Algorithm to Locating p-Central Elements function p_central( G:group; p:prime ):element; (* Given a group G of order p ms, where m >0 and p does not divide s, return a p-central element of G *)
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function p_central( G:group; p:prime ):element;
(* Given a group G of order p ms, where m >0 and p does not divide s, return a p-central element of G *)
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- Give pseudocode for computing a join: r ⋈r.A=s.A s using a single MapReduce step, assuming that the map() function is invoked on each tuple of r and s. Assume that the map() function can find the name of the relation using context.relname().What method should I use to place nodes into a data structure to assure that insertion, deletion, and searching have a temporal complexity less than O(n)?Is it possible to utilize two clustering indices for different search keys on the same relation in general? Describe how you arrived at your conclusion.
- For the following number patterns write the recurrence relation i) 5, 8.2, 11.4, 14.6, …. ii) 400, 50, 6.25, 0.781How to code in Python or Java below Algorithm # 10 General Algorithm for Testing Loosless Join DecompositionInput: A universal relation R, a decomposition D={R1,R2,...Rm}of R , and a set F of functional dependencies.1. Create an initial matrix S with one row for each relation Riin D, and one column for each attribute Aj in R.2. Set S(i,j)= bij for all matrix entries.( Note that each bij isa distinct symbol associated with indices (i,j) ).3. For each row i representing relation schema RiFor each column j representing attribute AjIF the relation Ri includes attribute Aj then set S(i,j)= aj.( Note that aj is a distinct symbol associated with index j)4. Repeat the following loop until a complete loop execution results in no changes to SFor each functional dependency X→Y in FFor all rows in S that have the same symbols in the columns corresponding toattributes in X.Make the symbols in each column that correspond to anattribute in Y be the same in all these rows as follows:▪ If any of the…How to code in Python or Java below Algorithm # 10 General Algorithm for Testing Loosless Join DecompositionInput: A universal relation R, a decomposition D={R1,R2,...Rm}of R , and a set F of functional dependencies.1. Create an initial matrix S with one row for each relation Riin D, and one column for each attribute Aj in R.2. Set S(i,j)= bij for all matrix entries.( Note that each bij isa distinct symbol associated with indices (i,j) ).3. For each row i representing relation schema RiFor each column j representing attribute AjIF the relation Ri includes attribute Aj then set S(i,j)= aj.( Note that aj is a distinct symbol associated with index j)4. Repeat the following loop until a complete loop execution results in no changes to SFor each functional dependency X→Y in FFor all rows in S that have the same symbols in the columns corresponding toattributes in X.Make the symbols in each column that correspond to anattribute in Y be the same in all these rows as follows:▪ If any of the…
- Consider this query that retrieves from the text’s Companydatabase the SSN and last name of employees who earn more than10000 and have a daughter and a sonSELECT ssn, lnameFROM dependent xINNER JOIN employee e ON (x.essn = e.ssn)INNER JOIN dependent y ON (y.essn = e.ssn)WHERE x.relationship = 'Son’and y.relationship = 'Daughter’and e.salary > 10000Create a query tree for the aboveDesign a data structure for a set in which insertions, deletions, and membership queries can be processed in O(1) tim e in the worst case. You m ay assume that the set elements are integers drawn from a finite set {1, 2,...,n}.Suppose you have a relation containing x, y coordinates and names of restaurants. Suppose also that the only query that will be asked are of the following forms. The query specified a point and asks if there is a restaurant exactly at that point. Which type of index would be preferable, R-Tree or B-tree? Why?
- The following query is given as an expression of relational algebra.Project[Projects.jid,Projects.name,Orders.price](Join[Projects.jid=Orders.jid]( Select[budget>500.000](Projects), Select[date>’1/1/2010’](Orders)))All tables have hash indexes defined on keys. We have B+ trees defined forOrders.date and Projects.budget, and a hash index on Orders.jid.Suppose our DBMS includes the implementations of the index nested loops join and thesort-merge join. Find a query plan that reads the least number of blocks from the disk.Write all assumptions.How does query optimization differ when querying against nested JSON objects as compared to flat key-value pairs?For the following query:Map it to a query treeProvide a simplified WHERE clauseMap a query with simplified WHERE clause in the above 2) to a query treeSELECT ENAME, PNAMEFROM EMP, ASG, PROJWHERE (DUR > 12 OR RESP = "Analyst") ANDEMP.ENO = ASG.ENO AND(TITLE = "Elect. Eng."OR ASG.PNO < "P3") AND(DUR > 12 OR RESP NOT= "Analyst") ANDASG.PNO = PROJ.PNO