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admin:indexing:strategies:aggregations [2012/01/26 23:30] doc |
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| Count aggregations are any SELECT statements that request "COUNT(*)", "COUNT(column)", or "COUNT(DISTINCT column)", regardless of whether there is a GROUP BY clause. These queries are optimized using a collection of Omnidex indexes. Each column that is referenced in the GROUP BY clause and referenced in the COUNT clause must be indexed using a standard Omnidex index. Omnidex will use all of these indexes in combination to optimize the query. | Count aggregations are any SELECT statements that request "COUNT(*)", "COUNT(column)", or "COUNT(DISTINCT column)", regardless of whether there is a GROUP BY clause. These queries are optimized using a collection of Omnidex indexes. Each column that is referenced in the GROUP BY clause and referenced in the COUNT clause must be indexed using a standard Omnidex index. Omnidex will use all of these indexes in combination to optimize the query. | ||
| - | The advantage of this approach to optimizing queries is that a small number of indexes can support nearly any combination of GROUP BY columns, providing the highest performance at the least cost. | + | The advantage of this optimization approach is that a small number of indexes can support nearly any combination of GROUP BY columns, providing high performance at little cost. |
| - | There are some situations in which specialized index is better for optimizing a query. When the GROUP BY column have especially high cardinality, such as over 64,000 distinct values, it will be necessary to create a multi-column index as described below. Additionally, if the same GROUP BY columns are used repeatedly, a multi-column index will perform faster. | + | There are some situations in which specialized indexes are better for optimizing a query. When a GROUP BY column has especially high cardinality, such as over 64,000 distinct values, it is necessary to create a multi-column index as described below. Additionally, if the same GROUP BY columns are used frequently, a multi-column index will provide even faster performance. |
| ==== Optimizing Other Aggregations ==== | ==== Optimizing Other Aggregations ==== | ||
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| In this example, the COUNT(*) does not require any additional indexes. | In this example, the COUNT(*) does not require any additional indexes. | ||
| - | <code sql> | + | <code> |
| select count(*) | select count(*) | ||
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| In this example, the COUNT(*) does not require any additional indexes, but the GROUP BY clause requires an index. | In this example, the COUNT(*) does not require any additional indexes, but the GROUP BY clause requires an index. | ||
| - | <code sql> | + | <code> |
| select GENDER, count(*) | select GENDER, count(*) | ||
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| In this example, the GROUP BY clause contains columns from multiple parents. | In this example, the GROUP BY clause contains columns from multiple parents. | ||
| - | <code sql> | + | <code> |
| select C.DESCRIPTION, S.DESCRIPTION, H.CITY, count(DISTINCT H.ZIP) | select C.DESCRIPTION, S.DESCRIPTION, H.CITY, count(DISTINCT H.ZIP) | ||
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| In this example, both SQL statements can be satisfied by one Omnidex index. | In this example, both SQL statements can be satisfied by one Omnidex index. | ||
| - | <code sql> | + | <code> |
| select GENDER, BIRTHDATE, count(DISTINCT HOUSEHOLD) | select GENDER, BIRTHDATE, count(DISTINCT HOUSEHOLD) | ||
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| - | <code sql> | + | <code> |
| select HOUSEHOLD, GENDER, count(*) | select HOUSEHOLD, GENDER, count(*) | ||
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| This sample environment file shows the Omnidex indexes that will optimize these queries. | This sample environment file shows the Omnidex indexes that will optimize these queries. | ||
| - | <code sql> | + | <code> |
| create environment | create environment | ||
| in "simple.xml" | in "simple.xml" | ||