Efficiently accessing an encoded data slice in a memory container utilizing a memory bin

1. A method for execution by one or more computing devices, the method comprises:

determining whether a substantially similar data object to a data object is stored in a dispersed storage network (DSN); and

when the substantially similar data object is not stored in the DSN:

dividing the data object into a plurality of data segments;

encoding the plurality of data segments to produce a plurality of encoded data segments, wherein an encoded data segment of the plurality of encoded data segments includes a first number of data blocks and a second number of parity blocks;

arranging the data blocks and the parity blocks of the plurality of encoded data segments into a matrix, wherein the data blocks and the parity blocks of an encoded data segment of the plurality of encoded data segments are placed in the matrix in a first orientation;

establishing a set of encoded data slices from the matrix based on a second orientation of the matrix; and

outputting the set of encoded data slices to storage units of the DSN for storage therein.

2. The method of claim 1 , wherein the determining whether the substantially similar data object is stored in the DSN comprises one or more of:

comparing a portion of the data object to the substantially similar data object:

comparing a hash of the portion of the data object to a hash of the portion of the substantially similar data object; and

determining data segment boundaries and comparing one or more data segments of the data objects to one or more data segments of the substantially similar data object.

3. The method of claim 1 further comprises:

when the substantially similar data object is stored in the DSN:

dividing the data object into the plurality of data segments based on a segmenting scheme used to segment the substantially similar data object;

identifying different data segments of the data object in comparison to data segments of the substantially similar data object;

encoding the different data segments to produce a set of encoded data segments;

arranging the data blocks and the parity blocks of the set of encoded data segments into the matrix;

establishing a new set of encoded data slices from the matrix; and

outputting the new set of encoded data slices to storage units of the DSN for storage therein.

4. The method of claim 1 , wherein the arranging the data blocks and the parity blocks of the plurality of encoded data segments into the matrix comprises:

placing the data blocks and parity blocks of one of the plurality of encoded data segments in a column of the matrix;

placing the data blocks and parity blocks of a second one of the plurality of encoded data segments in a second column of the matrix;

placing the data blocks and parity blocks of a third one of the plurality of encoded data segments in a third column of the matrix; and

placing the data blocks and parity blocks of an x th one of the plurality of encoded data segments in an x th column of the matrix, wherein x corresponds to the number of data segments in the plurality of data segments.

5. The method of claim 4 , wherein the establishing a set of encoded data slices from the matrix comprises:

establishing a first encoded data slice of the set of encoded data slices to include data blocks of a first row of the matrix;

establishing an m th encoded data slice of the set of encoded data slices to include data blocks of a m th row of the matrix, wherein m corresponds to the first number;

establishing an m th +1 encoded data slice of the set of encoded data slices to include parity blocks of a m th +1 row of the matrix; and

establishing an n th encoded data slice of the set of encoded data slices to include parity blocks of a n th row of the matrix, wherein n corresponds to the sum of the first number and the second number.

6. A computing device comprises:

an interface;

memory; and

a processing module operably coupled to the interface and to the memory, wherein the processing module is operable to:

determine whether a substantially similar data object to a data object is stored in a dispersed storage network (DSN); and

when the substantially similar data object is not stored in the DSN:

divide the data object into a plurality of data segments;

encode the plurality of data segments to produce a plurality of encoded data segments, wherein an encoded data segment of the plurality of encoded data segments includes a first number of data blocks and a second number of parity blocks;

arrange the data blocks and the parity blocks of the plurality of encoded data segments into a matrix, wherein the data blocks and the parity blocks of an encoded data segment of the plurality of encoded data segments are placed in the matrix in a first orientation;

establish a set of encoded data slices from the matrix based on a second orientation of the matrix; and

output, via the interface, the set of encoded data slices to storage units of the DSN for storage therein.

7. The computing device of claim 6 , wherein the processing module is further operable to determine whether the substantially similar data object is stored in the DSN by one or more of:

comparing a portion of the data object to the substantially similar data object:

comparing a hash of the portion of the data object to a hash of the portion of the substantially similar data object; and

determining data segment boundaries and comparing one or more data segments of the data objects to one or more data segments of the substantially similar data object.

8. The computing device of claim 6 , wherein the processing module is further operable to:

when the substantially similar data object is stored in the DSN:

divide the data object into the plurality of data segments based on a segmenting scheme used to segment the substantially similar data object;

identify different data segments of the data object in comparison to data segments of the substantially similar data object;

encode the different data segments to produce a set of encoded data segments;

arranging the data blocks and the parity blocks of the set of encoded data segments into the matrix;

establish a new set of encoded data slices from the matrix; and

output, via the interface, the new set of encoded data slices to storage units of the DSN for storage therein.

