Abstract: Presented herein are methodologies for implementing erasure coding in a distributed log structured storage system. A method includes receiving a write request for first data from a file system, selecting a physical sector on a selected storage device in an array of storage devices on which to store the first data, assigning a key to the physical sector, storing the key and an indication of the physical sector in a key-to-physical medium map, erasure coding the data, including generating parity data associated with the first data, writing the first data and the parity data as a data stripe to each storage device in the array of storage devices and, in response to receiving the write request, sending the key to the file system. Read, update, and delete procedures in the context of a log structured framework are also described.

Abstract: Presented herein are methodologies for implementing erasure coding in a distributed log structured storage system. A method includes receiving a write request for first data from a file system, selecting a physical sector on a selected storage device in an array of storage devices on which to store the first data, assigning a key to the physical sector, storing the key and an indication of the physical sector in a key-to-physical medium map, erasure coding the data, including generating parity data associated with the first data, writing the first data and the parity data as a data stripe to each storage device in the array of storage devices and, in response to receiving the write request, sending the key to the file system. Read, update, and delete procedures in the context of a log structured framework are also described.

Abstract: Presented herein are methodologies for implementing erasure coding in a distributed log structured storage system. A method includes receiving a write request for first data from a file system, selecting a physical sector on a selected storage device in an array of storage devices on which to store the first data, assigning a key to the physical sector, storing the key and an indication of the physical sector in a key-to-physical medium map, erasure coding the data, including generating parity data associated with the first data, writing the first data and the parity data as a data stripe to each storage device in the array of storage devices and, in response to receiving the write request, sending the key to the file system. Read, update, and delete procedures in the context of a log structured framework are also described.

Abstract: Presented herein are methodologies for implementing erasure coding in a distributed log structured storage system. A method includes receiving a write request for first data from a file system, selecting a physical sector on a selected storage device in an array of storage devices on which to store the first data, assigning a key to the physical sector, storing the key and an indication of the physical sector in a key-to-physical medium map, erasure coding the data, including generating parity data associated with the first data, writing the first data and the parity data as a data stripe to each storage device in the array of storage devices and, in response to receiving the write request, sending the key to the file system. Read, update, and delete procedures in the context of a log structured framework are also described.

Abstract: A technique provides memory efficient caching of metadata managed by a volume layer of a storage input/output stack executing on one or more nodes of a cluster. Efficient caching of the metadata in a memory of a node may be realized through the use of a caching data structure, i.e., a page cache, configured to store a key-value pair, wherein the key is an extent key and the value is a metadata page containing the index entries. The page cache illustratively includes two data structures configured to maintain the properties of Least Recently Used (LRU) and Least Frequently Used (LFU) for the cache. The first data structure is a hash table that stores a dense tree metadata page (value) indexed by the extent key. The second data structure is a recycle queue that controls the metadata page stored in the hash table based on spatial and temporal locality of the page.

Abstract: A technique provides memory efficient caching of metadata managed by a volume layer of a storage input/output stack executing on one or more nodes of a cluster. Efficient caching of the metadata in a memory of a node may be realized through the use of a caching data structure, i.e., a page cache, configured to store a key-value pair, wherein the key is an extent key and the value is a metadata page containing the index entries. The page cache illustratively includes two data structures configured to maintain the properties of Least Recently Used (LRU) and Least Frequently Used (LFU) for the cache. The first data structure is a hash table that stores a dense tree metadata page (value) indexed by the extent key. The second data structure is a recycle queue that controls the metadata page stored in the hash table based on spatial and temporal locality of the page.

Abstract: A deferred refcount update technique efficiently frees storage space for metadata (associated with data) to be deleted during a merge operation managed by a volume layer of a node. The metadata is illustratively volume metadata embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) to extent keys maintained by an extent store layer of the node. One or more requests to delete (or overwrite) an LBA range within a LUN may be captured as page keys associated with metadata pages during the merge operation and the storage space associated with those metadata pages may be freed in an out-of-band fashion. The page keys of the metadata pages may be persistently recorded in a reference count (refcount) log to thereby allow the merge operation to complete without resolving deletion of the keys. A batch of page keys may be organized as one or more delete requests and, once the merge completes, the keys may be inserted into the refcount log.