Real-time classification of data into data compression domains

A system for real-time classification of data into data compression domains in a computing environment, the system comprising:

• a processor device operable in the computing storage environment, wherein the processor device:
• decides, by a plurality of nodes, which of the data compression domains write operations should be forwarded to by reading randomly selected data of the write operations for computing a set of classifying heuristics thereby creating a fingerprint for each of the write operations,
• compresses together, by the plurality of nodes, in a compression stream those of the write operations having a similar fingerprint;
• wherein the processor device, for computing the set of classifying heuristics, uses a combination of all of the heuristics:
• entropy of the randomly selected data, a core character set and size of character that compose a majority of bytes in the randomly selected data, a full or partial histogram of the randomly selected data or the core character set, groups of dominant characters or groups of non-dominant characters of the randomly selected data, one of a mean, a variance, and an alternative moment of the full or partial histogram or the core character set, and an indication of a data structure of the data, and
• splits the write operations having different fingerprints into different compression streams.

A computer program product real-time classification of data into data compression domains by a processor device, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

• a first executable portion decides, by a plurality of nodes, which of the data compression domains write operations should be forwarded to by reading randomly selected data of the write operations for computing a set of classifying heuristics thereby creating a fingerprint for each of the write operations;
• a second executable portion that compresses together, by the plurality of nodes, in a compression stream those of the write operations having a similar fingerprint;
• wherein computing a set of classifying heuristics includes a combination of all of:
• an entropy of the randomly elected data, a core character set and size of character that compose a majority of bytes in the randomly selected data, a full or partial histogram of the randomly selected data or the core character set, groups of dominant characters or groups of non-dominant characters of the randomly selected data, one of a mean, a variance, and an alternative moment of the full or partial histogram or the core character set, and an indication of a data structure of the data;
• and
• a third executable portion that splits the write operations having different fingerprints into different compression streams.