Abstract:
Embodiments herein are directed to efficient crash recovery of persistent metadata managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. Volume metadata managed by the volume layer is organized as a multi-level dense tree, wherein each level of the dense tree includes volume metadata entries for storing the volume metadata. When a level of the dense tree is full, the volume metadata entries of the level are merged with the next lower level of the dense tree. During a merge operation, two sets of generation IDs may be used in accordance with a double buffer arrangement: a first generation ID for the append buffer that is full (i.e., a merge staging buffer) and a second, incremented generation ID for the append buffer that accepts new volume metadata entries. Upon completion of the merge operation, the lower level (e.g., level 1) to which the merge is directed is assigned the generation ID of the merge staging buffer.
Abstract:
A technique quantifies logical storage space trapped in an extent store due to overlapping write requests associated with volume metadata managed by the volume layer. 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. When a level of the dense tree is full, the volume metadata entries of the level are merged with a next lower level of the dense tree in accordance with a merge operation. Illustratively, the technique may be invoked during the merge operation to examine the volume metadata entries at each level of the dense tree involved in the merge and determine the LBA range overlap of the entries. To that end, the technique may include an algorithm configured to calculate the overlapping space per level and then aggregate the overlapping space of all levels involved in the merge operation to arrive at a result that quantifies the logical storage space trapped in the extent store.
Abstract:
A technique quantifies logical storage space trapped in an extent store due to overlapping write requests associated with volume metadata managed by the volume layer. 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. When a level of the dense tree is full, the volume metadata entries of the level are merged with a next lower level of the dense tree in accordance with a merge operation. Illustratively, the technique may be invoked during the merge operation to examine the volume metadata entries at each level of the dense tree involved in the merge and determine the LBA range overlap of the entries. To that end, the technique may include an algorithm configured to calculate the overlapping space per level and then aggregate the overlapping space of all levels involved in the merge operation to arrive at a result that quantifies the logical storage space trapped in the extent store.
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., 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:
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 low-overhead merge technique enables restart of a merge operation with minimal logging of state information relating to progress of the merge operation by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The technique enables restart of the merge operation by ensuring that metadata, i.e., metadata pages, generated during the merge operation is not subject to de-duplication by providing a unique value in each metadata page that distinguishes the page, i.e., renders the page distinct or “unique”, from other metadata pages in an extent store. In addition, the technique ensures that a reference count on each metadata page is a value denoting a lack of de-duplication. To that end, the extent store layer is configured to not increment the reference count for a metadata page if, during the merge operation, the page is identical (and thus subject to deduplication) to an existing metadata page in the extent store.
Abstract:
A technique quantifies logical storage space trapped in an extent store due to overlapping write requests associated with volume metadata managed by the volume layer. 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. When a level of the dense tree is full, the volume metadata entries of the level are merged with a next lower level of the dense tree in accordance with a merge operation. Illustratively, the technique may be invoked during the merge operation to examine the volume metadata entries at each level of the dense tree involved in the merge and determine the LBA range overlap of the entries. To that end, the technique may include an algorithm configured to calculate the overlapping space per level and then aggregate the overlapping space of all levels involved in the merge operation to arrive at a result that quantifies the logical storage space trapped in the extent store.
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 technique quantifies logical storage space trapped in an extent store due to overlapping write requests associated with volume metadata managed by the volume layer. 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. When a level of the dense tree is full, the volume metadata entries of the level are merged with a next lower level of the dense tree in accordance with a merge operation. Illustratively, the technique may be invoked during the merge operation to examine the volume metadata entries at each level of the dense tree involved in the merge and determine the LBA range overlap of the entries. To that end, the technique may include an algorithm configured to calculate the overlapping space per level and then aggregate the overlapping space of all levels involved in the merge operation to arrive at a result that quantifies the logical storage space trapped in the extent store.