2023年大学毕业设计仓库管理系统数据库计算机外文参考文献原文及翻译.docx
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1、河北工程大学毕业论文(设计)英文参考文献原文复印件及译文论文题目:鸿海种业仓库管理系统的设计与实现作者姓名:石成华专业班级:信管1001学号信息:指导老师:张贵炜论文日期:Muc h e f f o r t has been spe n t in th e data b ase in d us t r y a nd resea r c h c o mmunity tow a rd s a c hie v ing th i s g oal.T he tradi t i onal da t abase app r oa c h to h eterog e neou s database integ
2、 r ation is to b u ild w rappers and i n t e gr a to r s( o r m e d i ators)ontopof mul t i p 1 e , heter o gene o us dat a bas e s. A va r iety o f data j o i ner and d ata blade produc t s bel o ng t o t his ca tegory. Whenaqueryis pos e d to a c lient s ite, a m e tadat a dictio n ary is used to
3、t r a ns 1ate the query into q u e r ies a p propr i ate f o r the indiv i du a 1 he t e rogeneous sit e s in v olved. T hes e q u erie s are t h en map p e d a n d sent to local q u er y pro c e ss o r s . The res u Its r e turne d fro m the diff e r e nt si t e s are inte g r a te d in t o a g 1 o
4、bal a n s w er set. This que r y-dri v en appr o a c h re q uire s com p le x i nform a tion filterin g and int e gr a tion proce s s es, and com p etes f or re s ources wi t h p r oc e ssi n g a t lo c al sou r c e s . It is i nef f icient and potent i a 1 1 y e xpens i ve f or f req u ent q u eri
5、e s, espe c ially for q uerie s requ i rin g aggre g atio n s.Dat a w a r eh o u sing pr o v i des an i nter e s t ing alte r nati veto th e t r a d iti o nal approac h o f he t ero gen eous da t ab a se i nt e grat i o n des c ri be dab ove. Ra t her t h an u s i ng a q u ery-dr i v en approach, da
6、t a w a rehousi n g em p 1 oys an upd a ted riven a pproach in which inf o rmation f rom mu 1 t i p le, h e ter o ge n e o u s sources is int e gra t ed in ad v a nee a n d stored i n a ware h ouse fo r direc t q u er y ing a nd ana 1 ysi s . U n 1 ike o n line transa c ti o n p rocessin g d a tabas
7、es, d ata ware h o u s e s do not c o n t a i n t h e most current i n fo r m a tio n . H o w ev e r, a d a ta war e hous e brings h i gh performance t o t he i n te g r a ted h e terog e neous d atabas e sys t em since d ata are c o pi e d, p r eproc ess e d, i nte g rat e d, a n nota t ed, summ a
8、rized, a n d res t r u c t ur e d int o one semanti c d ata stor e . F ur t hermor e , query proc ess ing in data wa r e h ouses does not int e r f ere with the process i n g at 1 ocal source s . More over, d a ta warehou s es c a n stor e a nd inte g r ate hi s t o ric a 1 i n forma t ion and suppo
9、 r t com p lex m u Itidim e nsiona 1 que r i es. As a r e suit, data warehousing ha s b e c ome v ery popular in i n dus try.1. Di f fer e nee s bet ween op e rat i on a 1 database s y stem s a nd data war e h ous e sSin cemostpe ople are f a mi 1 ia r with com merci a 1 r e 1 a tiona 1 d a t a base
10、 systems, it i s easy t o understand what a d a ta w a r ehou s e is by com p ar i n g these t wo k i nds o f s y s terns.The major tas k of on-line op e r a tio n a 1 databas e s y stems is to per for m o n-line transac t i o n and query pr o cessi n g. The s e system s a r e c a 1 led o n-lin e t
11、r ansa c tion proce s s i ng (OLTP) system s . Th e y co v er m ost of the day t o-day ope rationsofan organiz a tion, s uch a s , pu r chas i ng, i n v e n tor y , m a n u fa c tu r ing, bankin g , payroll, reg i str a tio n , a nd accou n ting. Data war e h ouse sy s t ems, on the oth er hand, s e
12、 rve users or “k n owled g e wor k er s H in the rol e of data anal y s i s an d d e c i s ion making. Su c h sys t e m s can organize a nd pre s e nt data in v a rious formats i n order to accommod a t e th e div e rse nee d s of t h e di f fer e n t u s ers. The s e s yst e m s a r e k n own a s o
