Vmware, Inc.

Maxime Austruy

Wenguang Wang

Junlong Gao

Richard Paul Spillane

Christos Karamanolis

Satish Pudi

Petr Vandrovec

Ilia Sokolinski

Marcos Kawazoe Aguilera

Vamsi Gunturu

Ilya Languev

Robert T Johnson

Adrian Drzewiecki

Ole Agesen

Boris Weissman

Keith Adams

Jennifer-Ann M Anderson

Mallik Mahalingam

Irfan Ahmad

Asit Desai

Christoph Klee

Jad Chamcham

Yunshan Luke Lu

Christian Czezatke

Christian Matthew Leroy

Mounesh Badiger

Rawlinson Rivera

Alexander T Garthwaite

Abhishek Gupta

Eric Shannon Knauft

Ilia Langouev

Matthew Benjamin Amdur

Vamsidhar Gunturu

Long Yang

Kapil Arya

Kamal Jeet Charan

Pushpesh Sharma

Rick Spillane

The present disclosure provides techniques for deduplicating files. The techniques include creating a cache or subset of a large data structure. The large data structure organizes information by random hash values. The random hash values result in a random organization of information within the data structure, with the information spanning a large number of storage blocks within a storage system. The cache, however, is within memory and is small relative to the data structure. The cache is created so as to contain information that is likely to be needed during deduplication of a file. Having needed information within memory rather than in storage results in faster read and write operations to that information, improving the performance of a computing system.

Small in-memory cache to speed up chunk store operation for deduplication

Examples disclosed herein relate to propagating changes made on a file system volume of a primary cluster of nodes to the same file system volume also being managed by a secondary cluster of nodes. An application is executed on both clusters, and data changes on the primary cluster are mirrored to the secondary cluster using an exo-clone file. The exo-clone file includes the differences between two or more snapshots of the volume on the primary cluster, along with identifiers of the change blocks and (optionally) state information thereof. Just these changes, identifiers, and state information are packaged in the exo-clone file and then exported to the secondary cluster, which in turn makes the changes to its version of the volume. Exporting just the changes to the data blocks and the corresponding block identifiers drastically reduces the information needed to be exchanged and processed to keep the two volumes consistent.

Container runtime image management across the cloud

The disclosure herein describes storing data using a capacity data storage tier and a smaller performance data storage tier. The capacity data storage tier includes capacity data storage hardware configured to store log-structured leaf pages (LLPs), and the performance data storage tier includes performance data storage hardware. A virtual address table (VAT) includes a set of virtual address entries referencing the LLPs. A tree-structured index includes index nodes referencing the set of virtual address entries of the VAT. Data to be stored is received, and at least a first portion of metadata associated with the received data is stored in the LLPs using the VAT, and at least a second portion of metadata associated with the received data is stored in the performance data storage tier. The architecture reduces space usage of the performance data storage tier.

Storing data in a log-structured format in a two-tier storage system

The disclosure provides techniques for deduplicating files. The techniques include, upon creating or modifying a file, placing a logical timestamp of the current logical time, within a queue associated with the directory of the file. The techniques further include placing the logical timestamp within a queue of each parent directory of the directory of the file. To determine a set of files for deduplication, the techniques disclosed herein identify files that have been modified within a logical time range. The set of files modified within a logical time is identified by traversing directories of a storage system, the directories being organized within a tree structure. If a directory's queue does not contain a timestamp that is within the logical time range, then all child directories can be skipped over for further processing, such that no files within the child directories end up being within the set of files for deduplication.

Fast algorithm to find file system difference for deduplication

Disclosed techniques include deduplication. Techniques include determining whether a file is unique, and depending on whether the file is unique, deduplicating only part of the file or the entire file. The techniques include processing the first chunk of a file to determine whether the hash of the chunk hash is already within a chunk hash table, and if not, then a percentage of chunks of the file is similarly processed. If any of the hashes of chunks are already in the chunk hash table, then at least some of file has been previously deduplicated, and file is not unique the storage system. If none of the processed chunks have a hash that is already in the chunk hash table, then the file is considered to be unique within chunk store and only a partial percentage of the file's chunks are deduplicated. Not all of a unique file's chunks are deduplicated.

Probabilistic algorithm to check whether a file is unique for deduplication

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

The disclosure herein describes writing data to a log-structured merge (LSM) tree file system on an object storage platform. Write data instructions indicating data for writing to the LSM tree file system are received. Based on the received instructions, the data is written to the first data cache. Based on an instruction to transfer data in the live data cache to the LSM tree file system, the first data cache is converted to a stable cache. A second data cache configured as a live data cache is then generated based on cloning the first data cache. The data in the first data cache is then written to the LSM tree file system. Use of a stable cache and a cloned live data cache enables parallel writing data to the file system by the stable cache and handling write data instructions by the live data cache.

