Consider the following relational schema and SQL query: Employee(eid integer, did: integer, sal: real, hobby: char(20)) Department did integer, dname : char(20). floor : integer, phone: char(10)) Financeldid: integer, budget: real, sales : real, expenses: real) SELECT D.dname, F.budget FROM Employee E, Department D, Finance F WHERE E.did = D.did AND D.did F.did AND D.floor= 1 AND E.sal >= 59000 AND E.hobby= golf Suppose we have the following indexes: . B+ indexes exist on the attributes Employee.did. Employee.sal, Deptfloor, Department.did, and Finance.did. . The DBMS has only the index nested loops and sort-merge as join algorithms (A) 110%! Trace the System R dynamic programming algorithm on this query (B) 110%) Give a relational algebra tree that is reasonably efficient (Hint: think of algebraic equivalences) Consider the following relational schema and SQL query: Employee(eid integer, did: integer, sal: real, hobby: char(20)) Department did integer, dname : char(20). floor : integer, phone: char(10)) Financeldid: integer, budget: real, sales : real, expenses: real) SELECT D.dname, F.budget FROM Employee E, Department D, Finance F WHERE E.did = D.did AND D.did F.did AND D.floor= 1 AND E.sal >= 59000 AND E.hobby= golf Suppose we have the following indexes: . B+ indexes exist on the attributes Employee.did. Employee.sal, Deptfloor, Department.did, and Finance.did. . The DBMS has only the index nested loops and sort-merge as join algorithms (A) 110%! Trace the System R dynamic programming algorithm on this query (B) 110%) Give a relational algebra tree that is reasonably efficient (Hint: think of algebraic equivalences)