13、n-line a n alytica 1 p r o c e ss i ng ( 0 LAP) s ystem s .T he maj o r disti n guis h in g f eat u re s be twe e n O L TP and O L AP are summa r ized as f o 1 lows.(1 ). U s ers an d syst e m oriental i on: An 0 ETP s y stem i s c us t ome r-or i ente dandisusedfortr ans a c tio n a nd q uery pr o
14、c e s s i ng by c 1 e rks, cl i ent s , a nd i nf o rm a t i on tec h no 1 ogy profess i onals. A n 0 LAP sy s t e m i s marketori e n ted a n d is u sed f or d a t a an a lysi s b y know e dg e worke r s, i ncl u di n g manager s , e x e c utives, and an a 1 ysts.(2). Data contents: An O L T P syst
15、em mana g e s c urrent data that, ty p ically, are t oo d e t ai 1 ed to be easily u s e d for decisi o n m a k ing. An OL AP syst e m mana g es 1 a r ge amount s of his t or i cal d a ta, pr o v i d es f a cilities fo r s u mm a rizat i on a n d a g g regation, a n d st o r es and ma n a g e s info
16、rmation a t differ ent 1 e v e Is o f gra n ulari t y. Th e se f e a tures make t h e dataeasierforus e i n info rmeddecisio n m a king.(3 ). Database d esign: An OLT P s y stem usua 1 ly adopts a n ent i t y-re 1 ations h ip (ER) datamodel and an app 1 ication -o r i ented d a t ab a s e design. An
17、OLAP syst e m ty p ic a 1 1 y adop t s e it h e r a star or snow f lake mod e 1, a nd a subj e ctor i e n ted database desig n .(4). V i ew: An OLT P system focuses m a i nly on th e c u r r ent data w i t hin an enterprise or de p art me n t, w i thout re f er r ing to histori c a 1 d a t a o r da
18、t a in diffe r ent o rganiza t i o ns. In c o n t r ast, an O L AP s ys t e m of t e n spa n s mu 1 ti p 1 e ver s i o n s o f a data b ase s c hem a, due to the ev o 1 u tionary p r o c e ss ofanorganiz ation. OLAP syst e ms a Iso deal with i n f o rma t i o n tha t o ri gin at e s fr om differ e n
19、t o rganiz a tio n s, in t egrating info rmati o n f r om many d a tastores. Be c ause of t h eir h u g e volume, O LAP data are s t ore d o n mul t i p 1 e s t orag e m e di a .(5). Acc e ss p a tte r n s : The a cc e s s pa t te r ns o f a n O L TP s ystem c onsi s t mainl y o f sh o rt, at o mic
20、t r a nsactions. S u ch a s y stem r e qu i r es concu r r ency con t rol a n d re c o v ery mecha n i s ms. Howe v e r, access es to OLAP s yst e ms are mo s tly r eado n ly op e ratio n s (sine e m o s t datawarehousesst ore hist o r i c a 1 rather th a n u p -to date info r m a tion), a 1 th o ug
21、h m a ny could b e c o m p 1 ex q ueries.Othe r feat u res whi c h dis t i n gui s h betwe enOL TPand O L AP sy s t ems i n elude da t a base s iz e , f r e qu e n c y of op e ra t i o ns, an d p e rfo r mance metrics and s o on. 2. But, why have a s e p ar a te data w areh o use?“ S inc e o p erati
22、 o nal d at a base s store h u g e a mounts o f d a t a ”,you ob s erve, why n ot pe r f o r m o n 1 i n e analyti c a 1 p r o c essing d i rec t ly on such d a tabases in s te a d o f spe n di n g add itional tim e and r e s ou r ce s to con s t r uct a separate d at a w areh o u se?nA maj o r r e
23、ason f o r s u ch a s e p a ration i s to h elp prom o te t h e hi g h p erf o rmanc e of b oth s y s t em s . A n operational d at a base is desig n ed a n d tuned f rom k nown tasks and workl o a d s , s uch as index i ng a nd has h ing using prima r y keys, sea r c hi n g for particular rec o rd
24、s , and opti mizing “canned q ueries. On the oth e r h a nd, data warehous e q uerie s are o f t en c o mpl e x . They involve the computa t i on of 1 a rge gro ups o f data a t summ a r iz e d levels, and may r e qui r e the u se of s pecia 1 da t a org a niza t i on, acce s s, an d im p 1 e m e n
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