Indexes and Joins in Font

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Indexes and Joins
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Very few queries involve just a single table, and one of the most common operations in a query is the join. Making joins efficient is certainly worthwhile. Joins involve comparing the values of fields in each of the tables involved in the join. While a join can be on any field, a very common situation is joining the foreign key in one table to the primary key in the table it is referencing. Figure 9-4 shows the Entry table and some columns from the Member table. In the Entry table, MemberID is a foreign key referring to the Member table, which means that any value in MemberID in the Entry table must already exist in the Member table. The data was split into these two separate tables to avoid the updating problems discussed in 1. However, many queries involving the Entry table will also require information from the Member table (for example, a member s name), so we need to join the tables as shown in Listing 9-4. A similar join between the Entry and Tournament tables is also likely to be carried out often.
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Listing 9-4. Joining the Entry and Member Tables SELECT * FROM Member m INNER JOIN Entry e ON m.MemberID = e.MemberID
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How does a database management system carry out a join between the Entry and Member tables Well, it can take many approaches. You don t need to specify which approach to take, as the query optimizer in your database software will choose the most efficient one, as discussed shortly. However, it is useful to have a bit of an idea of what may happen, so you can make some informed decisions about adding indexes. One approach to joining tables is called nested loops. This means that you scan down the rows in one table, and for each row, you look through all the rows in the other table to find matches for the join condition. The nested-loop approach is depicted in Figure 9-5.
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CHAPTER 9 EFFICIENC Y C ON SIDE RATIONS
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Part of Member table
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Part of Entry table
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Figure 9-4. A join will often occur on the two MemberID fields in the Member and Entry
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tables.
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For each row in first table...
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Find match in second table...
Figure 9-5. Nested-loops approach to finding rows with matching MemberIDs
CHAPTER 9 EFFICIENC Y C ON SIDE RATIONS
Obviously, which table is in the outside loop will make a difference. If we start scanning the Entry table, we need to be able to quickly find the row with the matching MemberID in the Member table. If we start by choosing rows in the Member table, we need to quickly find the matching MemberID in the Entry table. Because there will always be an index on the primary key MemberID in the Member table, the first option will always be quite efficient. The picture in Figure 9-5 shows the outside loop being around the Member table. For each row, the database system will need to search for the matching row in the Entry (inner) table. If there is an index on the foreign key MemberID in the Entry table, this option will also be a possible choice. Your query optimizer software will do all the sums and figure out the best way. Another approach to doing a join is to first sort both tables by the join field. It is then very easy to find matching rows. This is called a merge join and is shown in Figure 9-6.
First sort on matching field
First sort on matching field
Then compare
Figure 9-6. A merge-join approach first sorts each table by the field being compared.
Sorting each table as in Figure 9-6 is an expensive operation. However, if the tables are already sorted (they both have a clustered index on the join field MemberID), then this merging operation is very efficient.
What Should We Index
We have two types of indexes, clustered and nonclustered, and as you saw in the previous section, it can make quite a difference which you use. Clustered indexes provide rapid access to all the information in a row via the field on which you have indexed. For this reason, you need very good reasons not to have the primary key as the clustered index on a table.
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