Abstract: A first plurality of block identifiers is sorted based, at least in part, on a measure of spatial locality. A second plurality of block identifiers is sorted based, at least in part, on the measure of spatial locality. At least the first plurality of block identifiers and the second plurality of block identifiers are incrementally merged into a third plurality of block identifiers based, at least in part, on the measure of spatial locality. A block of data corresponding to metadata associated with a plurality of block identifiers of the third plurality of block identifiers is updated.

Abstract: A first plurality of block identifiers is sorted based, at least in part, on a measure of spatial locality. A second plurality of block identifiers is sorted based, at least in part, on the measure of spatial locality. At least the first plurality of block identifiers and the second plurality of block identifiers are incrementally merged into a third plurality of block identifiers based, at least in part, on the measure of spatial locality. A block of data corresponding to metadata associated with a plurality of block identifiers of the third plurality of block identifiers is updated.

Abstract: A first plurality of block identifiers is sorted based, at least in part, on a measure of spatial locality. A second plurality of block identifiers is sorted based, at least in part, on the measure of spatial locality. At least the first plurality of block identifiers and the second plurality of block identifiers are incrementally merged into a third plurality of block identifiers based, at least in part, on the measure of spatial locality. A block of data corresponding to metadata associated with a plurality of block identifiers of the third plurality of block identifiers is updated.

Abstract: A technique preserves efficiency for replication of data between a source node of a source cluster (“source”) and a destination node of a destination cluster (“destination”) of a clustered network. Replication in the clustered network may be effected by leveraging global in-line deduplication at the source to identify and avoid copying duplicate data from the source to the destination. To ensure that the copy of the data on the destination is synchronized with the data received at the source, the source creates a snapshot of the data for use as a baseline copy at the destination. Thereafter, new data received at the source that differs from the baseline snapshot are transmitted and copied to the destination. In addition, the source and destination nodes negotiate to establish a mapping of name-to-data when transferring data (i.e., an extent) between the clusters.

Abstract: A N-way merge technique efficiently updates metadata in accordance with a N-way merge operation managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata is embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) accessible by a host to durable extent keys, and is organized as a multi-level dense tree. The mappings are organized such that a higher level of the dense tree contains more recent mappings than a next lower level, i.e., the level immediately below. The N-way merge operation is an efficient (i.e., optimized) way of updating the volume metadata mappings of the dense tree by merging the mapping content of all three levels in a single iteration, as opposed to merging the content of the first level with the content of the second level in a first iteration of a two-way merge operation and then merging the results of the first iteration with the content of the third level in a second iteration of the operation.

Abstract: A first plurality of block identifiers is sorted based, at least in part, on a measure of spatial locality. A second plurality of block identifiers is sorted based, at least in part, on the measure of spatial locality. At least the first plurality of block identifiers and the second plurality of block identifiers are incrementally merged into a third plurality of block identifiers based, at least in part, on the measure of spatial locality. A block of data corresponding to metadata associated with a plurality of block identifiers of the third plurality of block identifiers is updated.

Abstract: A first plurality of block identifiers is sorted based, at least in part, on a measure of spatial locality. A second plurality of block identifiers is sorted based, at least in part, on the measure of spatial locality. At least the first plurality of block identifiers and the second plurality of block identifiers are incrementally merged into a third plurality of block identifiers based, at least in part, on the measure of spatial locality. A block of data corresponding to metadata associated with a plurality of block identifiers of the third plurality of block identifiers is updated.

Abstract: A flash-optimized, log-structured layer of a file system of a storage input/output (I/O) stack executes on one or more nodes of a cluster. The log-structured layer of the file system provides sequential storage of data and metadata (i.e., a log-structured layout) on solid state drives (SSDs) of storage arrays in the cluster to reduce write amplification, while leveraging variable compression and variable length data features of the storage I/O stack. The data may be organized as an arbitrary number of variable-length extents of one or more host-visible logical units (LUNs) served by the nodes. The metadata may include mappings from host-visible logical block address ranges (i.e., offset ranges) of a LUN to extent keys, as well as mappings of the extent keys to SSD storage locations of the extents. The storage location of an extent on SSD is effectively “virtualized” by its mapped extent key (i.e.

Abstract: A N-way merge technique efficiently updates metadata in accordance with a N-way merge operation managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata is embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) accessible by a host to durable extent keys, and is organized as a multi-level dense tree. The mappings are organized such that a higher level of the dense tree contains more recent mappings than a next lower level, i.e., the level immediately below. The N-way merge operation is an efficient (i.e., optimized) way of updating the volume metadata mappings of the dense tree by merging the mapping content of all three levels in a single iteration, as opposed to merging the content of the first level with the content of the second level in a first iteration of a two-way merge operation and then merging the results of the first iteration with the content of the third level in a second iteration of the operation.

Abstract: A N-way merge technique efficiently updates metadata in accordance with a N-way merge operation managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata is embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) accessible by a host to durable extent keys, and is organized as a multi-level dense tree. The mappings are organized such that a higher level of the dense tree contains more recent mappings than a next lower level, i.e., the level immediately below. The N-way merge operation is an efficient (i.e., optimized) way of updating the volume metadata mappings of the dense tree by merging the mapping content of all three levels in a single iteration, as opposed to merging the content of the first level with the content of the second level in a first iteration of a two-way merge operation and then merging the results of the first iteration with the content of the third level in a second iteration of the operation.

