Netapp, Inc.

Satbir Singh

Alok Sharma

Praveen Killamsetti

Sudhanshu Gupta

Subramaniam Periyagaram

Bipul Raj

Multiple key-value stores may be employed to smooth out random updates (based on the extent ID) to the EMAP database. The updates to the EMAP database occur in a two-stage manner: (i) using an append-only log store for the first stage and (ii) using an on-disk hash store for the second stage. The append-only log store is used to convert the random updates to sequential write operations on the EMAP database. Once full, the contents of the log store are sorted and moved to the on-disk hash store, which holds the updates for a transient period of time to enable batching of the updates. Once sufficient batching of the extent map entries are accumulated, those entries are sorted and moved to the EMAP database. Thereafter, the EMAP database can be scanned to find extent map entries having identical checksum bits to perform data deduplication.

Two-stage front end for extent map database

An extent map (EMAP) database may include one or more extent map entries configured to map extent IDs to PVBNs. Each extent ID may be apportioned into a most significant bit (MSB) portion, i.e., checksum bits, and a least significant bit (LSB) portion, i.e., duplicate bits. A hash may be applied to the data of the extent to calculate the checksum bits, which illustratively represent a fingerprint of the data. The duplicate bits may be configured to denote any reoccurrence of the checksum bits in the EMAP database, i.e., whether there is an existing extent with potentially identical data in a volume of the aggregate. Each extent map entry may be inserted on a node having one or more key/value pairs, wherein the key is the extent ID and the value is the PVBN. The EMAP database may be scanned and utilized to perform data deduplication.

Data deduplication utilizing extent ID database

A storage server is coupled to a storage device that stores data blocks, and generates a fingerprint for each data block stored on the storage device. The storage server creates a master datastore and a plurality of datastore segments. The master datastore comprises an entry for each data block that is written to the storage device and a datastore segment comprises an entry for a new data block or a modified data block that is subsequently written to the storage device. The storage server merges the entries in the datastore segments with the entries in the master datastore in memory to free duplicate data blocks in the storage device. The storage server overwrites the master datastore with the entries in the plurality of datastore segments and the entries in the master datastore to create an updated master datastore in response to detecting that the number of datastore segments meets a threshold.

Segmented fingerprint datastore and scaling a fingerprint datastore in de-duplication environments

A storage server is coupled to a storage device that stores blocks of data, and generates a fingerprint for each data block stored on the storage device. The storage server creates a fingerprints datastore that is divided into a primary datastore and a secondary datastore. The primary datastore comprises a single entry for each unique fingerprint and the secondary datastore comprises an entry having an identical fingerprint as an entry in the primary datastore. The storage server merges entries in a changelog with the entries in the primary datastore to identify duplicate data blocks in the storage device and frees the identified duplicate data blocks in the storage device. The storage server stores the entries that correspond to the freed data blocks to a third datastore and overwrites the primary datastore with the entries from the merged data that correspond to the unique fingerprints to create an updated primary datastore.

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Bengaluru, India

Satbir Singh