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    <p>As with all optimizer-related statistics, these values are estimates with varying degrees of accuracy from whenever statistics were gathered on the table. As such, it is entirely expected that they would be close but not completely accurate and entirely possible that they would be wildly incorrect.</p> <p>When you gather statistics, you specify a percentage of the rows (or blocks) that should be sampled. It is possible to specify a 100% sample size, in which case Oracle would examine every row, but it is relatively rare to ask for a sample size nearly that large. It is much more efficient to ask for a much smaller sample size (either explicitly or by letting Oracle automatically determine the sample size). If your sample of rows happens not to include the one row with a value of 1000, the <code>HIGH_VALUE</code> would not be 1000, the <code>HIGH_VALUE</code> would be 5 assuming that is the largest value that the sample saw.</p> <p>Statistics are also a snapshot in time. By default, 11g will gather statistics every night on objects that have undergone enough change since the last time that statistics were gathered on that object to warrant refreshing the statistics though you can disable that job or change the parameters. So if you gather statistics today with a 100% sample size in order to get a <code>HIGH_VALUE</code> of 1000 and then insert one row with a value of 3000 and never modify the table again, it's likely that Oracle would never gather statistics on that table again (unless you explicitly requested it to) and that the <code>HIGH_VALUE</code> would remain 1000 forever. </p> <p>Assuming that there is no histogram on the column (which is another whole discussion), Oracle uses the <code>LOW_VALUE</code> and <code>HIGH_VALUE</code> to estimate how selective a particular predicate would be. If the <code>LOW_VALUE</code> is 1, the <code>HIGH_VALUE</code> is 1000, there are 1,000,000 rows in the table, there is no histogram on the column, and you run a query like</p> <pre><code>SELECT * FROM some_table WHERE column_name BETWEEN 100 and 101 </code></pre> <p>Oracle will guess that the data is uniformly distributed between 1 and 1000 so that this query would return 1,000 rows (multiplying the number of rows in the table (1 million) by the fraction of the range the query covers (1/1000)). This selectivity estimate, in turn, would drive the optimizer's determination of whether it would be more efficient to use an index or to do a table scan, what join methods to use, what order to evaluate the various predicates, etc. If you have a non-uniform distribution of data, however, you'll likely end up with a histogram on the column which gives Oracle more detailed information about the distribution of data in the column than the <code>LOW_VALUE</code> and <code>HIGH_VALUE</code> provide.</p>
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    1. COThank you for your very thorough response, I have another small follow-up question though; in your example, you used a range predicate (BETWEEN). If I were to have a query with an equality predicate (for example: WHERE column_name = 100), then it would NOT make use of the HIGH_VALUE and LOW_VALUE data am I correct? In this case the selectivity should be 1/NUM_DISTINCT? Thanks
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    2. CO@BYS2 - Correct, assuming the value is between the `LOW_VALUE` and the `HIGH_VALUE`. If you are querying for a value that is outside the range that Oracle expects to have data, it may adjust the cardinality estimate downward from 1/`NUM_DISTINCT`
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    3. CObrilliant, thank you very much!
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