Figure 9-9 A clustered index in Java

Printer Data Matrix ECC200 in Java Figure 9-9 A clustered index
Figure 9-9 A clustered index
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The pointer from an index key to a data row is called a row locator The structure of the row locator depends on whether the data pages are stored in a heap or are clustered For a heap, a row locator is a pointer to the row For a table with a strong-clustered index, the row locator is the cluster key Strong clustering certainly looks like a winning idea Assume you have two tables based on Figure 9-8 and Figure 9-9 and execute this query on each:
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SELECT * WHERE column1 = 'SUSAN'
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Which query is faster Well, the DBMS will need three I/Os if it has a heap (two I/Os to scan the index and one more to get the data row) but only two I/Os if it has a cluster (two I/Os to scan the index and zero needed to get the data row) It doesn't really matter even if the data rows in the leaf
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page are likely to be twice as big as the index keys, because remember the earlier talk about the number of layers being the important criterion doubling the key size doesn't double the access time This advantage appears for strong-clustered indexes only With either a weak- or a strong-clustered index, data rows are in order But the fact that the expression WHERE column1 = 'SUSAN' works with one less I/O is an additional effect that appears only with strong-clustered indexes To sum it up, both varieties of clustered indexes are good for GROUP BY, ORDER BY, and WHERE clauses Strong clusters are also good for long keys (because a strong-clustered index on a long key takes no extra space for the leaf level) An extra benefit if the DBMS is Microsoft is automatic garbage collection (Microsoft doesn't have automatic garbage collection for ordinary heap tables) 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 There is no question that any changes that affect the cluster key will be huge and slow, because when the key value changes, the whole row must move in order to stay in order However, there is a simple remedy: Never update the cluster key In fact, under the hood, there is no such thing as an UPDATE of a cluster key the DBMS translates such an UPDATE to a DELETE followed by an INSERT Choice of clustered key The conventional advice is that you should have a clustered index for almost any table that's not tiny or temporary This means you have to pick a set of columns for the cluster key and it better be a good pick, because it is extremely inconvenient to change the cluster key after the table is full of data By definition, there can only be one cluster key because the rows can only have one order So what columns should form the cluster key Good news Many have asked that question before, and a body of sage counsel can guide the picking Unfortunately, there's also bad news priorities differ depending on whether the DBMS has strong or weak clustering When clustered indexes are strong, the primary key can be the cluster key This saves time and confusion, and is often the default behavior, so we'll just defer this piece of sage counsel to 10, "Constraints" In situations where the primary key isn't there or isn't an obvious choice for a cluster key, you should explicitly state that the primary key is nonclustered Then choose a cluster key with these characteristics:
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It shouldn't be volatile It shouldn't be a "serial" data type that is, the key should not auto-increment It should be short (preferably an integer) It should be unique (Some DBMSs for example, Microsoft will add a uniquifier integer if the key is not unique, but that's worth avoiding) It should be the column on which you'll most often want to do range searches It might as well have the order in which you'll want to get results
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However, when clustered indexes are weak, the rule "the primary key can be the cluster key" is weak too Here are two rules for choosing the cluster key for a weak-clustered index, especially popular among IBM experts:
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Base the cluster key on a foreign key The effect of clustering is that most rows with the same value for the foreign key will be together Therefore a search like this:
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