Remarks to Optimization Rules for the End User Programming Language OttoVonG Opatia 8.6.2007

1. Remarks to Optimization Rules for the End User Programming Language OttoVonGOpatia 8.6.2007 Klaus Beneckebenecke@iws.cs.uni-magdeburg.deIWS/FIN, Otto-von-Guericke-Universität MagdeburgPostfach 4120Magdeburg, Germany 39016, Sachsen/Anhalt

2. 1 Aims of OttoVonG Universal Enduser Query Language for • Documents (XML) • Tables (databases) • Internet (of XML-Documents) • Graphics

3. 1 Objects of OttoVonG Generating Operations • El_tab • Tag0 • Tuple_t • Coll_t • Alternate_t

4. 2 Counter Examples for Optimization Rules (1) << M( A, L( B, C)):: 1 2 3 4 5 >> (Tabment T0) (a) B=4(B::C=3(T0) ) B::C=3(B=4(T0))

5. 2 Counter Examples for Optimization Rules (2) << M( A, L( B, C)):: 1 2 3 4 5 >> (Tabment T0) (b) B::pos(B)=1 (B::B=4(T0))  B::B=4(B::pos(B)=1(T0))

6. 2 Counter Examples for Optimization Rules (3) << M( A, L( B, C)):: 1 2 3 4 5 >> (Tabment T0) (c) B::C=3(L(C)[-1]=5(T0))  L(C)[-1]=5(B::C=3(T0))

7. 2 Attributes • name • C(name) (C collection symbol; M; B; L) • pos(name) • Attribute[i] (i: integer)

8. 2 Nonrecursive Example DTD • NAME TYPOS • TABMENT L(A?, B, M(C, D)) • C E, F • D M(H) • F M(G) • A,... TEXT

9. 2 Example Extended Tree L   | (A: TEXT)?, (B: TEXT), M   | (C: (E: TEXT), (F: M)), (D: M)   | | (G: TEXT) (H: TEXT)

10. 2 Condition Types (1) • Simple condition name1:: cond1, where cond1 contains only names and deepest name of cond1 is as deep as name1 example: G:: G=B counter example1: E:: G=B counter example2: n:: G=H

11. 2 Condition Types (2) • Relational condition name1::: cond1, where name1:: cond1 is simple example: G::: G=B abbreviates: G:: G=B E:: G=B A:: G=B

12. 3 Commuting Conditions(1) • EMPS: M(ENO, NAME, FIRSTNAME, LOCATION, SALARY, SEX, PATENTCNT, INSTITUTE, M(HOBBY), M(PROJECT, TIME)) • Query 1: not commuting conditions aus EMPS gib B-(SALARY, NAME, LOCATION, SEX) mit LOCATION=”Magdeburg” ## simple condition mit pos(SALARY) < 50 ## position selecting condition

13. 3 Commuting Conditions(2) • EMPS: M(ENO, NAME, FIRSTNAME, LOCATION, SALARY, SEX, PATENTCNT, INSTITUTE, M(HOBBY), M(PROJECT, TIME)) • Query 2: commuting conditions aus EMPS mit PROJECT:: TIME > 10 # simple condition mit LOCATION=”Magdeburg” # simple condition

14. 3 Commuting Conditions (3) • cond2(cond1(tab)) = cond1(cond2(tab)), • if one of the following conditions is satisfied: 1 cond1 and cond2 are simple. 2 one condition does not select in a fix level of the other 3 cond1 and cond2 arerelational. 4 cond1 and cond2 refer to the same level and are not position selecting.

