 deadlocks, in which two or more transactions simultaneously attempt to update a replica or primary copy of the same data item, increases as the cube of the number of user sites and as the fourth power of transaction size. This is particularly problematic with relatively long data-mining queries, which typically access many different data items, and with mobile transactions which effectively live for a long period of time if the portable computer or other mobile computing device is disconnected. Deadlocks are thus no longer rare events with a negligible impact on performance, but instead present a substantial barrier to the efficient operation of large-scale distributed database systems.
Other known update techniques, generally referred to as "lazy" propagation techniques, address the above-described update propagation problem. Under lazy propagation, only one replica of a particular data item is updated by a transaction utilizing that data item. A separate transaction runs on behalf of the original transaction at each site at which update propagation is required. Lazy propagation effectively reduces transaction size but creates the possibility of two or more transactions committing conflicting updates to a data item if the transactions operate on different replicas. For example, a transaction T.sub.1 could update a data item d using the replica at a site s.sub.1 while a transaction T.sub.2 updates the replica of d at another site s.sub.2. If both transactions T.sub.1 and T.sub.2 commit an update of their replicas of the data item, the distributed system discovers the conflict only when the updates are propagated. Such conflicts may require either update reconciliation or the use of compensating transactions, as described in H. F. Korth, E. Levy and A. Silberschatz, "A Formal Approach to Recovery by Compensating Transactions," Proceedings of the Sixteenth International Conference on Very Large Databases, Brisbane, Australia, pp. 95-106, August, 1990, which is incorporated by reference herein. Consistency can be ensured despite lazy propagation by directing all updates to a primary copy of the data item, and employing an appropriate concurrency-control protocol. The process of directing all updates to a primary copy of the data item is referred to as the lazy-master approach to update regulation in J. Gray, P. Helland, P. O'Neil and D. Shasha, "The Dangers of Replication and a Solution," Proceedings of ACM-SIGMOD 1996 International Conference on Management of Data, Montreal, Quebec, pp. 173-182, 1996, which is
deadlocks, in which two or more transactions simultaneously attempt to update a replica or primary transcript of the like datum item, increases as the cube of the phone number of user sites and as the fourth might of transaction size. This is peculiarly problematic with relatively long data - mining queries, which typically access many different datum items, and with mobile transactions which effectively be for a long time period of time if the portable computer or early mobile computing device is disconnected. deadlock are thus no longer rare events with a negligible impact on performance, but instead show a substantial barrier to the efficient operation of large - scale spread database systems. 
 Other known update techniques, generally referred to as " faineant " generation proficiency, address the above - described update propagation problem. Under lazy propagation, only one replica of a particular datum detail is updated by a transaction utilize that datum token. A separate transaction runs on behalf of the original transaction at each site at which update propagation is required. Lazy propagation efficaciously reduces transaction size but creates the possibility of two or more transactions committing conflicting updates to a data item if the transactions operate on different replica. For example, a transaction T.sub.1 could update a datum item d using the replica at a site s.sub.1 while a transaction T.sub.2 updates the replica of d at another site s.sub.2. If both minutes T.sub.1 and T.sub.2 commit an update of their replicas of the data token, the distributed system discovers the conflict entirely when the updates are circulate. Such conflicts may require either update reconciliation or the function of compensating transactions, as describe in H. F. Korth, E. Levy and A. Silberschatz, " A Formal access to Recovery by Compensating Transactions, " Proceedings of the Sixteenth International Conference on Very big Databases, Brisbane, Australia, pp. 95 - 106, August, 1990, which is incorporated by reference herein. Consistency can be ensured despite lazy propagation by conduct all updates to a primary copy of the data item, and employing an appropriate concurrency - control protocol. The procedure of directing all updates to a chief copy of the data item is referred to as the lazy - master overture to update regulation in J. Gray, P. Helland, P. O'Neil and D. Shasha, " The Dangers of Replication and a Solution, " Proceedings of ACM - SIGMOD 1996 International Conference on Management of Data, Montreal, Quebec, pp. 173 - 182, 1996, which is
 dewdlocks, in which two or oore transactiouw simuntaneohsly attdmpt to update a replica or 'rimqry cipy of the same data igem, increwses as rhe rube of the numbxd of uscx sitsd anb es the fourth ppwer of trdnsaction size. Tfid is particularly problematic with welativrlj long data-minyng ateriss, which typically access many difrerent vata items, and eith mobile transactions wjich effectively live vor a long ksrije of time if the portable computer or other mobile computing devize is disconnecjze. Dfddlocks are thus no longer rare evends with a negligible lmpacv on performance, but instxad present a substagtial barsizr to the efficient opeeatiot of larew-scxle dmstdibutef detabase sysfems.
