Abstract: For efficient serialization of journal data using a processor device, serialization is combined with journaling of data into one data storage system on a write operation with subsequent consolidation for serialization of the journal data.

Abstract: B-Tree data is serialized to existing data for all types of workloads. Each of an identified data range is encoded with frequency encoding, wherein a first value in a frequency encoded identified data range is a first value in original data and all subsequent values in the frequency encoded identified data range are equal to a difference between a corresponding value in an input file and a previous value in the input file.

Abstract: B-Tree data is serialized to existing data for all types of workloads by converting a B-Tree data structure into a format capable of being stored and resurrected while containing all data stored in the B-Tree data structure and information relating to the B-Tree data structure. The serialized B-Tree data is divided into a plurality of sections. The serialized B-Tree data is stored into a plurality of buffers, where storing the B-Tree information section in a first binary buffer, the B-Tree key section in a second binary buffer, and the B-Tree data section in a third binary buffer. In the B-Tree data section, B-Tree data elements stored in the B-Tree data structure are saved, where a size of the B-Tree data section is equal to a total number of the B-Tree data elements in the B-Tree data structure multiplied by a size of each of the B-Tree data elements.

Abstract: Various embodiments for identifying data in a data deduplication system, by a processor device, are provided. In one embodiment, a method comprises efficiently identifying duplicate data in the data deduplication system by identifying fingerprint matches using a direct inter-region fingerprint lookup to search for the fingerprint matches in at least one of a plurality of metadata regions, the direct inter-region fingerprint lookup supplementing a central fingerprint index.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include receiving a request to create a storage entity on a storage system, the storage entity including data and metadata, the metadata used to manage the storage entity. Upon receiving the request, multiple metadata attributes are identified for the metadata, and for each given identified metadata attribute, a respective metadata region is created on the storage system, and a subset of the metadata having the given metadata attribute is stored to the respective metadata region. Finally, a data region is created on the storage system, and the data is stored to the data region.

Abstract: Various embodiments for identifying data in a data deduplication system, by a processor device, are provided. In one embodiment, a method comprises efficiently identifying duplicate data in the data deduplication system by identifying fingerprint matches using a direct inter-region fingerprint lookup to search for the fingerprint matches in at least one of a plurality of metadata regions, the direct inter-region fingerprint lookup supplementing a central fingerprint index.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include receiving a request to create a storage entity on a storage system, the storage entity including data and metadata, the metadata used to manage the storage entity. Upon receiving the request, multiple metadata attributes are identified for the metadata, and for each given identified metadata attribute, a respective metadata region is created on the storage system, and a subset of the metadata having the given metadata attribute is stored to the respective metadata region. Finally, a data region is created on the storage system, and the data is stored to the data region.

Abstract: B-Tree data is serialized to existing data for all types of workloads by converting a B-Tree data structure into a format capable of being stored and resurrected while containing all data stored in the B-Tree data structure and information relating to the B-Tree data structure. The serialized B-Tree data is divided into a plurality of sections. The serialized B-Tree data is stored into a plurality of buffers, where storing the B-Tree information section in a first binary buffer, the B-Tree key section in a second binary buffer, and the B-Tree data section in a third binary buffer. In the B-Tree data section, B-Tree data elements stored in the B-Tree data structure are saved, where a size of the B-Tree data section is equal to a total number of the B-Tree data elements in the B-Tree data structure multiplied by a size of each of the B-Tree data elements.

Abstract: B-Tree data is serialized to existing data for all types of workloads. Each of an identified data range is encoded with frequency encoding, wherein a first value in a frequency encoded identified data range is a first value in original data and all subsequent values in the frequency encoded identified data range are equal to a difference between a corresponding value in an input file and a previous value in the input file.

Abstract: B-Tree data is serialized to existing data for all types of workloads. The serialized B-Tree data, that has been split, sorted and classified into identified data ranges, is then compressed.

Abstract: B-Tree data is serialized to existing data for all types of workloads by converting a B-Tree data structure into a format capable of being stored and resurrected while containing all data stored in the B-Tree data structure and information relating to the B-Tree data structure.

Abstract: For efficient serialization of journal data using a processor device, serialization is combined with journaling of data into one data storage system on a write operation with subsequent consolidation for serialization of the journal data.

Abstract: B-Tree data is serialized to existing data for all types of workloads by converting a B-Tree data structure into a format capable of being stored and resurrected while containing all data stored in the B-Tree data structure and information relating to the B-Tree data structure.

Abstract: B-Tree data is serialized to existing data for all types of workloads. The serialized B-Tree data, that has been split, sorted and classified into identified data ranges, is then compressed.