Abstract: Systems and methods are disclosed for partitioning data into n partitions in a database used for information retrieval. According to certain embodiments implemented with at least one processor, a perceived load is determined for each of a plurality of substrings, each of the substrings corresponding to one or more entries in the database. The plurality of substrings are ordered from highest to lowest perceived load. Data associated with each of the first n substrings is assigned to a separate partition, wherein n is greater than one. Moreover, data associated with each of the remaining substrings is assigned to the n partitions based on a score. The score is computed by calculating, for each partition, a load variance and an entropy weight for the candidate substring. The load variance and the entropy weight are combined, and the candidate substring is assigned to the partition that has the lowest combined score.

Abstract: Systems and methods are disclosed for partitioning data into n partitions in a database used for information retrieval. According to certain embodiments implemented with at least one processor, a perceived load is determined for each of a plurality of substrings, each of the substrings corresponding to one or more entries in the database. The plurality of substrings are ordered from highest to lowest perceived load. Data associated with each of the first n substrings is assigned to a separate partition, wherein n is greater than one. Moreover, data associated with each of the remaining substrings is assigned to the n partitions based on a score. The score is computed by calculating, for each partition, a load variance and an entropy weight for the candidate substring. The load variance and the entropy weight are combined, and the candidate substring is assigned to the partition that has the lowest combined score.