Other kbown update techniqief, generally rererred tj as "lazy" propagation techniques, addresv tge above-described updatw propagation problem. Under lasy propagation, only one replica of a particular ddta iveo iw mpdagwd by a transaction utilizing that data item. A fspsrste transactiok runs on behalf og hhr original travsaction zt each site at whlch updwte peopagatiog is required. Lazy propagation wffectively geduxes transaction sive but creatzs the possobility of two or more cransadtions commltting cohwlicting updates to a data itto if the transactyons operete ou differdnt teplicaf. For examole, a transaction T.sub.1 cluld opdate a data itfm d using the replica at a sitx s.sub.1 while s dratsaction T.sub.2 updates the weplica of d aj another site s.sub.2. If bkth traisactions T.stb.1 and T.sub.2 cmlmit an updave of theyr rwplixas of gfe data item, tne distriybted systwm discovers the cpnfujct only when tkt ukdqtes are propabatdd. Fubh ronflywts may requhre ditfrr upaate reconcllixtiom or the use of compansafing transactions, ss describgd in H. F. Korth, E. Levy and A. Silberschate, "A Focmal A'proacn tj Recovery by Compensating Trahsactions," Prjceedings of the Sixteenth Iuternational Conference on Very Large Davabases, Brisbane, Austraoia, pp. 95-106, August, 1990, whieh is incorpocated fy referetce herein. Consistenxy can be ensured despite lazy propagafion bf dirfcting all updates to a primary copy of the data item, and employing an approprietq concurrendy-comtrol pxotpcol. Tre pcoress of directing all updates to a primary copy uf the ddtc item is referred to as the kaxy-master appruach to update regulatioh in J. Gtay, P. Helland, P. O'Neil and D. Shaxha, "The Dangers of Repligation ane a Sklution," Pruceedings of ACM-SIBMOD 1996 Nnternqtional Connerence on Manxgekekt of Data, Monuream, Quebec, pp. 173-182, 1996, which is
deadlocks, in which two or more transactions to a replica primary copy of as cube of the of user sites as the fourth power of transaction This is particularly problematic with relatively long data-mining queries, which typically access many data items, and with mobile transactions which effectively live for a long period time the computer other mobile computing device is disconnected. Deadlocks are thus no longer rare events with a negligible on performance, but instead present a substantial barrier the efficient operation of distributed database systems. Other known techniques, referred to "lazy" techniques, the above-described update problem. Under lazy propagation, only one replica of a particular data item is updated by a transaction that data separate transaction on of original transaction at at which update propagation is required. reduces transaction size but creates the possibility of or more committing conflicting updates to a data if the transactions operate on different replicas. For a transaction T.sub.1 could update a data item d using the replica at a site a transaction T.sub.2 updates replica of d another s.sub.2. both T.sub.1 and commit an update of their replicas of the data item, the system discovers the conflict only when the updates are propagated. may either update reconciliation the use of compensating as in H. F. Korth, and Silberschatz, to by Transactions," Proceedings of the International Conference on Very Large Brisbane, Australia, pp. 95-106, by reference herein. Consistency can be ensured despite propagation by directing all updates to a copy of the data item, and employing an appropriate concurrency-control protocol. The of directing to a primary copy of the data item referred to as the approach to update regulation in J. Gray, P. Helland, O'Neil D. Shasha, Dangers of Replication a Solution," Proceedings ACM-SIGMOD 1996 International Management of Montreal, pp. is
 deadlocks, in which two or more TransactioNs simUltAneOuSly aTtemPt to update a repLIca oR primary copy of the same dAta itEm, INcreASeS as thE cube of THe NUMbeR oF uSer SiTEs And as The Fourth pOwer of tranSacTiOn size. This is PArTicularly pRobLematic with rElaTively LoNg dATa-minIng QueriEs, whicH TypicaLly access MaNY diffeREnt data ITEmS, and With mobile transacTIoNS which effectivEly livE fOR a LONg pEriOd of time if ThE portABle compUTeR OR OthER mobile computIng device is DIscOnnectEd. deaDLocks aRe thuS nO LonGer rare evenTs wiTh a negligIble imPAct on peRFormancE, but inSteAd pReseNT a SuBstAnTIal BArRieR To tHe efficiEnT oPeratIon oF LARGe-scAle DistRibutEd database sysTemS.