9. The computing device of claim 6 , wherein the processing module is further operable to arrange the data blocks and the parity blocks of the plurality of encoded data segments into the matrix by:

placing the data blocks and parity blocks of one of the plurality of encoded data segments in a column of the matrix;

placing the data blocks and parity blocks of a second one of the plurality of encoded data segments in a second column of the matrix;

placing the data blocks and parity blocks of a third one of the plurality of encoded data segments in a third column of the matrix; and

placing the data blocks and parity blocks of an x th one of the plurality of encoded data segments in an x th column of the matrix, wherein x corresponds to the number of data segments in the plurality of data segments.

10. The computing device of claim 9 , wherein the processing module is further operable to establish the set of encoded data slices from the matrix by:

establishing a first encoded data slice of the set of encoded data slices to include data blocks of a first row of the matrix;

establishing an m th encoded data slice of the set of encoded data slices to include data blocks of a m th row of the matrix, wherein m corresponds to the first number;

establishing an m th +1 encoded data slice of the set of encoded data slices to include parity blocks of a m th +1 row of the matrix; and

establishing an n th encoded data slice of the set of encoded data slices to include parity blocks of a n th row of the matrix, wherein n corresponds to the sum of the first number and the second number.

11. A non-transitory computer readable memory device comprises:

a first memory section that stores operational instructions that, when executed by a computing device, causes the computing device to:

determine whether a substantially similar data object to a data object is stored in a dispersed storage network (DSN); and

a second memory section that stores operational instructions that, when executed by the computing device, causes the computing device to:

when the substantially similar data object is not stored in the DSN:

divide the data object into a plurality of data segments;

encode the plurality of data segments to produce a plurality of encoded data segments, wherein an encoded data segment of the plurality of encoded data segments includes a first number of data blocks and a second number of parity blocks;

arrange the data blocks and the parity blocks of the plurality of encoded data segments into a matrix, wherein the data blocks and the parity blocks of an encoded data segment of the plurality of encoded data segments are placed in the matrix in a first orientation;

establish a set of encoded data slices from the matrix based on a second orientation of the matrix; and

output the set of encoded data slices to storage units of the DSN for storage therein.

12. The non-transitory computer readable memory device of claim 11 , wherein the first memory section further stores operational instructions that, when executed by the computing device, causes the computing device to determine whether the substantially similar data object is stored in the DSN by one or more of:

comparing a portion of the data object to the substantially similar data object:

comparing a hash of the portion of the data object to a hash of the portion of the substantially similar data object; and

determining data segment boundaries and comparing one or more data segments of the data objects to one or more data segments of the substantially similar data object.

13. The non-transitory computer readable memory device of claim 11 further comprises:

a third memory section that stores operational instructions that, when executed by the computing device, causes the computing device to:

when the substantially similar data object is stored in the DSN:

divide the data object into the plurality of data segments based on a segmenting scheme used to segment the substantially similar data object;

identify different data segments of the data object in comparison to data segments of the substantially similar data object;

encode the different data segments to produce a set of encoded data segments;

arranging the data blocks and the parity blocks of the set of encoded data segments into the matrix;

establish a new set of encoded data slices from the matrix; and

output, via an interface, the new set of encoded data slices to storage units of the DSN for storage therein.

14. The non-transitory computer readable memory device of claim 11 , wherein the second memory section further stores operational instructions that, when executed by the computing device, causes the computing device to arrange the data blocks and the parity blocks of the plurality of encoded data segments into the matrix by:

placing the data blocks and parity blocks of one of the plurality of encoded data segments in a column of the matrix;

placing the data blocks and parity blocks of a second one of the plurality of encoded data segments in a second column of the matrix;

placing the data blocks and parity blocks of a third one of the plurality of encoded data segments in a third column of the matrix; and

placing the data blocks and parity blocks of an x th one of the plurality of encoded data segments in an x th column of the matrix, wherein x corresponds to the number of data segments in the plurality of data segments.

15. The non-transitory computer readable memory device of claim 14 , wherein the second memory section further stores operational instructions that, when executed by the computing device, causes the computing device to establish the set of encoded data slices from the matrix by:

establishing a first encoded data slice of the set of encoded data slices to include data blocks of a first row of the matrix;

establishing an m th encoded data slice of the set of encoded data slices to include data blocks of a m th row of the matrix, wherein m corresponds to the first number;

establishing an m th +1 encoded data slice of the set of encoded data slices to include parity blocks of a m th +1 row of the matrix; and

establishing an n th encoded data slice of the set of encoded data slices to include parity blocks of a n th row of the matrix, wherein n corresponds to the sum of the first number and the second number.