15. 4 Absorption of a Condition • Query 3: aus EMPS mit PROJECT:: PROJECT in L(“otto” ”SQL” ”XML”) mit TIME > 10 # existential condition aus EMPS mit TIME>10 i PROJECT in L(“otto” ”SQL” ”XML”) mit PROJECT:: PROJECT in L(“otto” ”SQL” ”XML”)

16. 5 Smuggling a Condition (1) • Query 4: aus EMPS mit LOCATION = ”Magdeburg” mit PROJECT:: TIME > 10 gib M(PROJECT, M(NAME, ENO, TIME)) aus EMPS mit LOCATION=”Magdeburg” mit PROJECT:: TIME>10 mit PROJECT = PROJECT gib M(PROJECT, M(NAME, ENO, TIME))

17. 5 Smuggling a Condition (2) • Query 4 continued: aus EMPS mit LOCATION=”Magdeburg” mit TIME > 10 mit PROJECT:: TIME>10 gib M(PROJECT, M(NAME, ENO, TIME)) aus EMPS mit LOCATION=”Magdeburg” mit PROJECT ::: TIME>10 gib M(PROJECT, M(NAME, ENO, TIME))

18. 6 Smuggling the Forget-Operation  (1) • The forget-operation is a relatively simple operation, which is similar to the relational projection, but which differs from projection in 3 points. • The argument of forget is not a list of attributes, which remain in the resulting structure, but the list of attributes, which are to omit. • forget does not omit duplicates in sets. • forget can be used also in recursive structures

19. 6 Smuggling the Forget-Operation  (2) Query 5 a: aus EMPS mit LOCATION = ”Magdeburg” gib M(INSTITUTE, B(NAME, SALARY)) aus EMPS mit LOCATION = ”Magdeburg” forget HOBBY, PROJECT, TIME, SEX,… gib M(INSTITUTE, B(NAME, SALARY))

20. 6 Smuggling the Forget-Operation  (3) Query 5 b: aus EMPS gib M(NAME, HOBBY, PROJECT) aus EMPS forget NAME, HOBBY, PROJECT, TIME, SEX,… gib M(NAME, HOBBY, PROJECT)

21. 7 Rules with the Extension Operation ext ()(1) • Query 7: a hierarchical join FACULTIES: M(FAC, DEAN, FACBUDGET) INSTITUTES: M(INSTI, MGR, BUDGET, FAC) ext F := FACULTIES ext G := INSTITUTES at FACBUDGET mit INSTI:: F/FAC = G/FAC mit FACBUDGET > 100000 mit INSTI:: BUDGET > 10000

22. 7 Rules with the Extension Operation ext ()(2) • Query 7: a hierarchical join of aus INSTITUTES mit BUDGET > 10000 =: $instis aus F:=FACULTIES mit FACBUDGET > 100000 ext G := $insts at FACBUDGET mit INSTI:: F/FAC = G/FAC

23. 7 Rules with the Extension Operation ext ()(3) sel-ext1 cond(assi(tab)) = assi (cond (tab)), this rule holds, if all operations are applicable, and the extension does not introduce a name, which is used in the condition. Counter example for sel-ext1: << L(A, B):: 1 2>> ext B := 3 at B mit B = 3

24. 7 Rules with the Extension Operation ext ()(4) sel-ext2 cond(X:=tab2 at Y(tab1))=X:= ( cond (tab2)) at Y(tab1), here is presupposed that all operations are applicable, that cond is a ::-condition and does not contain a name from tab1.

25. 7 Rules with the Extension Operation ext ()(5) ext-ext assi1(assi2(tab)) = assi2(assi1(tab)), this rule holds, if right and left hand side are defined and assi1 and assi2 have no common names or tabment names. Counter example for ext-ext (without importance): ext A := 1 ext C := 3 at A ext B := 2 at A # result type: A, B, C

26. 7 Rules with the Extension Operation ext ()(6) Counter example for ext-ext (without importance): ext A := 1 ext B := 2 at A ext A := 3 at A # result type: (A, A, B) but ext A := 1 ext A := 3 at A ext B := 2 at A # result type: (A, B, A, B)

27. Summary • We have powerful operations, which are implemented for XML-documents and TAB-files; • this implementation must be improved and generalized in several points • include optimization strategies; • generalize it to databases and Intranet

28. Thank you for attention