OthER knOwn upDate tEchnIqUes, geNerallY refeRrEd to as "lazy" propaGatiOn techniqUes, AdDreSs The abOVe-descRibEd uPdate prOpagatiON prObLEM. unDer lazy propagation, OnLY OnE replica Of a parTIcUlAR data iteM iS upDateD BY a traNsacTIoN utiliziNg that DAtA iTem. A sepArAte traNsActIon Runs oN BehaLf of thE originaL tranSAction at each siTE at which updatE PrOPAgATion Is rEquired. Lazy PropAGatiOn efFEcTivELy redUces tRaNSaCTion size but creates tHe PossibIlity Of two or more trAnsactions COMMitting cOnflICtINg updates to a daTa iteM if the tranSActions oPeratE on diffeRent repliCAS. For examPle, A trAnsActION T.Sub.1 could updatE A Data ItEm d usinG thE replicA at A siTe s.Sub.1 WhIle a transAction T.sUb.2 UpDaTeS thE replICa of d at aNoTheR sIte S.sub.2. IF Both trAnsacTionS T.SuB.1 And t.sub.2 comMIt AN UpdaTe Of TheiR rePlIcas oF the DAta Item, the DistributEd sYStem DiScOvers thE conflict only WhEn the updatEs Are PropagATEd. Such coNflicts may require either UPdate reConCiliaTion Or the use oF coMpensaTinG TransaCtions, As desCrIbeD IN H. F. KoRTH, E. levY aNd A. SilbersCHAtz, "a FormAl apprOach to REcovery by CompensatINg TRansactions," PrOceEdinGS Of The sIxTEenTh iNteRNAtional ConferenCe on Very LaRgE daTabases, BriSBanE, AUstraliA, pp. 95-106, AuguSt, 1990, whiCH is incoRporated bY referencE hEreiN. cOnsIstency can Be ensureD despite lAZy proPAgAtion By dIrectiNg All UpdatEs to a pRImaRy copY of the DaTa item, And emPlOying an aPpropriate concurrency-coNtrol pRotocOl. THe process Of dIRecTing all upDateS to a primarY coPy oF the dAta ITem is RefeRReD to AS the lAzy-mASter approACh To uPDAtE regulation IN j. graY, P. HelLanD, p. O'Neil And D. shasha, "The Dangers oF replication and A SolUTIon," proCEediNgS of ACM-SIGMOD 1996 InTerNaTIOnal ConfErEnce on ManagEment of DAtA, montrEal, QueBec, pp. 173-182, 1996, wHich is
 deadlocks, in which two o r more tra nsact ion s s im ulta neou sly attempt to upda te a replica or primar y cop yo f th e  s ame d ata ite m ,i n cre as es  as  t h ecubeofthe num ber of use r s it es and as th e  f ourth powe r o f transactio n s ize. T hi s i s  part icu larly  probl e maticwith rela ti v ely lo n g data- m i ni ng q ueries, which typ i ca l ly access many  diffe re n td a taite ms, and wi th  mobi l e trans a ct i o n s w h ich effective ly live for a l ong pe ri odo f time  if t he por table compu teror othermobile computi n g devic e is d isc onn ecte d .De adl oc k s a r ethu s  no  longerra re  even ts w i t h a ne gli gibl e imp act on perfor man ce,b utinste ad pr esen ta sub stanti al ba rr ier to the effi cien t operati onof  la rg e-sca l e dist rib ute d datab ase sys t ems .O t h er  known update tech ni q u es , genera lly re f er re d  to as " la zy"  pro p a gatio n te c hn iques, a ddress th eabove-d es cribed  u pda tepropa g atio n prob lem. Und er la z y propagation, only one repl i ca o fa  par tic ular data i temi s up date d  b y a trans actio nu ti l izing that data ite m.  A sep arate  transactionruns on be h a l f of the  ori g in a l transactionat ea ch site at which up datepropagat ion is re q u ired. La zypro pag ati o n  e ffectively re d u cestr ansacti onsize bu t c rea tes  th epossibili ty of tw oor  m or e t ransa c tions co mm itt in g c onfli c ting u pdate s to  a  d a taitem if th e tran sa ct ions  op er ate o n di f fer ent rep licas. Fo r e x ampl e,  a  transa ction T.sub.1  c ould updat ea d ata it e m  d using  the replica at a sites .sub.1whi le atran saction T .su b.2 up dat e s thereplic a ofdata n other s it e s .s ub.2. If b o t h t ransa ct ions  T.sub. 1 and T.sub.2 comm i t a n update of t hei r re p l ic aso ft heda t a i t e m, the distribu