Presentation at 1st IEEE Workshop on Information & Software as Services(WISS 2009)Shanghai, China, March 29, 2009

1. Adaptive Parallelization of Queries over Dependent Web Service Calls Manivasakan Sabesan and Tore Risch Uppsala Database Laboratory Dept. of Information Technology Uppsala University Sweden

3. WSMED System (Web Service MEDiator) WSMED OWF 1 WSDL metadata 1 WS Operation 1 WS Operation n WS Operation 1 WS Operation m WS 1 WS n WSDL metadata n SOAP call Import metadata SQL Query OWF n Automatically generated O peration W rapper F unction(OWF) makes web services queryable. Meta store 1 3 3 1 2

10. Query Processing in WSMED Parallel query plan SQL query Calculus Generator Parallel pipeliner Plan function generator Central plan creator Plan splitter Phase 1 Phase 2

11. Central plan - Phase1 Query1(pl,st) :- GetAllStates() and GetPlacesWithin(‘Atlanta’,_,15.0,’City’) and GetPlaceList(_, 100,’true’) Calculus expression γ GetPlacesWithin(‘Atlanta’, st1, 15.0, ‘City’) <pl, st> γ GetPlaceList (str, 100, ‘true’) γ GetAllStates() < st1 > <city , st2 > γ concat(city,’, ‘, st2) <str > Algebra expression

12. Plan Splitting and Plan Function Generation - Phase2 <city, state2> γ GetPlacesWithin(Atlanta’, st1, 15.0, ‘City’) γ concat(city,’, ‘, state2) <str > PF1 PF1(Charstring st1) -> Stream of Charstring str γ GetPlaceList(str,100,’true’) <pl, st> PF2 PF2(Charstring str) -> Stream of <Charstring pl, Charstring st>

13. WSMED Process Tree q i - query process (i=0,1,......n) Level 2 q0 q1 q3 q4 q2 PF1 GetAllStates PF2 q5 q8 q7 q6 Coordinator Level 1 Query1

14. Make Parallel Pipeline < str > < st1 > FF_APPLYLP( PF2, 3,str ) <pl, st> γ GetAllStates() FF_ APPLYP( PF1, 2, st1 ) Manually set fanouts on both levels

24. .......... 2. A monitoring cycle for a non-leaf query process is defined when number of received end-of-call messages equal to number of children. 2.1 After the first monitoring cycle A FF_APPLYP adds p new child processes - an add stage . 3. When an added node has several levels of children, the init stages of A FF_APPLYP s in the children will produce a binary sub–tree . q0 q1 q3 q4 q2 q5 Coordinator Level 1 q7 q9 q8 q10 Level 2 q6 q11

25. ...... 4. A FF_APPLYP records per monitoring cycle i the average time t i to produce an incoming tuple from the children. 4.1 If t i decreases more than a threshold ( 25% ) the add stage is rerun. 4.2 If t i increases we either stop or run a drop stage that drops one child and its children. q0 q1 q3 q4 q2 q5 Coordinator Level 1 q12 q10 Level 2 q6 q11

26. Adaptive Results- Query1

27. Adaptive Results –Query2