Abstract: The embodiments described herein are directed to an organization of metadata managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata managed by the volume layer, i.e., the volume metadata, is illustratively embodied as mappings from addresses, i.e., logical block addresses (LBAs), of a logical unit (LUN) accessible by a host to durable extent keys maintained by an extent store layer of the storage I/O stack. In an embodiment, the volume layer organizes the volume metadata as a mapping data structure, i.e., a dense tree metadata structure, which represents successive points in time to enable efficient access to the metadata.

Abstract: A technique preserves efficiency for replication of data between a source node of a source cluster (“source”) and a destination node of a destination cluster (“destination”) of a clustered network. Replication in the clustered network may be effected by leveraging global in-line deduplication at the source to identify and avoid copying duplicate data from the source to the destination. To ensure that the copy of the data on the destination is synchronized with the data received at the source, the source creates a snapshot of the data for use as a baseline copy at the destination. Thereafter, new data received at the source that differs from the baseline snapshot are transmitted and copied to the destination. In addition, the source and destination nodes negotiate to establish a mapping of name-to-data when transferring data (i.e., an extent) between the clusters.

Abstract: In one embodiment, a layered file system includes a volume layer and an extent store layer configured to provide sequential log-structured layout of data and metadata on solid state drives (SSDs) of one or more storage arrays. The data is organized as variable-length extents of one or more logical units (LUNs). The metadata includes volume metadata mappings from offset ranges of a LUN to extent keys and extent metadata mappings of the extent keys to storage locations of the extents on the SSDs. The extent store layer maintaining the extent metadata mappings determines whether an extent is stored on a storage array, and, in response to determination that the extent is stored on the storage array, returns an extent key for the stored extent to the volume layer to enable global inline de-duplication that obviates writing a duplicate copy of the extent on the storage array.

Abstract: A flash-optimized, log-structured layer of a file system of a storage input/output (I/O) stack executes on one or more nodes of a cluster. The log-structured layer of the file system provides sequential storage of data and metadata (i.e., a log-structured layout) on solid state drives (SSDs) of storage arrays in the cluster to reduce write amplification, while leveraging variable compression and variable length data features of the storage I/O stack. The data may be organized as an arbitrary number of variable-length extents of one or more host-visible logical units (LUNs) served by the nodes. The metadata may include mappings from host-visible logical block address ranges (i.e., offset ranges) of a LUN to extent keys, as well as mappings of the extent keys to SSD storage locations of the extents. The storage location of an extent on SSD is effectively “virtualized” by its mapped extent key (i.e.

Abstract: Partially overwriting a compression group without decompressing compressed data can consumption of resources for the decompression. A storage server partially overwrites the compression group when a file block identifier of a client's write request resolves to the compression group. The compression group remains compressed while the partial overwriting is performed.

Abstract: In one embodiment, a node coupled to one or more storage devices executes a storage input/output (I/O) stack having a volume layer, a persistence layer and an administration layer that interact to create a copy of a parent volume associated with a storage container on the one or more storage devices. A copy create start message is received at the persistence layer from the administration layer. The persistence layer ensures that dirty data for the parent volume is incorporated into the copy of the parent volume. New data for the parent volume received at the persistence layer during creation of the copy of the parent volume is prevented from incorporation into the copy of the parent volume. A reply to the copy create start message is sent from the persistence layer to the administration layer to initiate the creation of the copy of the parent volume at the volume layer.

Abstract: In one embodiment, storage arrays of solid state drives (SSDs) coupled to a node are organized as redundant array of independent disks (RAID) groups. Each storage array includes one or more segments. Each segment has contiguous free space on the SSDs. Data and metadata is organized on the SSDs with a sequential log-structured layout, with the data organized as variable-length extents of one or more logical units (LUNs). Segment cleaning is performed to clean a selected segment by moving the extents of the selected segment that contain valid data to one or more different segments so as to free the selected segment. Additional extents are written as a sequence of contiguous range write operations to the entire free segment with temporal locality to reduce data relocation within the SSDs as a result of the write operations.

Abstract: The embodiments described herein are directed to efficient merging of metadata managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata managed by the volume layer, i.e., the volume metadata, is illustratively organized as a multi-level dense tree metadata structure, wherein each level of the dense tree metadata structure (dense tree) includes volume metadata entries for storing the volume metadata. The volume metadata entries of an upper level of the dense tree metadata structure are merged with the volume metadata entries of a next lower level of the dense tree metadata structure when the upper level is full. The volume metadata entries of the merged levels are organized as metadata pages and stored as one or more files on the SSDs.

Abstract: In one embodiment, a technique is provided for distributing data and associated metadata within a distributed storage architecture. A set of hash tables that embody mappings of cluster-wide identifiers associated with storage locations are stored for write data of write requests organized into extents. A hash value is generated from a hash function applied to each extent. The hash value is overloaded and used for multiple purposes within the distributed storage architecture, including (i) a remainder computation on the hash value to select a bucket of a plurality of buckets representative of the extents, (ii) a hash table selector of the hash value to select a hash table from the set of hash tables, and (iii) a hash table index computed from the hash value to select an entry from a plurality of entries of the selected hash table having a cluster-wide identifier identifying a storage location for the extent.

Abstract: A three-way merge technique efficiently updates metadata in accordance with a three-way merge operation managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata is embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) accessible by a host to durable extent keys, and is organized as a multi-level dense tree. The mappings are organized such that a higher level of the dense tree contains more recent mappings than a next lower level, i.e., the level immediately below. The three-way merge operation is an efficient (i.e.