Renu A Varshneya

US Patent:

20100114870, May 6, 2010

Filed:

Oct 30, 2008

Appl. No.:

12/261058

Inventors:

Awny K. Al-Omari - Cedar Park TX, US
Renu Varshneya - Cupertino CA, US
Robert l. Wall - Austin TX, US

International Classification:

G06F 17/30

US Classification:

707718, 707E17136, 707E1714

Abstract:

One embodiment is a method that determines skew to predict costs for query plans for a database query. The method selects a query plan that accounts for the skew to evenly distribute processing load among multiple processors and then executes the query with the selected query plan.

US Patent:

20110055198, Mar 3, 2011

Filed:

Aug 31, 2009

Appl. No.:

12/550834

Inventors:

Roger Mitchell - Austin TX, US
Renu Varshneya - Cupertino CA, US
Awny K. Al-Omari - Cedar Park TX, US

International Classification:

G06F 17/30
G06F 7/00

US Classification:

707713, 707E17017, 707E17045, 707E17136

Abstract:

There is provided a computer-implemented method of optimizing a query. An exemplary method comprises receiving a first request from an optimizer that specifies a table, a first predicate and a first sample size, wherein the optimizer is optimizing a relational query language statement that specifies the table and the first predicate. The exemplary method also comprises generating a sample table, comprising a first subset of rows from the table, based on the request. The exemplary method also comprises selecting a second subset of rows from the sample table based on the predicate. The exemplary method additionally comprises sending a count of rows in the second subset to the optimizer.

US Patent:

20150106397, Apr 16, 2015

Filed:

Dec 19, 2014

Appl. No.:

14/577611

Inventors:

- Houston T, US
Renu Varshneya - Cupertino CA, US
Awny K. Al-Omari - Cedar Park TX, US

International Classification:

G06F 17/30

US Classification:

707768

Abstract:

There is provided a computer-implemented method of optimizing a query. An exemplary method retrieves a subset of rows from a sample table based on a query for a table associated with the sample table. The query specifies the table. The sample table is generated in a previous optimization of the query. The sample table includes a scrambled, random selection of rows from the table. A cardinality of the table is determined based on the subset. A query plan is generated based on the query and the cardinality.