NULLs & Outer Joins. Objectives of the Lecture :

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1 Slide 1 NULLs & Outer Joins Objectives of the Lecture : To consider the use of NULLs in SQL. To consider Outer Join Operations, and their implementation in SQL.

2 Slide 2 Missing Values : Possible Strategies Use a special value to represent missing data. E.g. N/A, T.B.A. The special value must have the same data type as the data that is missing, so it can be stored with the data that is known. Requires no special facility from the DBMS. Use NULL to represent missing data. NULL is the absence of a value. space NULL 0 NULL character NULL is not part of any data type. Requires special support from the DBMS. SQL DBMSs provide this support. So most DBs use NULLs to represent missing data. This is revision based on part of the earlier lecture The Data in a Relation. Slide 3 Display of SQL NULLs EmpNo EName M-S Sal E3 Smith S 18,000 E5 Robinson M 24,000 E9 Graham S E1 Robson D 32,500 E2 Atkins 24,000 E6 Blakelaw M 54,000 E7 Mortimer D 28,000 E4 Fenwick S 40,000 Blank space in Oracle. Keyword NULL in other SQL DBMSs. Other possibilities in other DBMSs. This is how Oracle displays NULLs in a retrieved table. Other SQL DBMSs use different conventions to display a NULL.

3 Slide 4 Dealing with NULLs in SQL Tables Three situations arise : Comparisons of column values. This occurs in the SQL equivalents of the Restrict and the various Join operations, plus Deletions and Updates. Calculations involving column values. This occurs in the SQL equivalents of the GroupBy and Extend operations. Comparisons of row values. This occurs in the SQL equivalents of the Project, GroupBy, Union, Intersect, and Difference operations. Each of these three cases is now considered in turn :-

4 Case One : Comparison of Column Values Slide 5 Comparison of Column Values (1) SQL provides special comparators to check for NULL :- X IS NULL X IS NOT NULL Let X be a numeric column. If X has a value, the comparison X = 3 makes sense. It should yield true or false. Suppose X is NULL. An error should arise. In fact SQL treats the NULL as representing an existing but unknown value. Comparison returns maybe. Rationale : We don t know if X = 3 because X is NULL (= not available). Note : X may represent some other case of missing data (e.g. not applicable, does not exist). The result is still maybe even though this is then illogical. NULLs can be used to represent many different cases of missing data. Each different case may require its own rationale for how to handle missing data, and they can vary significantly. So SQL s choice of rationale will generally only be valid in certain cases.

5 Slide 6 Comparisons of Column Values (2) Let X and Y be a numeric columns. Consider the comparison X = Y Suppose X and Y are both NULL. The result is maybe not true. NULL is not the same as maybe. Absence of a value. A truth value. SQL uses NULL to mean maybe! To avoid confusion in the remainder of the lecture, we will still assume the value maybe exists in SQL.

6 Slide 7 Restricts, Joins, Updates and Deletions Restrict SELECT * FROM TableName WHERE condition ; Join SELECT * FROM Table1 NATURAL JOIN Table2 ; Delete Update DELETE FROM TableName WHERE condition ; UPDATE TableName SET column(s) = new value(s) WHERE condition ; Column comparison used as a condition Similarly for other kinds of Join. Restrict / Join / Delete / Update action taken only where condition evaluates to true, not where it evaluates to maybe or false. In principle, there is no problem with this. In practice, problems arise because the presence of NULLs is forgotten, or it is assumed that SQL will take the same reasonable approach to NULLs that the user does, when in fact SQL doesn t take that approach. We need to assume NULLs may occur and include appropriate conditions for them. Consider an example of what happens if this is forgotten :-

7 Slide 8 Unexpected Results (1) They arise when forgetting that the condition can evaluate to maybe. Example :- SELECT * FROM EMP WHERE Sal >= UNION SELECT* FROM EMP WHERE Sal < ; If column Sal contains any NULLs, the result will not re-create table EMP. the 2 Restrictions will not necessarily contain all the rows of EMP between them. Of course it is not assumed that you will use 2 queries simply to re-create the original table! Each Restriction condition is the logical inverse of the other. Consequently there is a temptation to think that those rows not retrieved from the table by one query must inevitably be retrieved by the other query. This is guaranteed to be true if it were not for NULLs. If there are NULLs in the table, there will be a third set of rows only retrieved from the table by a Restriction condition that retrieves those rows containing NULLs. Therefore it is essential to decide when formulating the required Restriction condition whether the NULL-including rows should be retrieved as well. The following shows the Restriction conditions that correspond to the three sets of rows that arise when NULLs are included.

