Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.

Abstract: A variety of query optimization techniques are described herein. A first query optimization technique, referred to herein as non-empty transformation, may be applied to queries that specify one or more measures, a dimensional context within which the measure(s) are to be evaluated, and a filter condition specifying that rows with only empty measure values be excluded from a result set. The non-empty transformation technique enables such queries to be rewritten into another format that can be executed more efficiently than the original queries. A second query optimization technique described herein involves restructuring an operator tree representation of a query so as to avoid unnecessary duplicated evaluation of extension columns. A third query optimization technique described herein automatically selects a minimum number of join columns having the lowest cardinality for implementing a join between two tables.

Abstract: A variety of query optimization techniques are described herein. A first query optimization technique, referred to herein as non-empty transformation, may be applied to queries that specify one or more measures, a dimensional context within which the measure(s) are to be evaluated, and a filter condition specifying that rows with only empty measure values be excluded from a result set. The non-empty transformation technique enables such queries to be rewritten into another format that can be executed more efficiently than the original queries. A second query optimization technique described herein involves restructuring an operator tree representation of a query so as to avoid unnecessary duplicated evaluation of extension columns. A third query optimization technique described herein automatically selects a minimum number of join columns having the lowest cardinality for implementing a join between two tables.

Abstract: Methods and systems are disclosed for receiving and processing data analysis expressions. A particular method includes receiving a data analysis expression at a pivot table of a spreadsheet. The data analysis expression is executed for a particular cell of the pivot table by determining a context associated with the particular cell, calculating a value of the data analysis expression based on the context, and outputting the calculated value at the particular cell.