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+ | ~~NOTOC~~ | ||
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{{page>:top_add&nofooter&noeditbtn}} | {{page>:top_add&nofooter&noeditbtn}} | ||
- | ====== Administration: Indexing Strategies ====== | + | ====== Administration: Omnidex Indexing ====== |
===== Indexing Concepts ===== | ===== Indexing Concepts ===== | ||
- | **[[admin:indexing:concepts:home|Overview]]** | | + | [[admin:indexing:concepts:home|Overview]] | |
- | [[admin:indexing:concepts:basics|Basics]] | | + | |
[[admin:indexing:concepts:criteria|Criteria]] | | [[admin:indexing:concepts:criteria|Criteria]] | | ||
[[admin:indexing:concepts:joins|Joins]] | | [[admin:indexing:concepts:joins|Joins]] | | ||
- | [[admin:indexing:concepts:aggregations|Aggregations]] | | + | **[[admin:indexing:concepts:aggregations|Aggregations]]** | |
[[admin:indexing:concepts:ordering|Ordering]] | | [[admin:indexing:concepts:ordering|Ordering]] | | ||
- | [[admin:indexing:concepts:retrieval|Retrievals]] | | + | [[admin:indexing:concepts:retrieval|Retrievals]] |
- | [[admin:indexing:concepts:alternatives|Alternatives]] | + | |
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==== Aggregations ==== | ==== Aggregations ==== | ||
- | Indexes are most commonly used for processing criteria and joining tables, but they can also be quite helpful for aggregations. An index has the advantage of already being in sorted order. If a multi-column index contains all of the columns in the GROUP BY clause, as well as all of the columns referenced in COUNT, SUM, AVERAGE, MIN and MAX functions, the the index can simply be scanned in sorted order, and the aggregations can be returned without accessing the database. | + | Omnidex indexing is valuable for processing aggregations. Aggregations involve the use of the COUNT, SUM, AVERAGE, MIN and MAX functions, and may or may not include a GROUP BY clause. Omnidex first considers the type of aggregation. Queries to request a COUNT(*) without a GROUP BY clause are the simplest queries. These are optimized differently than queries that use a GROUP BY clause or use other aggregation functions. |
+ | |||
+ | === Simple COUNT(*) Queries === | ||
+ | |||
+ | Omnidex always maintains a count when accessing its indexes. Whether processing criteria or performing a table join, a count is always available. Counts that simply request COUNT(*) are subsequently the simplest to optimize. | ||
+ | |||
+ | The following query requests a simple count from a table. | ||
+ | |||
+ | <code> | ||
+ | |||
+ | select count(*) | ||
+ | from HOUSEHOLDS | ||
+ | where STATE = 'CO' and | ||
+ | CITY = 'Boulder' and | ||
+ | ZIP = '80301'; | ||
+ | </code> | ||
+ | |||
+ | |||
+ | Omnidex will search its indexes to process the criteria, and it will have the count ready when it is complete. There is no additional work needed to return the count, and no access to the database is required. Since these types of queries are very common, this makes Omnidex especially fast as a count engine. | ||
+ | |||
+ | === General Aggregations === | ||
+ | |||
+ | Queries that aggregate data often use GROUP BY clauses or other aggregation functions. These queries can be optimized with Omnidex indexing as well. The following query shows counts from the HOUSEHOLDS table aggregated by STATE, CITY and ZIP. | ||
+ | |||
+ | <code> | ||
+ | |||
+ | select STATE, CITY, ZIP, count(*) | ||
+ | from HOUSEHOLDS | ||
+ | group by STATE, CITY, ZIP | ||
+ | </code> | ||
+ | |||
+ | An index has the advantage of already being in sorted order. If the STATE, CITY and ZIP columns are all individually indexed with Omnidex, then these three indexes will be used in combination to perform the aggregation. The STATE index will be scanned, followed by the CITY index, followed by the ZIP index. The aggregations can be returned without accessing the database. | ||
+ | |||
+ | Some aggregations benefit from multi-column indexes, such as a single index with the STATE, CITY and ZIP. This is more efficient than using three separate indexes, and is especially important if any of the columns contain fairly unique values. It is also required for aggregations that use the SUM, AVERAGE, MIN and MAX functions. | ||
+ | |||
+ | These techniques can be used even after other indexes have been used to process criteria. After the criteria has been processed, the isolated record pointers can be used as a filter when the aggregation index is scanned. This allows for great flexibility, since the columns referenced in criteria do not need to be included in the aggregation index. In the following query, the same aggregations are restricted to people in the United States. | ||
+ | |||
+ | <code> | ||
+ | |||
+ | select STATE, CITY, ZIP, count(*) | ||
+ | from HOUSEHOLDS | ||
+ | where COUNTRY = 'US' | ||
+ | group by STATE, CITY, ZIP | ||
+ | </code> | ||
- | This technique can be used even after other indexes have been used to process criteria. After the criteria has been processed, the isolated record pointers can be used as a filter when the aggregation index is scanned. This allows for great flexibility, since the columns referenced in criteria do not need to be included in the aggregation index. | + | Omnidex will first qualify the rows in the United States, and will then allow those record pointers to be used as a filter against the aggregation index. |
- | As was seen with criteria and table joins, sometimes an index is not the fastest approach to aggregating data. Using an index for aggregations requires scanning the index from the beginning to the end. If the criteria isolates only a small number of rows, it would be faster to simply retrieve the rows and aggregate them directly, than to scan millions of entries in an index. | + | === When to Avoid Indexes === |
- | As a general rule of thumb, it is valuable to use indexing for processing criteria when aggregating greater than 0.01% of the rows in a table. If aggregating less than 0.01% of the rows, the overhead of indexes exceeds its gains, and it is better to simply scan the data. | + | As was seen with criteria and table joins, sometimes an index is not the fastest approach. Using an index for aggregations usually requires scanning the index from the beginning to the end, even when there is criteria. If the criteria isolates a very small number of rows, it would be faster to simply retrieve the rows and aggregate them directly, than to scan millions of entries in an index. |
- | Omnidex automatically considers this issue when optimizing SQL queries. Omnidex maintains a configuration setting called the AGGREGATION_THRESHOLD which controls whether to use an indexes to resolve aggregations. The AGGREGATION_THRESHOLD defaults to 0.01%, meaning that indexes will be used to aggregate more than 0.01% of the data. This [[admin:optimization:config:aggregation|setting]] can be overridden as needed. | + | As a general rule of thumb, it is valuable to use indexing for processing criteria when aggregating greater than 0.01% of the rows in a table. Omnidex automatically follows this rule of thumb, and you may find that some queries don't use indexes for this very reason. Omnidex also allows this threshold to be configured. A setting called the AGGREGATION_THRESHOLD is set to 0.01% by default, but can be [[admin:optimization:config:thresholds|changed]] if needed. |
- | The [[admin:indexing:basic:aggregations|following article]] explains basic strategies for optimizing aggregations. | + | ==== ==== |
+ | The [[admin:indexing:strategies:aggregations|following article]] explains basic strategies for optimizing aggregations. | ||
===== ===== | ===== ===== | ||
- | **[[admin:indexing:concepts:criteria|Next]]** | + | **[[admin:indexing:concepts:joins|Prev]]** |
+ | **[[admin:indexing:concepts:ordering|Next]]** | ||
====== Additional Resources ====== | ====== Additional Resources ====== |