Vmware, Inc.

Vmare, Inc.

Vamsi Gunturu

Wenguang Wang

Junlong Gao

Eric Shannon Knauft

Petr Vandrovec

Maxime Austruy

Ilia Sokolinski

Satish Pudi

Ilya Languev

Pascal Renauld

Enning Xiang

Ilia Langouev

Hardik Singh Negi

Matt Amdur

Blake H Lewis

Asit Desai

Peng Mi

A method for performing write operations on a set of one or more physical disks of a set of one or more host machines is provided. The method receives a data block to write on at least one physical disk in the set of physical disks and generates a first set of one or more compressed sectors based on the received data block. The method writes (i) a first entry having a first header and the first set of compressed sectors to a data log that is maintained in a cache, and (ii) the first set of compressed sectors to a bank in memory. The method further determines if a size of data including compressed sectors in the bank satisfies a threshold, and when the size of data in the bank satisfies the threshold, writes the data to the at least one physical disk in the set of physical disks.

Enhanced data compression in distributed datastores

The efficiency of segment cleaning for a log-structured file system (LFS) is enhanced at least by storing additional information in a segment usage table (SUT). Live blocks (representing portions of stored objects) in an LFS are determined based at least on the SUT. Chunk identifiers associated with the live blocks are read. The live blocks are coalesced at least by writing at least a portion of the live blocks into at least one new segment. A blind update of at least a portion of the chunk identifiers in a chunk map is performed to indicate the new segment. The blind update includes writing to the chunk map without reading from the chunk map. In some examples, the objects comprise virtual machine disks (VMDKs) and the SUT changes between a list format and a bitmap format, to minimize size.

Enhancing efficiency of segment cleaning for a log-structured file system

The present disclosure is related to methods, systems, and machine-readable media for cloneless snapshot reversion. A request can be received to revert to a past snapshot of a virtual computing instance in a snapshot chain of a snapshot tree provided by a software defined data center. A live snapshot can be created at an end of the snapshot chain comprising the past snapshot. An intervening snapshot in the snapshot chain can be indicated as abandoned in a snapshot map associated with the snapshot tree based on the reversion.

Cloneless snapshot reversion

The present disclosure is related to methods, systems, and machine-readable media for log-structured file system management operations. An aggregate amount of over-provisioned computing resources assigned to a plurality of log-structured file system (LFS) objects that are allocated for performance of memory management operations associated with a virtual storage area network (vSAN) can be determined. A subset of LFS objects that are candidates for performance of a particular memory management operation based on an amount of over-provisioned computing resources consumed by one or more LFS objects among the plurality of LFS objects exceeding a resource consumption threshold associated with the determined amount of over-provisioned computing resources assigned to the plurality of LFS objects can be selected. The particular memory management operation using one or more of the candidate LFS objects can be performed.

Dynamic over-provisioning of space in a log-structured file system

Techniques for using data mirroring across regions to reduce the likelihood of losing objects in a cloud object storage platform are provided. In one set of embodiments, a computer system can upload first and second copies of a data object to first and second regions of the cloud object storage platform respectively, where the first and second copies are identical. The computer system can then attempt to read the first copy of the data object from the first region. If the read attempt fails, the computer system can retrieve the second copy of the data object from the second region.

Using data mirroring across multiple regions to reduce the likelihood of losing objects maintained in cloud object storage

Solutions for supporting storage using a multi-writer log-structured file system (LFS) are disclosed that include receiving incoming data from an object of a plurality of objects that are configured to simultaneously write to the LFS from different nodes; based at least on receiving the incoming data, determining whether sufficient free segments are available in a local segment usage table (SUT) for writing the incoming data; based at least on determining that insufficient free segments are available, requesting allocation of new free segments; writing the incoming data to a log; acknowledging the writing to the object; determining whether the log has accumulated a full segment of data; based at least on determining that the log has accumulated a full segment of data, writing the full segment of data to a first segment of the free segments; and updating the local SUT to mark the first segment as no longer free.

Supporting storage using a multi-writer log-structured file system

A method for managing data associated with objects stored in a cloud storage is provided. The method receives, at a first compute node, first data associated with an object stored in the cloud storage, the first compute node being one of a plurality of compute nodes that store data associated with different objects as storage objects in a log-structured merging (LSM) tree data structure. The method then assigns a first unique name to a first storage object associated with the first data, the first unique name comprising a combination of at least an identifier identifying the first compute node and a first incremental local value. The method stores the first storage object in a first level (L0) of the LSM tree data structure.

