| 摘要 |
Mechanisms are provided for performing efficient compression and deduplication of data segments. Compression algorithms are learning algorithms that perform better when data segments are large. Deduplication algorithms, however, perform better when data segments are small, as more duplicate small segments are likely to exist. As an optimizer is processing and storing data segments, the optimizer applies the same compression context to compress multiple individual deduplicated data segments as though they are one segment. By compressing deduplicated data segments together within the same context, data reduction can be improved for both deduplication and compression. Mechanisms are applied to compensate for possible performance degradation. |
