ࡱ> .)*+,-Y( 32N/ 0|DArialas-(0(B 0 DTimes New Roman(0(B 0  DWingdingsRoman(0(B 0 0DSymbolgsRoman(0(B 0 @DVerdanasRoman(0(B 0 " 0(.2  @n?" dd@  @@``    (J  5   **5 ()()      ()()   ()  5  21()  p)q)r/p//y=ZW 6$M(y,I891>:VMV]-mhQ 'ae]#3]DEEGFE 0e0e     A@  A5% 8c8c     ?1 d0u0@Ty2 NP'p<'pA)BCD|E||s " 0e@        @ABC DEEFGHIJK5%LMNOPQRSTUWYZ[ \]^_ `abN E5%  N E5%  N F   5%    !"?N@ABC DEFFGHIJK5%LMNOPQRSTUWYZ[ \]^_ `ab ff@8ghwB ʚ;"O2ʚ;g4?d?d@B 0Hppp@ <4ddddlpC 0\- <4BdBdlhG 080___PPT10 ? %O  =XE .Buffering in Query Evaluation over XML Streams//(WZiv Bar-Yossef Technion Marcus Fontoura Vanja Josifovski IBM Almaden Research Center JXP3  33,! F0 XML Document H1XML Document Tree J3 XPath Queries  Z= XPath Queries  N5XPathQuery = path pattern + predicates XPath 2.0 Forward axis only Eval(Q,D): nodes in D that match Q Two modes of XPath evaluation: Full fledged evaluation: given Q,D, output Eval(Q,D) Filtering: given Q,D, determine whether Eval(Q,D) is nonempty. "Ct 9 ) @b")8*P6 XML StreamsXML stream: sequence of SAX events startDocument(), endDocument(), startElement(name), endElement(name), text(str) Why XML streams? For transferring XML between systems For efficient access to large XML documents Critical resources Memory Processing time #PQ#-Q b#   Streaming XML AlgorithmsXFilter and YFilter [Altinel and Franklin 00] [Diao et al 02] X-scan [Ives, Levy, and Weld 00] XMLTK [Avila-Campillo et al 02] XTrie [Chan et al 02] SPEX [Olteanu, Kiesling, and Bry 03] Lazy DFAs [Green et al 03] The XPush Machine [Gupta and Suciu 03] XSQ [Peng and Chawathe 03] FluX [Koch el al 04] TurboXPath [Josifovski, Fontoura, and Barta 05] & i+3333"3 3333 &332;    Q98Memory Bottleneck I: Storage of Large Transition Tables89##%B##Framework of most algorithms: Q NFA Simulate NFA by DFA Caveat: exponential blowup However: exponential blowup is not necessary [Bar-Yossef, Fontoura, Josifovski 04] Algorithm for filtering XML streams whose space is linear in the query size oL &3> RV:5Memory Bottleneck II: Buffering of Document Fragments86##!B##HScenario 1: buffering nodes, which may or may not be part of the output.*I >lL5Memory Bottleneck II: Buffering of Document Fragments86##!B##EScenario 2: buffering nodes needed for evaluating pending predicates."F <]?5Memory Bottleneck II: Buffering of Document Fragments86##!B##SScenario 3: buffering multiple candidate matches that are nested within each other.*T I^@ Our ResultsfQuantitative space lower bounds for: Full-fledged evaluation of queries with predicates (Scenario 1) Filtering/full-fledged evaluation of queries with  multi-variate predicates (Scenario 2) Matching upper bound Eager evaluation of predicates In all other scenarios: no buffering required Filtering of queries with  univariate predicates over non-recursive documents is possible without buffering [Bar-Yossef, Fontoura, Josifovski 04]%ZZZZ.ZZ 4 P  m %  b M _A Related Work3Space complexity of XPath evaluation over non-streaming XML documents [Gottlob, Koch, Pichler 03], [Segoufin 03] Space complexity of XPath evaluation over streams of indexed XML data [Choi, Mahoui, Wood 03] Space complexity of select-project-join queries over relational data streams [Arasu et al 02]sZZZ* 3+363 33 330/\ `BDocument Concurrency"Q: query D = a1,& ,an: document Each ai is an SAX event at = (a1,& ,at) Definition: x D is alive at step t if x at and $ b, g s.t. x Eval(Q, atb) x Eval(Q, atg) t-concurrency(D,Q): number of nodes that are alive at step t concurrency(D,Q): maxt t-concurrency(D,Q)UUOU$UhU FFF  *$ ,bDConcurrency: Example eELower Bound NotionsA  normal lower bound: For every algorithm A, there exist Q and D s.t. A uses on Q and D W(concurrency(D,Q)) bits of space. Q and D may be  pathological Doesn t say much about real-world queries/documents An  ideal lower bound: For every A, every Q, and every D, A uses on Q and D W(concurrency(D,Q)) bits of space. Too good to be true A can have D and Q  hard-coded , and then know the result a priori Space of A on D and Q = minimum description length of Q and DZfZRZZYZZZ R >DfFOur Lower Bound@Theorem: For every A, every Q, and every D, there exists an almost isomorphic document D , s.t. A uses on Q and D , W(concurrency(D,Q)) bits of space. D is the same as D, except for a few extra empty nodes with auxiliary names. Theorem holds only if: Q is  star-free D is non-recursive e$ 'e$  ,[gG.Why isn t this Obvious? Reason 1: we want the theorem to work for every Q and D, not only ones with high MDL. Reason 2: Obvious: If x is alive at step t A has to remember x Because: A may or may not need to output x Not obvious: If x and y are alive at step t A has to remember both If x and y are not  independent , maybe it s enough to remember just x (or just y)a7+ESN+ !S Z hHProof of Lower Bound C = t-concurrency(D,Q) x1,& ,xC = nodes that are alive at step t Recall: for every xi there exist bi and gi s.t. xi Eval(Q, atbi) xi Eval(Q, atgi) Lemma: there exist a single b and a single g s.t. for all i, xi Eval(Q, atb) xi Eval(Q, atg)p&>$  "       M0  iIProof of Lower Bound (cont.) For every S { 1,& ,C } define document DS: DS is the same as D, except For every i S, we  mark xi Marking: an extra empty child with an auxiliary name Note: DS is almost-isomorphic to D A = any algorithm Note: From output of A on DS, one can  reconstruct the set S.2HwQ   #jJProof of Lower Bound (cont.) Consider state of A at step t when running on DS If suffix = g, none of the xi s should be output A could not have output any xi by step t If suffix = b, no information in suffix about S but S can be reconstructed from output state of A at step t must have all information about S Conclusion: space e" W(C) Actual proof: by one-way communication complexity11+W92/   J9    LkK Conclusions  nOur contributions: Quantitative space lower bounds Full-fledged evaluation of queries with predicates Filtering/full-fledged evaluation of queries with  multi-variate predicates Matching upper bound Open problems: Quantitative lower bounds for XQuery evaluation over streams Address larger fragments of XPath Z ZZZZ_ZZ  `JP5 /G IL[d ` Ot{h______` M <ff33̙3` +ffO=ff̙H7` fff3f̙` Tff33ff` 0Ky{kOz` )R{f` GiIfff̙fR` ̙|̙3f` 3ff~>?" dd@'?lFd@  nK'o`P( n?" dd@   @@``PT     o (`0p>> (((  ZB  c $D"`   6 "M }  X Click to edit Master title style!!  