure 2,ls to multiplex together a
number of relahvely slow data streams from the pump, carry
out the transnussion at the higher aggregate rate, and then, at
each access manager, demultiplex the stream mto a number of
slower channels, each of which operates at a rate smtable for
the pattern comparator technology m the access managers A
need for more storage 1s accommodated by addmg a new storage
subsystem to the pump and new pattern comparamr subsystems
at each of the access managers Besides providmg
flexlbtity m database SUR, this approach also reduces the clock
rate reqmred ~nthm the pattern comparator ele.ctromcs
Record Access
Manager
Subsystems
3 + Host
Communlcatlons
Figure 2. The Datacycle Prototype

The database prototype uses frammg and transrms~ion elecrromcs
created for an expernnental broadband commumcations
system nnplemented m Bellcore [Hayw87] The basic subchannel
rate 1s 140 megalxts/second, accessible for readmg or
wnhng through a 17 5 megabyte/second byte parallel mterface
prowded by an mtegrated cucmt framer Up to sxteen such
subchannels feed cascaded 4 1 GaAs multiplexors to create an
aggregate 2 24 @gabit/second bit stream that modulates a
semconductor laser The outputs of sixteen lasers can be
mulnplexed optically onto one single mode ophcal fiber
Thus, the transrmssion technology avadable for the prototype
could transrmt a database of over four ggabytes m less than
one second over a smgle fiber Early versions of the prototype
wdl use 4 to 16 140 Mbps subchannels
In addmon to the pnmary broadcast channel, an upstream
channel is requu?d to transrmt record update requests from the
access managers to the record update manager In the snnple
version of the architecture presented here, this upstream channel
1s separate from the broadcast mednun and may be implemented
by any commumcanons network provldmg the requlred
funchonahty and performance In our prototype, upstream
commumcahons between access managers and the update
manager urlll be through EthemeP
EthemeiTM 1s a trademark of Xerox Corporation

Storage Pump. Implementahon of the record storage pump
IS driven by system tequnements for teadmg records from the
pump and transmmmg them onto the broadcast medmm, and
for wnhng new or altered records mto the pump storage to
update the database An evaluation of the two most popular
storage technologes today, movmg head magnetic &Sk and
senuconductor memory, m&cates that seuuconductor memory
1s a more appropnate choice for the storage pump apphcation
m terms of cost and design sunphclty The sustamable read
rate for most c ommerclal dnves-appmmtely 8 5
megabyte&c , mcludmg seeks, platter rotation, etc , m the
case of one high performance dnve [FuJi84+is too low relahve
to storage volume That IS, such a dnve can transmtt less
than 3% of its capactty m a second, m the Datacycle at&tecture,
the extra capacity IS wasted On the other hand, generatmg
the appropnate I/O bandwtdths for synchronous, sequenti
read access to senuconductor memory 1s a relatively
str~ghtforward design exercise The mayor disadvantage of
senuconductor memory as pnmary storage for a database apphcation
1s its volatity, which affects strateges for system
rehablhty and recovery (c f , [Hagm86])
In the Datacycle prototype, the storage pump wfi conust of a
number of 4 megabyte banks of sermconductor memory, with
each bank managed by a rmcroprocessor, as shown 111 Figure
3 Using a DMA-l&e address sequencer, each bank w& m
turn, create a 17 5 megabytes/secondata stream to feed the
framer mterface Dual-ported memory m each bank proties
the mechamsm for the update manager to promde new records
to pump storage and to mstruct the bank nucroprocessor to
delete old records The bank nucroprocessor 1s responsible
for mamtauung the memory bank as instructed by the update
manager Assummg that four tisy-chamed banks feed a smgle
framer, each 140 Mbps transnusslon subchannel broadcasts
16 megabytes repeated every 0 9 seconds At any tune
111 a broadcast cycle, only one fourth of the banks Hrlll be m
“broadcast” mode, m the other banks, the bank nucroprocessors
will be addmg and delehng records, perfonmng storage
housekeeping duties, etc

