Abstract: An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: A computer-implemented data processing system and method writes a first plurality of copies of a data set at a first plurality of hosts and reads a second plurality of copies of the data set at a second plurality of hosts. The first and second pluralities of copies may be overlapping and the first and second pluralities of hosts may be overlapping. A hashing function may be used to select the first and second pluralities of hosts. Version histories for each of the first copies of the data set may also be written at the first plurality of hosts and read at the second plurality of hosts. The version histories for the second copies of the data set may be compared and causal between the second copies of the data set may be evaluated based on the version histories for the second copies of the data set.

Abstract: A computer-implemented data processing system and method includes storing a data set at a plurality of data centers. The data centers and hosts within the data centers may be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: A computer-implemented data processing system and method writes a first plurality of copies of a data set at a first plurality of hosts and reads a second plurality of copies of the data set at a second plurality of hosts. The first and second pluralities of copies may be overlapping and the first and second pluralities of hosts may be overlapping. A hashing function may be used to select the first and second pluralities of hosts. Version histories for each of the first copies of the data set may also be written at the first plurality of hosts and read at the second plurality of hosts. The version histories for the second copies of the data set may be compared and causal between the second copies of the data set may be evaluated based on the version histories for the second copies of the data set.

Abstract: A computer-implemented data processing system and method writes a first plurality of copies of a data set at a first plurality of hosts and reads a second plurality of copies of the data set at a second plurality of hosts. The first and second pluralities of copies may be overlapping and the first and second pluralities of hosts may be overlapping. A hashing function may be used to select the first and second pluralities of hosts. Version histories for each of the first copies of the data set may also be written at the first plurality of hosts and read at the second plurality of hosts. The version histories for the second copies of the data set may be compared and causal between the second copies of the data set may be evaluated based on the version histories for the second copies of the data set.

Abstract: An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: A computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs, version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: Management of a data cache having a compressed portion and an uncompressed portion by adaptively and dynamically allocating the relative amount space each portion receives. The relative sizes are defined based on one or more cost metrics and benefit metrics. The metrics are selected based on the performance of an application utilizing the cache. An optimized benefit relative to the cost is defined. Application operations on the cache are sampled and the relative cost and benefit is determined for different ratios of uncompressed to compressed cache sizes. The size of the uncompressed portion relative to the compressed portion is then re-adjusted based on an optimal cost-to-benefit ratio for the application.

Abstract: An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

Abstract: A computer-implemented data processing system and method writes a first plurality of copies of a data set at a first plurality of hosts and reads a second plurality of copies of the data set at a second plurality of hosts. The first and second pluralities of copies may be overlapping and the first and second pluralities of hosts may be overlapping. A hashing function may be used to select the first and second pluralities of hosts. Version histories for each of the first copies of the data set may also be written at the first plurality of hosts and read at the second plurality of hosts. The version histories for the second copies of the data set may be compared and causal between the second copies of the data set may be evaluated based on the version histories for the second copies of the data set.

Abstract: A computer-implemented data processing system and method writes a first plurality of copies of a data set at a first plurality of hosts and reads a second plurality of copies of the data set at a second plurality of hosts. The first and second pluralities of copies may be overlapping and the first and second pluralities of hosts may be overlapping. A hashing function may be used to select the first and second pluralities of hosts. Version histories for each of the first copies of the data set may also written at the first plurality of hosts and read at the second plurality of hosts. The version histories for the second copies of the data set may be compared and causal between the second copies of the data set may be evaluated based on the version histories for the second copies of the data set.

Abstract: A computer-implemented data processing system and method writes a first plurality of copies of a data set at a first plurality of hosts and reads a second plurality of copies of the data set at a second plurality of hosts. The first and second pluralities of copies may be overlapping and the first and second pluralities of hosts may be overlapping. A hashing function may be used to select the first and second pluralities of hosts. Version histories for each of the first copies of the data set may also written at the first plurality of hosts and read at the second plurality of hosts. The version histories for the second copies of the data set may be compared and causal between the second copies of the data set may be evaluated based on the version histories for the second copies of the data set.

Abstract: An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.