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25: 26: On the Complexity of Database Queries 27: 28: 29: Papadimitriou 30: 31: 32: Yannakakis 33: 34: Z00<2BFBFBF BFB F BF BF B FBFBF B1FBFBF BFBF BF B FBFBFB>u H  0޽h ? 3fffff3̙3f̙___PPT10i.Ia+D=' = @B +4- gZK0 3,+, A`((  2 & 04N  =content3~"  s *M }   2  0r V  ;paper32  0H^ KKN  ;title32  0 &: =section32  0 8id32  0h%<  ;title32  08 /  :root3L   c $Ԕ ' rL   c $Ԕ' L  @ c $ԔL  @ c $Ԕ%L   c $Ԕ' K^ 2  0R  B  =section32  0d T 8id32  0L p ;title3L @ c $ԔB  L @ c $ԔB }   s *4C"?x  ]%On the Complexity of Database Queries&(2&  s *C"?   ;Intro 2  s *C"?. 72 22 " 0 " @3 2 # 0LA 41  <author32 $ 0$b <author32 % 0P F =content3 ' <Ԕ?"0@NNN?N ( <Ԕ?"0@NNN?NB  2 ) 0D >  @3 2 * 0   @3 2 + 0x `  @3 2 , 0 C  @3 2 - 0  @3 2 . 046"& @3  / <Ԕ?"0@NNN?N' A  0 <Ԕ?"0@NNN?N' bL 1 <Ԕ?"0@NNN?N1 p  2 <Ԕ?"0@NNN?N 3 <Ԕ?"0@NNN?NN KT  4@ <Ԕ?"0@NNN?N< u  5 <Ԕ?"0@NNN?N /  6@ <Ԕ?"0@NNN?NT}6 7 <Ԕ?"0@NNN?N 8 s *C"? L  E Papadimitriou(2 9 s *C"?   \ Yannakakis (2   : s *C"? ?c =Results 2 ; s *=C"?  yada yada yada 262 H 0D=  =section32 I 0 =C ! 3  8id32 J 00=   ;title3L K@ c $Ԕ h ] f L L c $Ԕ ]  M s *$=C"?Q  91(2 N s *T=C"? (  c etc etc etc 2  O s *=C"? q  73 22 Q 0t=r yy  =content3 R <Ԕ?"0@NNN?N ] 7 2 S 0 =( X   @3 2 T 0@= w  @3  U <Ԕ?"0@NNN?N  V <Ԕ?"0@NNN?Ny ' ' (  \ s *@'=C"?   A Conclusions 2  ^@ <Ԕ?"0@NNN?N] ' b ` TZGH̙I^Ԕ?"0@NNN?N' u   s *+=C"? :   bla bla bla 2 6H  0޽h ?       &' %( #/ $0 #)1$*2"3,4&+5.6%-7HIKHJLHQRJTUQSVH^ ` 3fffff3̙3f̙___PPT10i.Ia+D=' = @B +#: gZK0 W1O10 CdP-(  ~"  s *^=M }  =  7 0h5=C"?[ ?Results 2 8 0`=C"?h  yada yada yada 262  6e=   =content32  6j=  ;paper32  6h=   ;title32  6Xp=[ =section32  6(u=   8id32  6Ds=E i5  ;title32   6z=  :root3R   s *Ԕ R   s *Ԕ R  @ s *Ԕ[  R  @ s *Ԕ[E R  s *Ԕ  2  6x= vz  =section32  6= 6 8id32  6X=;= ;title3R @ s *Ԕ x R @ s *Ԕ `x;  0@=C"? d _%On the Complexity of Database Queries&(2&  0=C"? P  =Intro 2  0=C"?yda 72 22   6=DF @3 2 ! 6X=9 JM  <author32 " 60="sw <author32 # 6\=  =content3 $ BԔ?"0@NNN?N[  % BԔ?"0@NNN?N x 2 & 6P= U  @3 2 ' 6= R  @3 2 ( 6= o  @3 2 ) 6ܱ= 1  @3 2 * 6="y @3 2 + 6 =\+ @3  , BԔ?"0@NNN?N L9  - BԔ?"0@NNN?N s . BԔ?"0@NNN?N L  / BԔ?"0@NNN?Nu  0 BԔ?"0@NNN?N D 1@ BԔ?"0@NNN?N5   2 BԔ?"0@NNN?N   3@ BԔ?"0@NNN?N?`\ 4 BԔ?"0@NNN?N#" 5 0=C"?w s/7  G Papadimitriou(2 6 0=C"? x  ^ Yannakakis (2  2 D 6@=:   =section32 E 6=; 2m  8id32 F 6t= m   ;title3R G@ s *Ԕ >  Y R H s *Ԕ  >  I 0=C"?   91(2 J 0=C"? % P  e etc etc etc 2  K 0=C"? s  73 22 M 6=d < i F  =content3 N BԔ?"0@NNN?N  2 O 6$=  @3 2 P 6=:  @3  Q BԔ?"0@NNN?N > F :  R BԔ?"0@NNN?NF S S  X 0(=C"?$   C Conclusions 2  Y@ BԔ?"0@NNN?N : b Z ZZGH̙I^Ԕ?"0@NNN?N.  [ 0 =C"? tl   bla bla bla 2 6 c Bo?"6@ NNN?Nx d BA ?"6@ NNN?N8  /paper[author= Papadimitriou ]/section[@id =  2 or title =  Intro ]/contentM l@D@D@ D@D@D@D@D@D@D,  #7_H  0޽h ?      $ #% !, "- !&. 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Z _%On the Complexity of Database Queries&(2& 8 s *$YAC"? 1F  =Intro 2 8 s *\AC"?oW 72 22 8 0_A:h  @3 2 8 0cA/ lo  <author32 8 0ZA <author32 8 0,fA ' =content3 8 <Ԕ?"0@NNN?NQ  8 <Ԕ?"0@NNN?N  2 8 0nA $w{  @3 2  8 0qA t  @3 2 !8 0vA =  @3 2 "8 0luA S  @3 2 #8 0|A @3 2 $8 0{AR ! @3  %8 <Ԕ?"0@NNN?N n/  &8 <Ԕ?"0@NNN?N  '8 <Ԕ?"0@NNN?N n  (8 <Ԕ?"0@NNN?N  )8 <Ԕ?"0@NNN?N : *8@ <Ԕ?"0@NNN?N+   +8 <Ԕ?"0@NNN?N   ,8@ <Ԕ?"0@NNN?NaR -8 <Ԕ?"0@NNN?NE .8 s *PAC"?m Q-  G Papadimitriou(2 /8 s * AC"? n  ^ Yannakakis (2  2 08 0ԍA0  B  =section32 18 0XA1 T  8id32 28 0A 1  ;title3L 38@ c $Ԕ ` * O L 48 c $Ԕ * `  58 s *ԘAC"?   91(2 68 s *AC"? 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++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F ++0+ F + g <<`DD9(  x  c $pvFM }  F   c $lwF9<$ 0 F   s *(yFC"?8l,$ 0 ?Results 22  s *AC"?H ,$ 0 yada yada yada 262  0@A P[ ,$@ 0 =content32  0F10   ,$@ 0 ;paper32  00F M ,$@ 0 ;title32   0Fgn| ,$@ 0 =section32   0F |k ,$@  0 8id32   0dF 6 ,$@  0 ;title32   0hF? ,$@  0 :root3   c $Ԕ  1,$@  0  c $Ԕ|  ,$@  0 @ c $Ԕ u ,$@ 0 @ c $Ԕ ru ,$@ 0  c $Ԕ   ,$@ 02  0F B' ,$@ 0 =section32  0F ,$@ 0 8id32  0lF-^,$@ 0 ;title3 @ c $Ԕ 5 ,$@ 0 @ c $Ԕ -5-,$@ 0   s *`FC"? 7,$ 0 _%On the Complexity of Database Queries&(2&  s *4FC"?  ,$ 0 =Intro 2  s *FC"?dPyL,$ 0 72 22  0F5z,$@ 0 @3 2  0ijF nRj ,$@ 0 <author32  0FuZ ,$@ 0 <author32  0F ,$@ 0 =content3  <Ԕ?"0@NNN?N uU ,$@ 0  <Ԕ?"0@NNN?N 5 ,$@ 02   0 F Y ,$@ 0 @3 2 ! 0F 76 ,$@  0 @3 2 " 0LF1  ,$@! 0 @3 2 # 0F=  ,$@" 0 @3 2 $ 0ȪF&d,$@# 0 @3 2 % 0hF'n,$@$ 0 @3  & <Ԕ?"0@NNN?N  ` ,$@% 0 ' <Ԕ?"0@NNN?N  uB ,$@& 0 ( <Ԕ?"0@NNN?Nj ` ,$@' 0 ) <Ԕ?"0@NNN?N h ,$@( 0 * <Ԕ?"0@NNN?N 5,$@) 0 +@ <Ԕ?"0@NNN?N br= ,$@* 0 , <Ԕ?"0@NNN?N U}1 ,$@+ 0 -@ <Ԕ?"0@NNN?N-',$@, 0 . <Ԕ?"0@NNN?N,$@- 0 / s *dFC"? h ,$. 0 G Papadimitriou(2  0 s *4FC"?% U ,$/ 0 ^ Yannakakis (2  2 1 0F w ,$@0 0 =section32 2 0F  k ,$@1 0 8id32 3 0xF@ u  ,$@2 0 ;title3 4@ c $Ԕ ~ ,$@3 0 5 c $Ԕ ~ @ ,$@4 0 6 s *0FC"?c K ,$5 0 91(2 7 s *FC"? 2| ,$6 0 e etc etc etc 2  8 s *FC"?X * ? ,$7 0 73 22 9 0F ,$@8 0 =content3 : <Ԕ?"0@NNN?N ~ ,$@9 02 ; 0DG"  E ,$@: 0 @3 2 < 0<Gr  X % ,$@; 0 @3  = <Ԕ?"0@NNN?N r ,$@< 0 > <Ԕ?"0@NNN?N " ,$@= 0 ? s *GC"?< ' [ ,$> 0 C Conclusions 2  @@ <Ԕ?"0@NNN?N ~  ,$@? 0b A TZG HJIԔ?"0@NNN?N   ,$@@ 0/ B s *FC"? g ,$A 0  bla bla bla 2 6 C Bo?"6@ NNN?N,$@B 0 D BxG ?"6@ NNN?N,$C 0 %/paper[title != section/title]/author& l@D@D@D@D@D 7_H  0޽h ?           & '  ( !)* #+",%-$.12413519:3<=9;>1@A 3ff~___PPT10v.Vo04Z+"Dx' = @B DEx' = @BA?%,( < +O%,( < +DA' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*F%(D/g' =%(Df' =%(D' =A@BBBB0B%(D' 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DD D DD&D1D2D4D1D3D5D1D9D:D3D-.Vo04Z+D+' = @B D*' = @BA?