Vinod P. Chirayath - Olathe KS, US Zackery M. Englang - Overland Park KS, US Venkatesh S. Gopal - Overland Park KS, US Salvador Ledezma - Mountain View CA, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/30
US Classification:
707758, 707E17075, 707E17044
Abstract:
Some embodiments include a method for searching a hierarchical database structure of a database management system. In some embodiments, the method comprises detecting text input in a database search field, wherein the text input defines a search for data in the hierarchical database structure, wherein the hierarchical database structure includes items, and wherein the items include one or more of actions to be performed on data in the hierarchical database structure, indexes for looking up data in the hierarchical database structure, and database schemas defining databases in the hierarchical database structure. The method can also comprise selecting items in the hierarchical database structure based on the text input; presenting selectable options, wherein the selectable options are associated with the items in the hierarchical database structure; detecting selection of one of the selectable options, and presenting data associated with the one of the items.
- Armonk NY, US Venkatesh S. Gopal - Overland Park KS, US Venkannababu Tammisetti - Shrewsbury MA, US Paul-John A. To - Olathe KS, US
International Classification:
G06F 17/30
Abstract:
Provided are techniques for estimating most frequent values. A sample of values made up of rows is received from each of multiple nodes. The sample of values from each of the multiple nodes are aggregated to generate a sample table storing the rows. A descending list of most frequent values and associated frequencies is obtained using the sample table. Most frequent values are pruned from the descending list whose associated frequencies are below a minimum absolute frequency. The remaining most frequent values are extrapolated to reflect a data set.
- Armonk NY, US Venkatesh S. Gopal - Overland Park KS, US
International Classification:
G06F 17/30
Abstract:
According to one embodiment of the present invention, a system for processing queries analyzes statistical information of input data records in relation to a first operation for a query. The system applies the first operation to a plurality of groups of input data records to produce corresponding groups of output data records, and coalesces the sets of output data records to form larger sets of data records for input to a subsequent second operation for the query based on the analysis. Embodiments of the present invention further include a method and computer program product for processing queries in substantially the same manners described above.
- Armonk NY, US Venkatesh S. Gopal - Overland Park KS, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/30
Abstract:
According to one embodiment of the present invention, a system for processing queries analyzes statistical information of input data records in relation to a first operation for a query. The system applies the first operation to a plurality of groups of input data records to produce corresponding groups of output data records, and coalesces the sets of output data records to form larger sets of data records for input to a subsequent second operation for the query based on the analysis. Embodiments of the present invention further include a method and computer program product for processing queries in substantially the same manners described above.
- Armonk NY, US Venkatesh S. Gopal - Overland Park KS, US Venkannababu Tammisetti - Shrewsbury MA, US Paul-John A. To - Olathe KS, US
International Classification:
G06F 17/30
US Classification:
707769, 707803
Abstract:
Provided are techniques for estimating most frequent values. A sample of values made up of rows is received from each of multiple nodes. The sample of values from each of the multiple nodes are aggregated to generate a sample table storing the rows. A descending list of most frequent values and associated frequencies is obtained using the sample table. Most frequent values are pruned from the descending list whose associated frequencies are below a minimum absolute frequency. The remaining most frequent values are extrapolated to reflect a data set.