Abstract: Techniques are provided for implementing garbage collection and bin synchronization for a distributed storage architecture of worker nodes managing distributed storage composed of bins of blocks. As the distributed storage architecture scales out to accommodate more storage and worker nodes, garbage collection used to free unused blocks becomes unmanageable and slow. Accordingly garbage collection is improved by utilizing heuristics to dynamically speed up or down garbage collection and set sizes for subsets of a bin to process instead of the entire bin. This ensures that garbage collection does not use stale information about what blocks are in-use, and ensures garbage collection does not unduly impact client I/O processing or conversely falls behind on garbage collection. Garbage collection can be incorporated into a bin sync process to improve the efficiency of the bin sync process so that unused blocks are not needlessly copied by the bin sync process.

Abstract: Techniques are provided for implementing garbage collection and bin synchronization for a distributed storage architecture of worker nodes managing distributed storage composed of bins of blocks. As the distributed storage architecture scales out to accommodate more storage and worker nodes, garbage collection used to free unused blocks becomes unmanageable and slow. Accordingly garbage collection is improved by utilizing heuristics to dynamically speed up or down garbage collection and set sizes for subsets of a bin to process instead of the entire bin. This ensures that garbage collection does not use stale information about what blocks are in-use, and ensures garbage collection does not unduly impact client I/O processing or conversely falls behind on garbage collection. Garbage collection can be incorporated into a bin sync process to improve the efficiency of the bin sync process so that unused blocks are not needlessly copied by the bin sync process.

Abstract: Techniques are provided for key-value store and file system integration to optimize key value store operations. A key-value store is integrated within a file system of a node. A log structured merge tree of the key-value store may be populated with a key corresponding to a content hash of a value data item stored separate from the key. A random distribution search may be performed upon a sorted log of the log structured merge tree to identify the key for accessing the value data item. A starting location for the random distribution search is derived from key information, a log size of the sorted log, and/or a keyspace size of a keyspace associated with the key.

Abstract: Techniques are provided for key-value store and file system integration to optimize key value store operations. A key-value store is integrated within a file system of a node. A log structured merge tree of the key-value store may be populated with a key corresponding to a content hash of a value data item stored separate from the key. A random distribution search may be performed upon a sorted log of the log structured merge tree to identify the key for accessing the value data item. A starting location for the random distribution search is derived from key information, a log size of the sorted log, and/or a keyspace size of a keyspace associated with the key.

Abstract: Techniques are provided for implementing garbage collection and bin synchronization for a distributed storage architecture of worker nodes managing distributed storage composed of bins of blocks. As the distributed storage architecture scales out to accommodate more storage and worker nodes, garbage collection used to free unused blocks becomes unmanageable and slow. Accordingly garbage collection is improved by utilizing heuristics to dynamically speed up or down garbage collection and set sizes for subsets of a bin to process instead of the entire bin. This ensures that garbage collection does not use stale information about what blocks are in-use, and ensures garbage collection does not unduly impact client I/O processing or conversely falls behind on garbage collection. Garbage collection can be incorporated into a bin sync process to improve the efficiency of the bin sync process so that unused blocks are not needlessly copied by the bin sync process.

Abstract: Techniques are provided for implementing garbage collection and bin synchronization for a distributed storage architecture of worker nodes managing distributed storage composed of bins of blocks. As the distributed storage architecture scales out to accommodate more storage and worker nodes, garbage collection used to free unused blocks becomes unmanageable and slow. Accordingly garbage collection is improved by utilizing heuristics to dynamically speed up or down garbage collection and set sizes for subsets of a bin to process instead of the entire bin. This ensures that garbage collection does not use stale information about what blocks are in-use, and ensures garbage collection does not unduly impact client I/O processing or conversely falls behind on garbage collection. Garbage collection can be incorporated into a bin sync process to improve the efficiency of the bin sync process so that unused blocks are not needlessly copied by the bin sync process.

Abstract: Techniques are provided for key-value store and file system integration to optimize key value store operations. A key-value store is integrated within a file system of a node. A log structured merge tree of the key-value store may be populated with a key corresponding to a content hash of a value data item stored separate from the key. A random distribution search may be performed upon a sorted log of the log structured merge tree to identify the key for accessing the value data item. A starting location for the random distribution search is derived from key information, a log size of the sorted log, and/or a keyspace size of a keyspace associated with the key.