Table scan predicate with integrated semi-join filter
US-2024419650-A1 · Dec 19, 2024 · US
US10042872B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10042872-B2 |
| Application number | US-201514746465-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 22, 2015 |
| Priority date | May 22, 2015 |
| Publication date | Aug 7, 2018 |
| Grant date | Aug 7, 2018 |
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Methods and systems for database optimization include detecting a plurality of columns in an unoptimized database that co-appear in queries to the database. The plurality of columns are compacted into a single hyper-column to form an optimized database. Each entry in the hyper-column includes data from a corresponding entry in each of the plurality of columns. An interface is generated for the optimized database that accepts queries according to a schema for the unoptimized database and translates the queries into queries according to a schema for the optimized database.
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The invention claimed is: 1. A method for database optimization, comprising: detecting a plurality of columns in an unoptimized database that co-appear in queries to the database; compacting the plurality of columns into a single hyper-column using a processor to form an optimized database, wherein each entry in the hyper-column comprises data from a corresponding entry in each of the plurality of columns; and generating an interface for the optimized database that accepts queries according to a schema for the unoptimized database and translates said queries into queries according to a schema for the optimized database. 2. The method of claim 1 , wherein the plurality of columns co-appear in select clauses. 3. The method of claim 1 , wherein the plurality of columns co-appear in where clauses. 4. The method of claim 1 , further comprising generating an index for the hyper-column. 5. The method of claim 4 , wherein entries for the hyper-column comprise only numerical data and wherein the index is an R-tree. 6. The method of claim 1 , further comprising compressing entries in the hyper-column if the entries in the hyper-column consist of textual data. 7. The method of claim 1 , wherein detecting the plurality of columns that co-appear in queries to the database comprises performing clustering across all columns in the database. 8. The method of claim 7 , wherein performing clustering comprises an approximation of K-minimum cut. 9. The method of claim 1 , wherein generating the interface comprises generating a virtual view of the database according to the schema for the unoptimized database. 10. A method for database optimization, comprising: detecting a plurality of columns in an unoptimized database that co-appear in at least one of where and select queries to the database by clustering across all columns according to co-appearance using an approximation of K-minimum cut; compacting the plurality of columns into a single hyper-column using a processor to form an optimized database, wherein each entry in the hyper-column comprises data from a corresponding entry in each of the plurality of columns; generating an index for the hyper-column, comprising generating an R-tree index if the hyper-column consists of numerical data and generating a B-tree index if the hyper-column consists of textual data; compressing entries in the hyper-column if the entries in the hyper-column consist of textual data; and generating an interface for the optimized database that accepts queries according to a schema for the unoptimized database and translates said queries into queries according to a schema for the optimized database, wherein said interface comprises a virtual view of the database according to the schema for the unoptimized database.
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