1. CS240A: Databases and Knowledge Bases Temporal Applications and SQL:1999 Carlo Zaniolo Department of Computer Science University of California, Los Angeles February 2003

2. Temporal Databases: Overview  Many applications  The problem is harder than what you think  Support for time in SQL: the good and the bad  A time ontology  Many approaches proposed  TSQL2  The physical level: efficient storage and indexing techniques.

3. An Introduction to Temporal Databases  Applications abound  A case study using SQL: Queries on time­varying data are hard to express in SQL.  Temporal databases provide built­in support for storing and querying time-varying information.

4. Applications Abound: Examples  Academic: Transcripts record courses taken in previous and the current semester or term and grades for previous courses  Accounting: What bills were sent out and when, what payments were received and when?  Delinquent accounts, cash flow over time  Money­management software such as Quickencan show e.g., account balance over time.  Budgets: Previous and projected budgets, multi­ quarter or multi­year budgets

5. Temporal DB Applications (cont.)  Data Warehousing: Historical trend analysis for decision support  Financial: Stock market data  Audit: why were financial decisions made, and with what information available?  GIS: Geographic Information Systems ()  Land use over time: boundary of parcels changeover time, as parcels get partitioned and merged.  Title searches  Insurance: Which policy was in effect at each point in time, and what time periods did that policy cover?

6. Temporal DB Applications (cont.)  Medical records: Patient records, drug regimes, lab tests.Tracking course of disease  Payroll: Past employees, employee salary history, salaries for future months, records of withholdingrequested by employees  Capacity planning for roads and utilities. Configuring new routes, ensuring high utilization  Project scheduling: Milestones, task assignments  Reservation systems: airlines, hotels, trains.  Scientific: Timestamping satellite images. Dating archeological finds

7. Temporal DBs Applications: Conclusion  It is difficult to identify applications that do not involve the management of temporal data.  These applications would benefit from built­in temporal support in the DBMS. Main benefits:  More efficient application development  Potential increase in performance

8. Reviewing the Situation  The importance of temporal applications has motivated much research on temporal DBs: but no satisfactory solution has been found yet:  SQL3 does not support temporal queries  Temporal DBs remain an open research problem.  The problem is much more difficult than it appears at first: we have become so familiar with the time domain that we tend to overlook its intrinsic complexity.  Some of the solutions proposed by researchers lack ease of use and amenability to efficient implementation

9. Case Study  University of Arizona's Office of Appointed Personnel has some information in a database. Employee(Name, Salary, Title)  Finding an employee's salary is easy.  The OAP wishes to add the date of birth Employee(Name, Salary, Title, DateofBirth DATE) SELECT Salary, DateofBirth FROM Employee WHERE Name = 'Bob'

10. Converting to a Temporal Database  Now the OAP wishes to computerize the employment history.  Adding validity periods to tuples: Employee (Name, Salary, Title, DateofBirth, Start DATE, Stop DATE)

11. Converting to a Temporal Database Example Employee (Name, Salary, Title, DateofBirth,Start DATE, Stop DATE) NameSalaryTitleDateofBirthStartStop Bob 60000 AssistantProvost 1945­04­19 1993­01­01 1993­06­01 Bob 70000 AssistantProvost 1945­04­19 1993­06­01 1993­10­01 Bob 70000 Provost 1945­04­19 1993­10­01 1994­02­01 Bob 70000 Professor 1945­04­19 1994­02­01 1995­01­01

12. Extracting the Salary  Find the employee's salary at a given time: e.g. the current one: SELECT Salary FROM Employee WHERE Name = 'Bob‘ AND Start <= CURRENT_TIMESTAMP AND CURRENT_TIMESTAMP <= Stop Instead of CURRENT_TIMESTAMP we could have given any time stamp or date

13. Distributing the Salary History  OAP wants to distribute to all employees their salary history.  Output: For each person, maximal intervals at each salary  Employee could have arbitrarily many title changes between salary changes. Name Salary Start Stop Bob 60000 1993­01­01 1993­06­01 Bob 70000 1993­06­01 1995­01­01

14. Extracting the Salary, cont. Alternative 1: Give the user a printout of Salary and Title information, and have user determine when his/her salary changed. Alternative 2: Use SQL as much as possible. Find those intervals that overlap or are adjacent and thus should be merged.

15. Bob’s Salary History in SQL CREATE TABLE Temp(Salary, Start, Stop) AS SELECT Salary, Start, Stop FROM Employee WHERE Name = 'Bob'; repeat UPDATE Temp AS T1 SET (T1.Stop) = (SELECT MAX(T2.Stop) FROM Temp AS T2 WHERE T1.Salary = T2.Salary AND T1.Start = T2.Start AND T1.Stop = T2.Start AND T1.Stop < T2.Stop) until no tuples updated;

16. Example  Initial table  After one pass  After two passes

17. Salary History (cont.)  Intervals that are not maximal must be deleted DELETE FROM Temp T1 WHERE EXISTS (SELECT * FROM Temp AS T2 WHERE T1.Salary = T2.Salary AND ( (T1.Start > T2.Start AND T1.Stop = T2.Start AND T1.Stop < T2.Stop) ) The loop is executed lgN times in the worst case, where N is the number of tuples in a chain of overlapping or adjacent, value­equivalent tuples. Then delete extraneous, non­ maximal intervals.