%,( < +O%,( < +Di' =%(D' =%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*CD %(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<* D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<* D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*&D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*1D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*2D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*3D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*4D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*5D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*9D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*:D%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*+B#style.visibility<*=D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*@D%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*FD%(D# ' =%(D ' =%(D!' =4@BBBB%(D' =,54*3>Bfillcolor=@BPB<*1DD' =1:B solid*a3>Bfill.type<*1DD' =1:B true*]3>Bfill.on<*1DD!' =4@BBBB%(D' =,54*3>Bfillcolor=@BPB<*3DD' =1:B solid*a3>Bfill.type<*3DD' =1:B true*]3>Bfill.on<*3DD!' =4@BBBB%(D' =,54*3>Bfillcolor=@BPB<*DD' =1:B solid*a3>Bfill.type<*DD' =1:B true*]3>Bfill.on<*DD4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*ED+%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*ED+x%(++0+DG ++0+ DG ++0+DG ++0+1DG ++0+2DG ++0+3DG ++0+9DJ ++0++B#style.visibility<*H%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*H%(D' =%(Dh' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*H!%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*H!%(+} g  L$(  Lr L S x'JM }  J r L S L(J; ` J H L 0޽h ? 3ff~___PPT10i._o>lr+D=' = @B + g  PP(  Pr P S 5JM }  J  P S 6J <$D 0 J H P 0޽h ? 3ff~vn___PPT10N._o+YD"' = @B D' = @BA?%,( < +O%,( < +D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P %(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P %(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P7%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P7G%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*PG%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P%(D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*P%(+% gZK0 H@  \(  \~" \ s * J/ _  J D \ 6J"`Nv  L1: 2:
3: 4: Intro 5: 6: 7: bla bla bla 8: 9:
10:
11: 12: Results 13: 14: 15: yada yada yada 16: 17:
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19: 20: Conclusions 21: 22: 23: etc etc etc 24: 25:
26: 27: On the Complexity of Database Queries 28: 29: 30: Papadimitriou 31: 32: 33: Yannakakis 34: 35: m00<2BFBFBF BFB F BF BF B F @D@BFBF B1FBFBF BFBF BF B FBFBFB>u " \ <?"6@ NNN?N 7  ,$D 0  \ B Ԕ?"6@ NNN?N j,$@ 0  \ H Ԕ?"6@ NNN?Np*z ,$@ 0A  \ <J ?"6@ NNN?NR ,$ 0 calive&0 2 A  \ <J ?"6@ NNN?NI,$ 0 calive&0 2 < \ <`J ?"6@ NNN?Naw,$ 0 ^dead"0 2  \ B Ԕ?"6@`NNN?N ,$@ 0 \ Bo?"6@ NNN?N \ BN ?"6@ NNN?N$ /paper[author= Papadimitriou ]/section[@id =  2 or title =  Intro ]/contentM l@D@D@ D@D@D@D@D@D@D,  #7_H \ 0޽h ? 3fffff3̙3f̙ ___PPT10.Ia+-D' = @B D ' = @BA?