Abstract: Embodiments of the present invention disclose generating a data profiling jobs for source data in a data processing system, the source data being described by at least one source functional data model. A target functional data model is provided, for describing target data that can be generated from the source data. One or more source functional data models are identified that correspond to the target functional data model. At least one functional source-to-target model mapping is associated to at least one source-target pair based on the target functional data model and identified source functional data models. A physical source-to-target model mapping for at least one source-target pair based on the logical source-to-target model mapping is calculated. For all physical source attributes, the needed data profiling jobs are generated based on the target attribute for analyzing the physical source attributes.

Abstract: A method, computer program product, and computer system for optimizing query processing is provided. An asynchronously updated index is provided for a main dataset. A time-sequences log of data modifications to the main dataset is provided. A query of the main dataset is received. The main dataset is joined with the time-sequenced log data resulting in a first intermediate result. The query is processed by keeping one or more entries satisfying the query by emulating a function of the asynchronously updated index resulting in a second intermediate result. Updated, deleted dataset entries are deleted from the asynchronously updated index. The query is processed resulting in a third intermediate result. A union of the second intermediate result and third intermediate result is built defining a final result.

Abstract: A method, computer program product, and computer system for optimizing query processing is provided. An asynchronously updated index is provided for a main dataset. A time-sequences log of data modifications to the main dataset is provided. A query of the main dataset is received. The main dataset is joined with the time-sequenced log data resulting in a first intermediate result. The query is processed by keeping one or more entries satisfying the query by emulating a function of the asynchronously updated index resulting in a second intermediate result. Updated, deleted dataset entries are deleted from the asynchronously updated index. The query is processed resulting in a third intermediate result. A union of the second intermediate result and third intermediate result is built defining a final result.

Abstract: A logging process in a data storage system having a set of storage tiers, each storage tier of the set of storage tiers having different performance characteristics, wherein the set of storage tiers is divided into a plurality of subsets of storage tiers using the performance characteristics, may include initiating the logging process for creating a separate log file for each of the plurality of subsets of storage tiers for maintaining a history of data changes in the subset of storage tiers, thereby creating a plurality of log files. In response to a change in data stored in at least one storage tier of a subset of storage tiers of the plurality of subsets of storage tiers, one or more log records including information about the change may be generated and written into respective log files.