18. Alternative 3 : Entirely in SQL CREATE TABLE Temp(Salary, Start, Stop) AS SELECT Salary, Start, Stop FROM Employee WHERE Name = 'Bob'; SELECT DISTINCT F.Salary, F.Start, L.Stop FROM Temp AS F, Temp AS L WHERE F.Start < L.Stop AND F.Salary = L.Salary AND NOT EXISTS (SELECT * FROM Temp AS M WHERE M.Salary = F.Salary AND F.Start < M.Start AND M.Start < L.Stop AND NOT EXISTS (SELECT * FROM Temp AS T1 WHERE T1.Salary = F.Salary AND T1.Start < M.Start AND M.Start <= T1.Stop)) AND NOT EXISTS (SELECT * FROM Temp AS T2 WHERE T2.Salary = F.Salary AND ( (T2.Start < F.Start AND F.Start <= T2.Stop) OR (T2.Start < L.Stop AND L.Stop < T2.Stop)))

19. Alternative 4: Using More Procedural Code  Use SQL only to open a cursor on the table  Maintain a linked list of intervals, each with a salary; Initialize this linked list to empty; DECLARE emp_cursor CURSOR FOR SELECT Salary, Start, Stop FROM Employee; OPEN emp_cursor; loop: FETCH emp_cursor INTO :salary,:start,:stop; if no data returned then go to finished; find position in linked list to insert this information; go to loop; finished: CLOSE emp_cursor; iterate through linked list, printing out dates and salaries

20. A More Drastic Alternatives Reorganize the schema  Separate Salary, Title, and DateofBirth information: Employee1 (Name, Salary, Start DATE, Stop DATE) Employee2 (Name, Title, Start DATE, S top DATE)  Getting the salary information is now easy: SELECT Salary, Start, Stop FROM Employee1 WHERE Name = 'Bob‘  But what if we want a table with both salary and title?

21. Temporal Joins NameSalaryStartStop Bob600001993­01­011993­06­01 Bob700001993­06­011995­01­01 NameTitleStartStop BobAssistantProvost1993­01­011993­10­01 BobProvost1993­10­011994­02­01 BobFullProfessor1994­02­011995­01­01 NameSalaryTitleStartStop Bob60000AssistantProvost1993­01­011993­06­01 Bob70000AssistantProvost1993­06­011993­10­01 Bob70000Provost1993­10­011994­02­01 Bob70000FullProfessor1994­02­011995­01­01 Their Temporal Join: Employee 1 : Employee 2 :

22. Temporal Join in SQL SELECT E1.Name, Salary, Title, E1.Start, E1.Stop FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name=E2.Name AND E2.Start <= E1.Start AND E1.Stop <= E2.Stop UNION ALL SELECT E1.Name, Salary, Title, E1.Start, E2.Stop FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name = E2.Name AND E1.Start > E2.Start AND E2.Stop< E1.Stop AND E1.Start < E2.Stop UNION ALL SELECT E1.Name, Salary, Title E2.Start, E1.St FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name = E2.Name AND E2.Start > E1.Start AND E1.Stop <= E2.Stop AND E2.Start < E1.Stop UNION ALL SELECT E1.Name, Salary, Title E2.Start, E2.Stop FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name = E2 Name AND E2.Start => E1.Start AND E2.Stop <= E1.Stop AND NOT (E1.Start = E2.Start AND E1.Stop = E2.Stop)

23. Extracting the Salary History in TSQL2 SELECT Salary FROM Employee WHERE Name = 'Bob‘ There is no explicit mention of time in the query. By default the system returns the coalesced time history

24. Temporal Joins in TSQL2 SELECT E1.Name, Salary, Title FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name = E2.Name

25. Summary  Coalescing and temporal joins are very difficult to express in SQL.  Solutions proposed …  Special operators for period-based representation  TSQL2: avoid explicit operations on periods (implicit model)  Point-Based Representation  Time stamp attributes rather than tuples (difficult on tables but not on structured XML documents)  Others,including combinations of above (more than 40 counted)

26. Operators on Periods  A new aggregate called coalesce  An overlap operator for joins: SELECT E1.Name, Salary, Title FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name = E2.Name AND overlap(E1.Start,E1.End, E2.Start, E2.End ) Definition of overlap

27. Allen Operators on Intervals  Overlap,  Contains,  Meets,  Precedes, follows.  Contains is also applicable to sets of intervals.

28. Point-Based Model Employee1 (Name, Sal, Day ) Bob 6000 1993­01­01 … Bob 6000 1993­05­31 Bob 7000 1993­05­31 … Bob 7000 1994­12­31 Internally we might still use the period-based representation for point- based and TSQL2: NameSalaryStartStop Bob600001993­01­011993­06­01 Bob700001993­06­011995­01­01

29. Queries in Point Based  No coalescing needed in the query: e.g., project out salary: SELECT E1.Name, E1.Day FROM Employee1 AS E1  Temporal Joins are simple: SELECT E1.Name, Sal, Title FROM Employee1 AS E1, Employee2 AS E2 WHERE E1.Name = E2.Name AND E1.Day=E2.Day

30. Conclusions  Several alternatives, in terms of data model and SQL extensions to be used,  Internal representation often must be divorced from external one—adding to alternatives and complexity  New temporal clustering and indexing schemes should be used for maximum performance.