Abstract: The present disclosure provides systems and methods for executing a query in a data analytics storage engine. An example method comprising: receiving a query to locate target data in the data analytics storage engine that comprises: rows of data divided into one or more splits of data having columns of data that correspond to the rows of data, and bitmap data embedded in the one or more splits, wherein the bitmap data is associated with the columns of data; and locating the target data using the bitmap data in the one or more splits.

Abstract: According to one embodiment of the present invention, a computer-implemented method of performing analytics on a large quantity of data accommodated by an external mass storage device is provided. The analytics may be divided into a set of modules, wherein each module is selectively executed and comprises a script for a parallel processing engine to perform a corresponding atomic operation on the analytics. A user selection is received of one or more modules to perform desired analytics on the large quantity of data from the external mass storage device, and the selected modules execute scripts for the parallel processing engine to perform the corresponding atomic operations of the desired analytics.

Abstract: According to one embodiment of the present invention, a computer-implemented method of performing analytics on a large quantity of data accommodated by an external mass storage device is provided. The analytics may be divided into a set of modules, wherein each module is selectively executed and comprises a script for a parallel processing engine to perform a corresponding atomic operation on the analytics. A user selection is received of one or more modules to perform desired analytics on the large quantity of data from the external mass storage device, and the selected modules execute scripts for the parallel processing engine to perform the corresponding atomic operations of the desired analytics.

Abstract: According to one embodiment of the present invention, a computer-implemented method of performing analytics on a large quantity of data accommodated by an external mass storage device is provided. The analytics may be divided into a set of modules, wherein each module is selectively executed and comprises a script for a parallel processing engine to perform a corresponding atomic operation on the analytics. A user selection is received of one or more modules to perform desired analytics on the large quantity of data from the external mass storage device, and the selected modules execute scripts for the parallel processing engine to perform the corresponding atomic operations of the desired analytics.

Abstract: According to one embodiment of the present invention, a computer-implemented method of performing analytics on a large quantity of data accommodated by an external mass storage device is provided. The analytics may be divided into a set of modules, wherein each module is selectively executed and comprises a script for a parallel processing engine to perform a corresponding atomic operation on the analytics. A user selection is received of one or more modules to perform desired analytics on the large quantity of data from the external mass storage device, and the selected modules execute scripts for the parallel processing engine to perform the corresponding atomic operations of the desired analytics.

Abstract: A computer-program product for improving LBAC performance in a database may include assigning a security label to a user of a database. The security label may be one of multiple security labels associated with a security policy of the database. Each of the multiple security labels may then be compared to the user's security label to provide multiple comparison results. These comparison results may be stored in a persistent label comparison results table for later retrieval. Upon receiving a command to read or write to an object in the database, the comparison result associated with the object may be retrieved from the persistent label comparison results table. Access to the object may then be granted or denied based on the comparison result.