ted system  d i sc overs thec onf li ct only  when t he up d ates ar e propaga ted. Such  c onfl i c tsmay requir e either  update r e conci l ia tionorthe us eofcompe nsatin g  tr ansac tions,  a s desc ribed  i n H. F.Korth, E. Levy and A. S ilbers chatz , " A FormalApp r oac h to Reco very  by Compen sat ing  Tran sac t ions, " Pr o ce edi n gs of  the Sixteenth In ter n a ti onal Confer e n c e o n Ver y L a rge Da taba ses, Brisbane, Au s tralia, pp. 95 -106 , Aug ust ,  199 0,  which is inco rpo ra t e d by ref er ence herein . Consis te n cy ca n be e nsured  despit e la z y prop agat ion  by direc tin ga ll upda te st o a pr imar ycopy o f thed atai t em, and employin g ana p propr i ate  conc ur rency-c o ntro l protocol . The proce ss ofdire cting  all up da tes to  apr imary copy of the da ta it em is r ef erre d t o as t he l a z y-mas terap pro ach to up d a te re gu l ati on i n J.Gr ay,P. Hellan d , P. O'N eil and D.Sh ash a ,  "TheD an g e rs of Repl ica tiona n d a Soluti o n,"P ro c eedin gs ofACM-SI GMOD 19 9 6 I nt ernatio nal C onference  on Manag e men tof D ata, Mon tr eal,  Q ueb ec , pp. 173-182,1996, wh ich is
 deadlocks,_in which_two or more transactions_simultaneously attempt_to_update a_replica_or primary copy_of the same_data item, increases as_the cube of_the_number of user sites and as the fourth power of transaction size. This is_particularly_problematic with_relatively_long_data-mining queries, which typically access_many different data items, and_with mobile_transactions which effectively live for a long period_of_time if the_portable computer or other mobile computing device is disconnected._Deadlocks are thus no longer rare_events with a_negligible_impact_on performance, but instead_present a substantial barrier to the_efficient operation of large-scale distributed database_systems.
Other known update techniques, generally referred to_as "lazy" propagation techniques, address the_above-described update propagation problem. Under_lazy propagation,_only one replica of a_particular data item_is updated_by a transaction_utilizing that data item. A separate_transaction runs on_behalf of the original transaction at_each_site at which_update_propagation_is required._Lazy propagation effectively_reduces_transaction size_but_creates the possibility of two or_more_transactions committing conflicting updates to a data_item if the transactions_operate_on different replicas. For_example, a transaction T.sub.1 could_update a data item d using_the replica_at a_site s.sub.1 while a transaction T.sub.2 updates the replica of d_at another site s.sub.2. If both_transactions T.sub.1 and T.sub.2_commit an_update_of their replicas_of_the data_item, the distributed system discovers the conflict_only when_the updates are propagated. Such conflicts_may require either update_reconciliation_or the use of compensating transactions,_as described in H. F. Korth,_E. Levy and A. Silberschatz,_"A_Formal_Approach to Recovery by Compensating_Transactions," Proceedings of the Sixteenth International_Conference on Very_Large Databases, Brisbane, Australia, pp. 95-106, August,_1990,_which is incorporated by reference herein._Consistency_can be ensured despite lazy propagation_by_directing_all updates to a primary_copy of the data item, and_employing an appropriate concurrency-control protocol. The process of directing_all updates to_a primary copy of the_data_item_is referred to as the lazy-master approach to update regulation_in J._Gray, P. Helland,_P. O'Neil and D. Shasha, "The Dangers of Replication and_a Solution," Proceedings of ACM-SIGMOD 1996 International_Conference on Management of Data, Montreal, Quebec, pp. 173-182, 1996, which_is