8 Slide 9 Unexpected Results (2) To ensure the table is re-created, re-write the query as follows :- In general, adjust statements to reflect the NULL possibility. SELECT * FROM EMP WHERE Sal >= UNION SELECT * FROM EMP WHERE Sal < UNION SELECT * FROM EMP WHERE Sal IS NULL ; In this particular case, should the rows with NULL Sals be retrieved with the salaries that are 20,000 or more, or with those that are less than 20,000; or do we genuinely want to ignore the NULL Sals?

9 Slide 10 Join involving NULLs : Example P# S# Qty Details P1 S1 5.. P2 S2 7.. R P# S# Qty P1 S1 5 P2 10 P2 S2 7 S S# Details S 1.. S 2.. S 3.. This row does not appear in the result. SELECT * FROM R Natural Join S ; If we want to include the missing row, we need to replace the R Natural Join S with R Join S Using On( some condition involving NULLs )

10 Slide 11 Oracle s NVL Function NVL supplies a value to use whenever a NULL is encountered. It can be used in SELECT and WHERE phrases. Example : NVL( Sal, 0 ) Put a column name in the first position. Put a value in the second position. This yields the value of the Sal column, except that if Sal is NULL, then a value of zero is returned. NVL can be used to ensure a comparison always yields true or false, and never maybe. Value S is used in the comparison when M-S is NULL. Comparison can never return maybe. Example :... WHERE NVL( M-S, S ) <> M Most SQL DBMSs have some function analogous to Oracle s NVL, although it may be somewhat different. Such a function can be very useful in practice, and can make it easier to design conditions that cope with possible NULLs.

11 Case Two : Calculations Involving Column Values Slide 12 Calculations Involving Column Values These arise in two situations : Scalar calculations along rows Extend EmpNo EName M-S Sal Aggregate calculations along columns GroupBy E3 Smith S E5 Robinson M 24,000 E9 Graham S E1 Robson D 32,500 E2 Atkins M E6 Blakelaw M E7 Mortimer D 28,000 E4 Fenwick S 40,000 We will now consider these two situations :-

12 Slide 13 Scalar Calculations Any calculation involving a NULL results in a NULL. Examples : let n be NULL. Then :- n + 1 NULL n concatenate ABCD NULL n - n NULL (not zero) Example :- SELECT Sal AS NewSal FROM EMP ; So NewSal will be NULL whenever Sal is NULL. This can give some surprising results. Take care! Slide 14 Aggregate Calculations If the columns being aggregated contain one or more NULLs, then the answer from : Sum Avg Min ignores the NULLs. Max Count( Distinct ) Count(*) includes the NULLs. Not all of these are mathematically valid. Take note and take care!

13 Slide 15 Example : Aggregation in GroupBy EmpNo EName M-S Sal Total M-S 40,000 S 24,000 M 60,500 D E3 Smith S E5 Robinson M 24,000 E9 Graham S E1 Robson D 32,500 E2 Atkins M E6 Blakelaw M E7 Mortimer D 28,000 E4 Fenwick S 40,000 SELECT Sum(Sal) AS Total, M-S FROM EMP GROUP BY M-S ; We consider here the aggregate calculation aspects of GroupBy, not the grouping aspects. Depending on the circumstances, what SQL does about NULLs may or may not be appropriate. See the earlier discussion on the rationale concerning missing data.

14 Case Three : Comparison of Row Values Slide 16 Comparisons of Rows In SQL, two rows are identical if : they have the same number of attributes; corresponding attributes are of the same data type; corresponding attributes have the same value. In an SQL row comparison, a NULL compared to a NULL true In an SQL column comparison (e.g. for a Join operation) a NULL compared to a NULL maybe Different!!

15 Slide 17 Example : Row Comparison E_No E_Name M_S Sal E2 Atkins 24,000 E2 Atkins 24,000 Comparison of M-S column values : Row Comparison : 2 NULLs are defined to be identical. A comparison yields true!! these 2 rows are identical. Column Comparison : 2 NULLs are not assumed identical. A comparison yields maybe!! these rows are rejected. Slide 18 Project, GroupBy, & Set Operators Project SELECT DISTINCT ColumnName(s) FROM TableName ; GroupBy SELECT Aggregation(s), GroupingCol(s) FROM TableName GROUP BY GroupingCol(s) ; Set Ops SELECT * FROM TableName1 UNION SELECT * FROM TableName2 ; Similarly for the other Set Ops, Intersect & Except/Minus. Project / GroupBy (grouping rows) / Union / Intersect / Except action taken on the basis that all NULLs are identical. Consider some examples :-

16 Slide 19 Example : Projection SELECT DISTINCT M-S FROM EMP ; EmpNo EName M-S Sal M-S S M D W E3 Smith S 18,000 E5 Robinson M 24,000 E9 Graham 18,000 E1 Robson D 32,500 E2 Atkins 24,000 E6 Blakelaw M 54,000 E7 Mortimer D 28,000 E4 Fenwick W 40,000 Slide 20 Example : Grouping in GroupBy SELECT Aggregation, M-S FROM EMP GROUP BY M-S ; EmpNo EName M-S Sal Aggregate Agg-Val1 Agg-Val2 Agg-Val3 Agg-Val4 M-S S M D E3 Smith S 18,000 E5 Robinson M 24,000 E9 Graham 18,000 E1 Robson D 32,500 E2 Atkins 24,000 E6 Blakelaw M 54,000 E7 Mortimer D 28,000 E4 Fenwick S 40,000 This example concerns the grouping of rows, not the calculation of aggregate values.

