The Bottom Line: Types of Indexes in Java

Generation ECC200 in Java The Bottom Line: Types of Indexes
The Bottom Line: Types of Indexes
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A compound index is an index whose keys contain values derived from more than one data column A compound index is good when you want to search for, or sort by (a) the left-most column or (b) the left-most column and any of the other columns Over indexing is useless because the DBMS often picks only one index as a driver The way to make use of an index on a second column is to put the column in a compound index Use compound indexes if queries often contain the same columns, joined with AND Use compound indexes if you have any key based on a one-character column The left-most column in a compound index should be the one that occurs in queries most often It should also be the most selective column When everything in the select list is in the index that will be used, the index is called a covering index Ordinarily, using a covering index will save one disk read, but only if the columns in the select list exactly match the columns in the covering index You lose the gain if you select functions or literals, or if you put the column names in a different order Whenever possible, persuade the DBMS to use a covering index regardless of whether it's searching for anything If the rows in the table are large, and the index keys are small, persuade the DBMS to use a covering index The benefits of "treating the index as a table" are often significant Just remember that (a) DBMSs never use covering indexes when there are joins or groupings, (b) the index selection can't be used for UPDATE statements, and (c) adding frequently changed columns to indexes strictly to make them covering indexes violates the principle that indexes should not be volatile Index selectivity is calculated as:
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Selectivity can be less than one if NULLs are indexed, or it can be less than one if duplicate keys are allowed When selectivity equals one, you have perfect selectivity and a unique index If the DBMS knows in advance a value can occur only once, it can exit the loop quickly after it has found that value It won't bother reading and checking again So unique indexes can save time Be prepared to drop redundant indexes When defining a compound index, put the most selective key on the left
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There are two main types of cluster indexes: "strong" clusters and "weak" clusters Strong clusters have these characteristics:
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The leaf level of a strong-clustered index doesn't contain index keys Instead, the leaf level contains the data rows themselves All data rows are in order Strong clusters are good for GROUP BY, ORDER BY, and WHERE clauses, and for long keys INSERTs are harder with strong clusters because you have to make room between existing rows to fit in the new value according to cluster key order But two subsequent INSERTs probably won't go to the same place, so clusters reduce contention UPDATEs are harder with strong clusters because any change in the cluster key means the row order can change too But you are less dependent on ROWID with clusters; access using the cluster key is almost as quick Updates that affect the cluster key will be huge and slow The primary rule for choosing a strong cluster key is Let the cluster key be the primary key The secondary rule for choosing a strong cluster key (for situations where the primary key isn't an obvious choice) is Choose a cluster key with these characteristics: (a) not volatile, (b) short and preferably an integer, (c) unique, (d) on which you'll most often want to do range searches, and (e) in the order in which you'll want to get results If you want quick access to a table's strong cluster-key columns alone, make a nonclustered index of the same columns The index must be a covering index and must have a short key
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Weak clusters have these characteristics:
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Data rows may be in order, but the DBMS does not guarantee this Weak clusters are good for GROUP BY, ORDER BY, and WHERE clauses The primary rule for choosing a weak cluster key is Base the cluster key on a foreign key or base the cluster key on the column with which you most often will do range searches or sequential passes
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Beware of the cluster key that is monotonically sequential The problem with monotonics (aka serials) is that the nth row and the (n + 1)th row will both fit in the same page so there might be contention for the same resource Usually, in multiuser systems, you want rows to be dispersed The benefits of clustered indexing depend on a monster assumption that you want to retrieve and sort by the cluster key far, far more often than with any other key Choose your cluster keys accordingly
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