Figure 3 Prototype Pump and Update Manager

Record Update Manager. The update manager m the Datacycle
prototype is a general purpose n~croprocessor which
receives update requests from the access managers over a local
ma network and provides altered records to the cell
rmcroprocessors through shared memory The mmal algonthm
for resolvmg update i~nfhcts 1s snnply first-come, fiistserved
For each cycle, the update manager mamtams tables
for the read sets and wnte sets of granted updates Record IDS
of mcommg update requests are checked agamst the tables, If a
non-senahzable confhct 1s detected, the update 1s ignored. If
the atonucity of the update to storage can be guaranteed, it is
executed, and the tables are updated to mclude the new read
and wnte set If the update atomcity cannot be guaranteed,
due to lack of mne mmauung 111 the cycle, the update 1s lgnored.
Update throughput can be unproved, at the cost of delaymg
transaction completion, by allowmg one or more adds
honal broadcast cycles between update request and confirmanon
Thus, an update request subnutted dunng cycle K nught
be mtmduced m the database dunng cycle K+n. The update
manager has responsltity for &tecMg con&B between each
new update attempt and updates which were granted prev~-
ously but which were not vlslble to the access manager
The cnhcal design issue for the pump and update manager 1s
how to prom& the guarantee of atonnc updates for each transacnon
w&out constrammg the update throughput to too low a
level This is an area of current research that is clearly cnhcal
to the successful reahzahon of the archltectuxe
Record Access Manager. The access manager provides
its host or hosts Hrlth the functlonahty of a typical database
machme, decomposmg requests mto database pnmmves, asngnmg
the prnmtwes to pattern comparator hardware, and
then processmg the returned data items to generate the response,
as described m Secnon 3 The access manager slmultaneously
supervises the concurrency control process, one
mew of which was described m Section 4
The access manager 1s the focus for our mmal research because
of its novel use of both the pattern comparator hardware
and the repehtwe broadcast of the database contents for
database quenes and for concurrency control The atchlttecture
1s cnhcally dependent on the efficiency of the pattern companson
operation For example, a selectton may reqmre dedtcatmg
pattern comparators for an exhaustive search of every sub
channel of the database Momtormg for concurrency control
also mcxases the demand for pattern comparators, as do complex
quenes such as moms
If pattern comparator hardware Hrlth the nzqmred boolean
functions 1s capable of hundreds of smmltaneous compansons
per IC, as [Faud85] protects, then sunple, exhaustive seamh
strategtes are plausible On the other hand, If pattern comparators
are expensive, then more sophtshcated and haxdwareefficient
query pmcessmg, concurrency control, and content
searchmg smateges may be reqnned. For example, the aviulable
pattern comparators mtght be more efficiently used by
utthzmg the channel structure together ~rlth some mdexmg or
hashmg scheme so that only some of the channels need to be
searched for a smgle pattern Further, segments defined by
saons of tune on a channel can also be used m the mdexmg
Our prototype record access manager 1s deslgned to prowde us
an environment m which to expenment ~tb altemaave approaches
m unplementmg key functions m the Datacycle archltectme
In the Datacycle prototype, the access manager
consists of dlstmct subsystems, the Query Manager (QM).
Data Manager (DM), and Intelhgent Record Retneval Modules

(IRS). as shown m Figure 4 In the model of Section 3, the
QM and DM compnse the supe~sory subsystem, and the IRS
contam the pattern comparators

su orvlsory
Su system ki
I Host

Figure 4 Record Access Manager Prototype

The Query Manager receives quenes from a host, decomposes
those quenes mto operatmg pnmmves, and subnuts the prnmhves
to the DM for execution The Query Manager also manages
the updates for comnuttmg transactions, nutzatmg the update
request to the update manager and, m conJunction ~th the
DMs and IRS, confirmmg the success of the update In our
prototype nnplementatton, the QM IS a m -based rmcrocomputer
which communicates with the host and the update
manager usmg Ethernet
As shown m Figure 4, the Data Manager m the prototype conslsts
of multiple processing nodes connected to form a network
expandable to manage access to many broadcast subchannels
The DM maps the lognzal data space (based on relatton
names and field values) to the physical data space (based
on subchannels and subchannel segments), routes the prmutlves
to the appropnate IRS, buffers mtermdate results, and
routes the results of the pnmmve database operations to the
Query Manager
Fmally, each IR consists of a processor managmg four VLSI
pattern comparator umts that perform the low level search operanons
111 the archmzchue The pattern comparator ICs are
bem
8
designed for lmt~al rmplementation m 2 0 nucron
CM S Thev anaapated capatines mclude vanable length
pr&z.ates, capacity to store up to 150 (four byte) pticates on
UN&m 1s a trademark of AT&T Bell Laboratones
chip, a throughput of 20 rmlhon snnple pr&cate tests per second,
capabtity to evaluate snnple boolean expressions, and the
abfity to surltch between target patterns on database segment
boundanes Pattern comparator ICs receive data from the
hansnusslon subsystem over the 17 S megabyte per second
byte parallel interfaces provided by tier ICs