17 Slide 21 Example : Union Operation EmpNo EName M-S Sal EmpNo EName M-S Sal E3 Smith S 18,000 E5 Robinson M 24,000 E9 Graham S E1 Robson D 32,500 E2 Atkins 24,000 E6 Blakelaw M 54,000 E3 Smith S 18,000 E5 Robinson M 24,000 E9 Graham S E1 Robson D 32,500 E2 Atkins 24,000 Union EmpNo EName M-S Sal E1 Robson D 32,500 E2 Atkins 24,000 E6 Blakelaw M 54,000

18 Outer Joins Slide 22 Joins - Inner versus Outer All joins considered so far are Inner Joins. Only a subset of each operand s tuples appear in the result. These are the tuples that match each other in the 2 operands. (Match the comparison (of whatever kind) is true). The tuples don t appear in the result. Sometimes it is useful to have tuples in the result as well. Outer Join Three kinds of Outer Join, to retain in the result all the tuples from : Left operand, Right operand, Left and Right operands. Consider now some illustrations of Inner and Outer Joins. For convenience, a Natural Join is always assumed, but the same principles apply to every type of join.

19 Slide 23 Inner Joins Unmatched tuples are not in the result. (Natural) Slide 24 Outer Join : Left Some tuples are in the result. (Natural)???? padding

20 Slide 25 Outer Join : Right Some tuples are in the result. (Natural) padding???????? Slide 26 Outer Join : Full All tuples are in the result. (Natural)???? padding padding????????

21 Slide 27 Outer Joins in SQL What padding attribute values are used with the columns? SQL uses NULLs. What syntax is used for outer joins? An extension of the FROM phrase inner join syntax. Natural Join, Join Using( ColNames ), Join On( condition ). Each of these can be used for Left, Right and Full outer joins. 9 possibilities. Although 9 possible kinds of outer join may seem a lot to cope with, it is made easier to cope with by remembering that they are the same 3 kinds of joins as for inner joins, and each can be used orthogonally with the 3 kinds of Outer facility; i.e. we decide independently on the kind of join and the kind of Outer facility required, and then just put the two together.

22 Slide 28 SQL2 Outer Natural Joins SELECT * Left Outer optionally inserted FROM R Natural Right Join S ; Full Examples :- SELECT * FROM SUPP Natural Left Outer Join SHIP ; Result retains all the rows of LHS table, i.e. SUPP. SELECT * FROM SUPP Natural Right Join SHIP ; Result retains all the rows of RHS table, i.e. SHIP. Slide 29 The Other Two SQL2 Outer Joins SELECT * Left FROM R Right Join S Using ( attribute(s) ) ; Full Outer SELECT * Left optionally inserted FROM R Right Join S On ( condition ) ; Full Example :- SELECT * FROM SUPP Left Outer Join SHIP Using( S# ) ; Left and right refer to the tables written to left and right of the join operator. Logically only left or right is required, but it is convenient to have both. Useful syntax rules to remember : If outer is optionally used, it always comes after the keyword left/right/full. The keyword(s) left/right/full (outer) always come before the keyword join.

23 Slide 30 Oracle : Outer Joins Original Oracle syntax is completely non-standard. The idea is to add a (+) suffix to the name of the column that is in the table whose columns will receive the NULLs as padding. Regarding left and right, this is the exact opposite of the SQL standard. Example :- SELECT AttributeNames FROM SUPP, SHIP WHERE SUPP.S# = SHIP.S#(+) ; Do NOT use unless desparate! Old fashioned SQL1 join syntax is required. Left & right refer to columns in the WHERE phrase, not tables in the FROM phrase. Full join Union of left and right outer joins. This outer join syntax is peculiar to Oracle and used by no other DBMS. It has several disadvantages, and now that Oracle has provided its DBMSs with an SQL2 standard outer join syntax, you are strongly advised to use that syntax and avoid the old Oracle version. The old version is only mentioned for completeness - only an overview of it is given here - should you find that you need to use an old version of an Oracle DBMS that lacks the modern SQL2 syntax.