Writing data to an LSM tree file structure using consistent cache staging

Examples provide a method of communication between a client driver and a filesystem server. The client driver executes in a virtual machine (VM) and the filesystem server executes in a hypervisor. The method includes: allocating, by the client driver, shared memory in an address space of the VM for the communication; sending identification information for the shared memory from the client driver to the filesystem server through an inter-process communication channel between the client driver and the filesystem server; identifying, by the filesystem server in cooperation with a kernel of the hypervisor, the shared memory within an address space of the hypervisor, based on the identification information, to create a shared memory channel; sending commands from the client driver to the filesystem server through the shared memory channel; and receiving completion messages for the commands from the filesystem server to the client driver through the shared memory channel.

Low-latency shared memory channel across address spaces in a computing system

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

The present disclosure provides techniques for deallocating previously allocated storage blocks. The techniques include obtaining a list of chunk IDs to analyze, choosing a chunk ID, and determining the storage blocks spanned by the chunk corresponding to the chosen chunk ID. The technique further includes determining whether any file references any storage blocks spanned by the chunk. The determining may be performed by comparing an internal reference count to a total reference count, where the internal reference count is the number of reference to the storage block by a chunk ID data structure. If no files reference any of the storage blocks spanned by the chunk, then all the storage blocks of the chunk can be deallocated.

Efficient garbage collection of variable size chunking deduplication

Solutions for managing archived storage include receiving, at a first node, a snapshot comprising object data (e.g., a virtual machine disk snapshot) from a second node (e.g., a software defined data center), and storing the snapshot in a tiered structure that includes a data tier and a metadata tier. Snapshots may be used for fail-over operations and/or backups, to support disaster recovery. The data tier comprises a log-structured file system (LFS), and the metadata tier comprises a content addressable storage (CAS) identifying addresses within the LFS. The metadata tier also comprises a logical layer indicating content in the CAS. Segment cleaning of the data tier is performed using a segment usage table (SUT). Some examples include performing a fail-over operation from the second node to a third node using at least the stored snapshot for workload recovery. In some examples, the CAS comprises a log-structured merge-tree (LSM-tree).

Log-structured formats for managing archived storage of objects

The present disclosure is related to methods, systems, and machine-readable media for supporting deduplication in object storage using subset hashes. A plurality of hashes of a plurality of blocks of a plurality of log segments can be received from a software defined data center, wherein each block corresponds to a respective logical address. Each of the plurality of logical addresses can be associated with a respective sequentially-allocated chunk identifier in a logical map. A subset hash comprising a hash of a subset of the plurality of blocks can be determined that corresponds to a contiguous range of the plurality of logical addresses. A search of a hash map for the subset hash can be performed to determine if the subset hash is a duplicate. The subset of the plurality of blocks can be deduplicated responsive to a determination that the subset hash is a duplicate.

Supporting deduplication in object storage using subset hashes

The present disclosure provides techniques for deduplicating files. The techniques include creating a data structure that organizes metadata about chunks of files, the organization of the metadata preserving order and locality of the chunks within files. The organization of the metadata within storage blocks of storage devices matches the order of chunks within files. Upon a read or write operation to a metadata, the preservation of locality of metadata results in the likely fetching, from storage into a memory cache, metadata of subsequent and contiguous chunks. The preserved locality results in faster subsequent read and write operations of metadata, because the read and write operations are likely to be executed from memory rather than from storage.

Organize chunk store to preserve locality of hash values and reference counts for deduplication

A system and method for transferring data between a user space buffer in the address space of a user space process running on a virtual machine and a storage system are described. The user space buffer is represented as a file with a file descriptor. In the method, a file system proxy receives a request for I/O read or write from the user space process without copying data to be transferred. The file system proxy then sends the request to a file system server without copying data to be transferred. The file system server then requests that the storage system perform the requested I/O directly between the storage system and the user space buffer, the only transfer of data being between the storage system and the user space buffer.

Zero copy method that can span multiple address spaces for data path applications

Techniques for the increased efficiency of storing data objects storage in the object storage of a software designed data center (SDDC) are provided. The techniques include the efficient storage of data, while enabling snapshots of each updating of the data. The snapshots of the data may be efficiently recovered via the techniques. Difference-level mappings for each snapshot are encoded in compact self-balancing data trees included in the object's metadata. The metadata mappings include mappings between various address spaces employed by the SDDC, as well as the address spaces employed by data stores that store the data on physical medium. Because the metadata is efficiently structured, the metadata for an object may be cached for quick lookups during data access and/or snapshot recovery. The techniques also provide low-latency recovery and/or system rollback in the event of any failure in the SDDC.

Growing community of inventors

Lausanne, Switzerland

Maxime Austruy