%,( < +O%,( < +D4' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*\%(D' =%(D' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<* \%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<* \%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<* \%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<* \%(D' =%(Du' =%(D' =4@BBBB%(D' =1:Bvisible*o3>+B#style.visibility<*\%(D' =A@BBBB0B%(D' =1:Bvisible*o3>+B#style.visibility<*\%(++0+ \N ++0+ \N ++0+\N +. g  dP(  dr d S NM }  N  d S N; F<$@ 0 N H d 0޽h ? 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3380___PPT10.O@pOr0Ztf^2 ƐZFP;oL;NDP OeVtZ ~]@Y5c@Bb~Zd Kٳ3Q{5e ltOh+'0# hp   ( 4@H@On the Memory Requirements of XPath Evaluation over XML Streams IBM_USERmorNetwork IBM_USERmor377Microsoft PowerPointmen@>/@%I@z7G~"g  7F  --$--'--% t `--'3f--F$!>G<G:H8I6J5L4N3P3R3T4V5X6Z8[:\<]>]@]B\D[FZGXHVITIRIPHNGLFJDIBH@G>G--'--F$!]G[GYHWIUJTLSNRPRRRTSVTXUZW[Y\[]]]_]a\c[eZfXgVhThRhPgNfLeJcIaH_G]G--'--F$!|GzGxHvItJsLrNqPqRqTrVsXtZv[x\z]|]~]\[ZXVTRPNLJIH~G|G--'--F$!>f<f:g8h6i5k4m3o3q3s4u5w6y8z:{<|>|@|B{DzFyGwHuIsIqIoHmGkFiDhBg@f>f--'--F$!]f[fYgWhUiTkSmRoRqRsSuTwUyWzY{[|]|_|a{czeyfwguhshqhogmfkeichag_f]f--'--F$!|fzfxgvhtiskrmqoqqqsruswtyvzx{z|||~|{zywusqomkihg~f|f--'f--F$!ffghikmoqsuwyz{|||{zywusqomkihgff--'3f--F$!><:86543334568:<>@BDFGHIIIHGFDB@>--'--F$!][YWUTSRRRSTUWY[]_acefghhhgfeca_]--'f--F$!|zxvtsrqqqrstvxz|~~|--'--F$!--'--F$!--'3f--F$!><:86543334568:<>@BDFGHIIIHGFDB@>--'f--F$!][YWUTSRRRSTUWY[]_acefghhhgfeca_]--'--F$!|zxvtsrqqqrstvxz|~~|--'--F$!--'f--F$!><:86543334568:<>@BDFGHIIIHGFDB@>--'--F$!][YWUTSRRRSTUWY[]_acefghhhgfeca_]--'--F$!|zxvtsrqqqrstvxz|~~|--'--F$!--'--F$!--'f--F$!><:86543334568:<>@BDFGHIIIHGFDB@>--'--F$!][YWUTSRRRSTUWY[]_acefghhhgfeca_]--'--F$!|zxvtsrqqqrstvxz|~~|--'--F$!--'--F$!><:86543 3 34568:<>@BDFGHII I HGFDB@>--'--F$!][YWUTSR R RSTUWY[]_acefghh h gfeca_]--'--F$!|zxvtsrq q qrstvxz|~  ~|--'--F$!    --'--F$!] [ Y!W"U#T%S'R)R+R-S/T1U3W4Y5[6]6_6a5c4e3f1g/h-h+h)g'f%e#c"a!_ ] --'--F$!  !"#%')+-/13456665431/-+)'%#"!  --'--%!44--'@Arial-. 3f$2 Buffering in Query (""!!,"."Systemti-@Arial-. 3f%2 Evaluation over XML %""!"$/".-@Arial-. 3f2 #Streamsn%1.-@Arial-. 32 qZiv Barn   .-@Arial-. 3 2 qz- .-@Arial-. 32 qYossef .-@Arial-. 2 vTechnion.-@Arial-. 32 Marcus Fontoura!    .-@Arial-. 32 Vanja   .-@Arial-. 32 U Josifovski  .-@Arial-. 12 G1IBM Almaden Research Center       .-՜.+,0l    On-screen ShowIBM ~O ArialTimes New Roman WingdingsSymbolVerdanaNetwork/Buffering in Query Evaluation over XML Streams XML DocumentXML Document TreeXPath QueriesXPath QueriesXPath XML StreamsStreaming XML Algorithms9Memory Bottleneck I: Storage of Large Transition Tables6Memory Bottleneck II: Buffering of Document Fragments6Memory Bottleneck II: Buffering of Document Fragments6Memory Bottleneck II: Buffering of Document Fragments Our Results Related WorkDocument ConcurrencyConcurrency: ExampleLower Bound NotionsOur Lower BoundWhy isnt this Obvious?Proof of Lower BoundProof of Lower Bound (cont.)Proof of Lower Bound (cont.) 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