Deduplicating data for a data storage system using similarity determinations

• US 9,933,970 B2
• Filed: 10/30/2015
• Issued: 04/03/2018
• Est. Priority Date: 10/30/2015
• Status: Active Grant

• Current Assignee: NetApp, Inc.
• Original Assignee: NetApp, Inc.
• Inventors: Kathpal, Atish, Yasa, Giridhar
• Primary Examiner(s): THAI, TUAN V
• Application Number:
  US14/928,848
• Publication Number:
  US 20170123711A1
• Time in Patent Office: 886 Days
• Field of Search: 711100, 711111, 711154
• CPC Class Codes: G06F 3/0608 Saving storage space on storage systems
• CPC Class Codes: G06F 3/0641 De-duplication techniques
• CPC Class Codes: G06F 3/0686 Libraries, e.g. tape libraries, jukebox

Abstract

A method and system for deduplicating data for a data storage system using similarity determinations are described. A tape library is arranged in a hierarchy of tape groups and tape plexes. Tape groups are an admin visible entity and are comprised of multiple tape plexes (at least equal to the number of replicas in a tape group). Tape plexes in turn comprise multiple tape cartridges. Data files and objects received within a time period are initially staged in a disk cache where they are logically segregated into cliques based on their expected deduplication ratios. These cliques are then evaluated for the amount of duplication they have with data existing in tape plexes. Based on the number of replicas being written, the top few tape plexes are selected from within the tape group. The cliques are deduplicated with data on the selected tape plexes, compressed, and written to tape.

Claims

1. A computing device comprising:

a memory resource to store instructions;

one or more processors using the instructions stored in the memory resource to;

receive data to be stored at a data storage system;

determine similarities between the received data and data stored on each of a plurality of storage elements at the data storage system;

select a first storage element and a second storage element of the plurality of storage elements based on the first storage element having a highest similarity and the second storage element having a next highest similarity;

write the received data to the first storage element, wherein the received data is deduplicated with data stored on the first storage element; and

write a replica of the received data to the second storage element, wherein the replica is deduplicated with data stored on the second storage element.

2. The computing device of claim 1, comprising further instructions used by the one or more processors to:

identify patterns of bytes within the received data;

separate the received data into one or more subsets based on the identified patterns of bytes; and

for each of the one or more subsets;

determine a subset similarity between the subset and data stored on each of the plurality of storage elements at the data storage system;

select one or more of the plurality of storage elements based on the subset similarity; and

write the subset to the one or more selected storage elements, including, for each of the selected storage elements, deduplicating the subset with the data stored on that storage element.

3. The computing device of claim 2, comprising further instructions used by the one or more processors to:

determine the subset similarity by (i) applying a hashing algorithm to the subset to generate a subset fingerprint, and (ii) comparing the subset fingerprint to stored fingerprints corresponding to the data stored on each of the plurality of storage elements; and

store the generated subset fingerprints in association with the selected storage elements.

4. The computing device of claim 1, wherein the data stored on each of the plurality of storage elements are divided into windows.

5. The computing device of claim 4, wherein the data is divided into the windows based on how recently the data was stored.

6. The computing device of claim 4, wherein similarity is determined between the received data and data from a predetermined number of recent windows on each of the plurality of storage elements.

7. The computing device of claim 1, wherein each of the plurality of storage elements comprises multiple linear storage devices.

8. A method of writing data in a data storage system, the method being implemented by one or more processors and comprising:

receiving data to be stored at the data storage system;

determining similarities between the received data and data stored on each of a plurality of storage elements at the data storage system;

selecting a first storage element and a second storage element of the plurality of storage elements based on the first storage element having a highest similarity and the second storage element having a next highest similarity;

writing the received data to the first storage element, wherein the received data is deduplicated with data stored on the first storage element; and

writing a replica of the received data to the second storage element, wherein the replica is deduplicated with data stored on the second storage element.

9. The method of claim 8, further comprising:

identifying patterns of bytes within the received data;

separating the received data into one or more subsets based on the identified patterns of bytes; and

for each of the one or more subsets;

determining a subset similarity between the subset and data stored on each of the plurality of storage elements at the data storage system;

selecting one or more of the plurality of storage elements based on the subset similarity; and

writing the subset to the one or more selected storage elements, including, for each of the selected storage elements, deduplicating the subset with the data stored on that storage element.

10. The method of claim 9, further comprising:

determining the subset similarity by (i) applying a hashing algorithm to the subset to generate a subset fingerprint, and (ii) comparing the subset fingerprint to stored fingerprints corresponding to the data stored on each of the plurality of storage elements; and

storing the generated subset fingerprints in association with the selected storage elements.

11. The method of claim 8, wherein the data stored on each of the plurality of storage elements are divided into windows.

12. The method of claim 11, wherein the data is divided into the windows based on how recently the data was stored.

13. The method of claim 11, wherein similarity is determined between the received data and data from a predetermined number of recent windows on each of the plurality of storage elements.

14. The method of claim 8, wherein each of the plurality of storage elements comprises multiple linear storage devices.

15. A non-transitory computer-readable medium that stores instructions, executable by one or more processors, to cause the one or more processors to perform operations that comprise:

receiving data to be stored at a data storage system;

determining similarities between the received data and data stored on each of a plurality of storage elements at the data storage system;

selecting a first storage element and a second storage element of the plurality of storage elements based on the first storage element having a highest similarity and the second storage element having a next highest similarity;

writing the received data to the first storage element, wherein the received data is deduplicated with data stored on the first storage element; and

writing a replica of the received data to the second storage element, wherein the replica is deduplicated with data stored on the second storage element.

16. The non-transitory computer-readable medium of claim 15, storing further instructions used by the one or more processors to perform operations that comprise:

identifying patterns of bytes within the received data;

separating the received data into one or more subsets based on the identified patterns of bytes; and

for each of the one or more subsets;

determining a subset similarity between the subset and data stored on each of the plurality of storage elements at the data storage system;

selecting one or more of the plurality of storage elements based on the subset similarity; and

writing the subset to the one or more selected storage elements, including, for each of the selected storage elements, deduplicating the subset with the data stored on that storage element.

17. The non-transitory computer-readable medium of claim 16, storing further instructions used by the one or more processors to perform operations that comprise:

determining the subset similarity by (i) applying a hashing algorithm to the subset to generate a subset fingerprint, and (ii) comparing the subset fingerprint to stored fingerprints corresponding to the data stored on each of the plurality of storage elements; and

storing the generated subset fingerprints in association with the selected storage elements.

18. The non-transitory computer-readable medium of claim 15, wherein the data stored on each of the plurality of storage elements are divided into windows.

19. The non-transitory computer-readable medium of claim 18, wherein the data is divided into the windows based on how recently the data was stored.

20. The non-transitory computer-readable medium of claim 18, wherein similarity is only determined between the received data and data from a predetermined number of recent windows on each of the plurality of storage elements.