7. DISCUSSION

As a system concept, the Datacycle architecture has amcnve
charactenstlcs, both for our ongmal network apphcatlon and
as a general purpose database system St& the architecture
has hnutations and weaknesses, and both techmcal feaslbhty
and pract~ahty remam unproven In this section, we &scuss
our current view of the domam of apphcablllty of the archltecture
and Identify key open Issues and areas of current research
The archltectmz appears well sated for very high throughput,
read-onented apphcations m which transactions have relatively
small. predeclared read sets and wish to access a common
database through any of several keys The “database-driven
network” problem which motivated our research has these
charactenstlcs The maxnnum size of a database slutable for
the Datacycle approach 1s a SubJect of current mvestiganon, for
a fixed broadcast cycle tune, a larger database requires a higher
bandwdth channel and, consequently, either more pattern
comparators (to search more subchannels) or faster comparators
We databases of hundreds of megabytes appear xealzable
with sub-second access hmes using current transnusslon
technology, the dommant cost of a large database system usmg
the Datacycle archlttecture 1s the hardware cost of searchmg
Whde the Datacycle approach 1s “read-onented”, It 1s not a
“read-only” anhecttne hke teletext. Use of the repetmve
broadcast of the database to decentrahze con&t detection and
synchroNze the aCtIOnS of the many access managers is a key
feature of amh~tecture The ar&tectme should exhlbt excellent
update throughput when compared with convenuonsl archltectuxes
We the centrahzed update manager remams an
ulmte throughput bottleneck m the archlttecture for transachens
which write, as well as read, the database, we are mveshgatmg
archltecmres which &smbute the update certlfcatlon
funChOn to achieve even greater throughput, applymg the approach
of [wem87]
An issue III the Datacycle architecture 1s support for transactions
which have large read sets and/or extended execuhon
phases, such transachons may have &fficulty completmg successfully
To address dus Issue, we are explonng concurrency
control techmques wluch increase the propomon of trans.-
achons which complete successfully m a high conflict envlronment
[Gopa87] One approach is to employ a multiversion
scheme, penmthng consistent reads to occur over multiple cycles
and mcreasmg concurrency, at the cost of increased storage
and bandHrldth reqmrements Other approaches may exploit
the hardware momtormg capabtity at the access managers
to penmt finer grsnulanty for local vabdation, pnzhcate-based
vahdahon, and recovery from con&t by parhal transactron
backup
A weakness of the archltectunz 1s the access latency which results
from the synchronous, pen&c presentation of data
llus read latency adversely affects the system response hme
for transacnons that consist of a senes of dependent reads, that
1s. where each database read depends on the result of Its predecessor
A transachon with K such reads applied to a
database with cycle tune T can take KT or longer to complete
Two approaches may reduce this problem first, structure the
database and query processmg language to anticipate such
quenes, and, second, dnve down the cycle hme T AS before,

reducmg T reqmres a h@er bandwdth channel and more mvestment
m search hardware, 1 e , either more, or faster, pattern
comparators
The cost of the hardware pattern comparison operation 1s crmcal
to query processmg, database search strateges, and concurrency
control m the Datacycle architecture Through the
VLSI design achmty m our prototype, we are mveshgahng altemahve
approaches to achlevmg highly parallel selechon operahons
m VLSI, technolo@es to pernnt very high speed compansons
are also desuable, smce they pemut shortenmg the
database cycle tune and reducmg the number of subchannels
reqmred for very large databases We are also explormg techxnques
exploltmg a pnorr knowledge of the data placement m
subchannels and subchannel segments to utilze hardware pattern
comparators more efficiently, while retammg most of the
snnpllclty of data management prormsed by the content-addressable
feature of the archltecture
Research on query decomposlhon explores the dependency of
decomposmon strategy and access manager architecture on the
funchonahty and cost of the hardware seh?chon operahons
More funchonahty (e g , tid card capabhty, boolean exprcssions)
can reduce the pattern comparatofls speed or capacity
for sunultaneous searches On the other hand, less funchonahty
results in less efficient fitenng of the data stream, mcreasmg
the I/O and processmg burden on the supe~sory
subsystem

8 SUMMARY

In this paper, we have described a novel architecture for high
throughput database systems based on exploltahon of abundant
commumcations bandwdth In this architecture, repetihve
broadcast of the entue contents of a database to many pm
cessmg elements ehmmates read bottlenecks, slmphfies data
management, supports rapid execuhon of complex queries,
and pernuts efficient concurrency control The architecture 1s
plausible Dven current transrmssion, storage, and VLSI technologes,
a system prototype is under Construchon

9 ACKNOWLEDGEMENTS

Many of the concepts described III dus paper draw on the conmbuhons
of past and present members of the Datacycle pro-
Ject Enc Gausmann, Kalwant Grewal, Dorothy DeLuca,
&ug Redmg, and David Wagner Also, we acknowledge
wth grahtude the comments and suggestions of our colleagues
elsewhere m Bellcore

[Top]
No.
제목
작성자
작성일
조회
17623Angel 1.5 v - Backup, Recovery Tool
보규니
2004-03-05
5696
16260안전한 오라클 데이터베이스 운영을 위한 Chec list
정재익
2003-11-12
7576
15811Angel 1.2.5 v - Oracle Tuning Tool 프리웨어
보규니
2003-10-07
6591
15738The Datacycle Architecture for Very High Throughput Database Systems
정재익
2003-09-29
7316
15737Oracle Enterprise Manager 를 이용한 Database 관리
정재익
2003-09-29
6955
14350visual studio로 oracle appl. 개발시 툴
이관목
2003-05-13
6870
12734Pro*C/C++ Precompiler Programmer's Guide [1]
여인수
2002-11-27
10416
Valid XHTML 1.0!
All about the DATABASE... Copyleft 1999-2023 DSN, All rights reserved.
작업시간: 0.046초, 이곳 서비스는
	PostgreSQL v16.1로 자료를 관리합니다