Scalable I/O operations on a log-structured merge (LSM) tree

In one set of embodiments, a computer system can create a snapshot of a data set, where the snapshot includes a plurality of data blocks of the data set. The computer system can upload the snapshot to a cloud object storage platform of a cloud infrastructure, where the snapshot is uploaded as a plurality of log segments conforming to an object format of the cloud object storage platform, and where each log segment includes one or more data blocks in the plurality of data blocks, and a set of metadata comprising, for each of the one or more data blocks, an identifier of the data set, an identifier of the snapshot, and a logical block address (LBA) of the data block. The computer system can then communicate the set of metadata to a server component running in a cloud compute and block storage platform of the cloud infrastructure.

Recovering the metadata of data backed up in cloud object storage

Techniques for reducing data log recovery time and metadata write amplification when checkpointing a data log of a storage object in a distributed storage system are provided. In one set of embodiments, a node of the system can determine whether the data log has reached a first threshold size, where the data log comprises a plurality of data log records, and where each data log record includes data and metadata for a write request directed to the storage object. If the data log has reached the first threshold size, the node can copy, from each of the plurality of data log records, the metadata for the write request to a corresponding metadata log entry in a metadata log of the storage object. The node can then truncate the data log by removing the plurality of data log records.

Techniques for reducing data log recovery time and metadata write amplification

A method for encrypting data in one or more data blocks is provided. The method receives a first data block to be written to a physical storage that includes one or more physical disks. The method applies a first random tweak to data indicative of the first data block to generate a first encrypted data block, and writes the first encrypted data block and the first random tweak to a first physical block of the physical storage. The method receives a second data block to be written to the physical storage. The method then applies a second random tweak, different than the first random tweak, to data indicative of the second data block to generate a second encrypted data block, and writes the second encrypted data block and the second random tweak to a second physical block of the physical storage.

Enhanced data encryption in distributed datastores using random tweaks stored in data blocks

Techniques for using erasure coding in a single region to reduce the likelihood of losing objects in a cloud object storage platform are provided. In one set of embodiments, a computer system can upload a plurality of data objects to a region of a cloud object storage platform, where the plurality of data objects including modifications to a data set. The computer system can further compute a parity object based on the plurality of data objects, where the parity object encodes parity information for the plurality of data objects. The computer system can then upload the parity object to the same region where the plurality of data objects was uploaded.

Using erasure coding in a single region to reduce the likelihood of losing objects maintained in cloud object storage

Techniques for using erasure coding across multiple regions to reduce the likelihood of losing objects in a cloud object storage platform are provided. In one set of embodiments, a computer system can upload each of a plurality of data objects to each of a plurality of regions of the cloud object storage platform. The computer system can further compute a parity object based on the plurality of data objects, where the parity object encodes parity information for the plurality of data objects. The computer system can then upload the parity object to another region of the cloud object storage platform different from the plurality of regions.

Using erasure coding across multiple regions to reduce the likelihood of losing objects maintained in cloud object storage

The present disclosure is related to methods, systems, and machine-readable media for supporting deduplication in file storage using file chunk hashes. A hash of a chunk of a log segment can be received from a software defined data center. A chunk identifier can be associated with the hash in a hash map that stores associations between sequentially-allocated chunk identifiers and hashes. The chunk identifier can be associated with a logical address corresponding to the chunk of the log segment in a logical map that stores associations between the sequentially-allocated chunk identifiers and logical addresses. A search of the hash map can be performed to determine if the chunk is a duplicate, and the chunk can be deduplicated responsive to a determination that the chunk is a duplicate.

Supporting deduplication in file storage using file chunk hashes

Processing write requests from clients includes logging the associated data into logs corresponding to the data objects targeted by the write requests. The logs are persisted by combining log entries from each of the logs into one ore more fixed-size data blocks. The fixed-size data blocks are inserted into a data tree stored on a block-based storage device.

Reduced write amplification using small-block log

Scalable segment cleaning for log-structured file systems (LFSs) includes determining counts of segment cleaners and virtual nodes, with each virtual node being associated with a plurality of objects. Each virtual node is assigned to a selected segment cleaner. Based at least on the assignments, performing, for each virtual node, segment cleaning of the objects by the assigned segment cleaner. A portion, less than all, of the virtual nodes are reassigned to a newly selected segment cleaner based on a change of the count of the segment cleaners and/or a change of the count of the virtual nodes. Based at least on the reassignments, segment cleaning of the objects is performed, for each reassigned virtual node, by the reassigned segment cleaner. In some examples, the objects comprise virtual machine disks (VMDKs) and the segment cleaning uses a segment usage table (SUT) to track segment usage and identify segment cleaning candidates.

Growing community of inventors

Palo Alto, CA, United States of America

Vamsi Gunturu