Netapp, Inc.

Edward D McClanahan

Dhaval Patel

Manish Swaminathan

Jeffrey S Kimmel

John A Muth

Mandar Naik

Pinkesh Zaveri

A technique reduces an amount of metadata stored in a memory of a node in a cluster. An extent store layer of a storage input/output (I/O) stack executing on the node stores key-value pairs in a plurality of data structures, e.g., cuckoo hash tables, resident in the memory. The cuckoo hash table embodies metadata that describes an extent and, as such, may be organized to associate a location on disk with a value that identifies the location on disk. The value may be embodied as a locator that includes a reference count used to support deduplication functionality of the extent store layer with respect to the extent. The reference count is divided into two portions: a delta count portion stored in memory for each slot of the hash table and an overflow count portion stored on disk in a header of each extent. One bit of the delta count portion is reserved as an overflow bit that indicates whether the in-memory reference count has overflowed. Another bit of the delta count portion is reserved as a sign bit that indicates whether the value of the remaining delta count portion, which stores the 'delta' of the reference count, is positive or negative. Overflow updates to the overflow count portion on disk are postponed until all of the bits of the delta count portion are consumed as negative/positive transitions.

Technique for reducing metadata stored in a memory of a node

A flow control technique prevents exhaustion of storage resources in an exactly once semantics (EOS) system of a storage input/output stack executing on a node of a cluster. An EOS server may service transactions sent by an EOS client and issue replies with results to the EOS client. In order to replay the transactions during normal operation after recovery from a crash, the EOS server persistently stores the transactions in the storage resources until an acknowledgement of completion is received from the EOS client for each pending transaction. The EOS client may issue a checkpoint acknowledgement, e.g., as a prune record, after a periodic interval that marks the completion of all pending transactions issued prior to the record. The EOS server need only log the prune record (rather than each pending transaction) to thereby prevent exhaustion of the storage resources, while also minimizing logging overhead of the server. In response to the crash and during replay of the transactions, the EOS server may employ the prune records to ignore those transactions that have already been acknowledged by the EOS client, thereby reducing time required for replay of the transactions.

Flow control technique for EOS system

A technique perturbs an extent key to compute a candidate extent key in the event of a collision with metadata (i.e., two extents having different data that yield identical hash values) stored in a memory of a node in a cluster. The perturbing technique may be used to compute a candidate extent key that is not previously stored in an extent store instance. The candidate extent key may be computed from a hash value of an extent using a perturbing algorithm, i.e., a hash collision computation, which illustratively adds a perturb value to the hash value. The perturb value is illustratively sufficient to ensure that the candidate extent key resolves to a same hash bucket and node (extent store instance) as the original extent key. In essence, the technique ensures that the original extent key is perturbed in a deterministic manner to generate the candidate extent key, so that the original extent and candidate extent key 'decode' to the same hash bucket and extent store instance.

Perturb key technique

A rate matching technique may be configured to adjust a rate of cleaning of one or more selected segments of the storage array to accommodate a variable rate of incoming workload processed by a storage input/output (I/O) stack executing on one or more nodes of a cluster. An extent store layer of the storage I/O stack may clean a segment in accordance with segment cleaning which, illustratively, may be embodied as a segment cleaning process. The rate matching technique may be implemented as a feedback control mechanism configured to adjust the segment cleaning process based on the incoming workload. Components of the feedback control mechanism may include one or more weight schedulers and various accounting data structures, e.g., counters, configured to track the progress of segment cleaning and free space usage. The counters may also be used to balance the rates of segment cleaning and incoming I/O workload, which may change depending upon an incoming I/O rate. When the incoming I/O rate changes, the rate of segment cleaning may be adjusted accordingly to ensure that rates are substantially balanced.

Rate matching technique for balancing segment cleaning and I/O workload

An optimized segment cleaning technique is configured to efficiently clean one or more selected portions or segments of a storage array coupled to one or more nodes of a cluster. A bottom-up approach of the segment cleaning technique is configured to read all blocks of a segment to be cleaned (i.e., an 'old' segment) to locate extents stored on the SSDs of the old segment and examine extent metadata to determine whether the extents are valid and, if so, relocate the valid extents to a segment being written (i.e., a 'new' segment). A top-down approach of the segment cleaning technique obviates reading of the blocks of the old segment to locate the extents and, instead, examines the extent metadata to determine the valid extents of the old segment. A hybrid approach may extend the top-down approach to include only full stripe read operations needed for relocation and reconstruction of blocks as well as retrieval of valid extents from the stripes, while also avoiding any unnecessary read operations of the bottom-down approach.

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Danville, CA, United States of America

Edward D McClanahan