Abstract: Compositions and methods for treating a retinopathy or inhibiting pathologic neovascularization in a subject are provided herein. In one embodiment, the method includes ablating or inhibiting IDO-dependent vascularizing cells (IDVCs) in the eye of the subject. Various methods of inhibiting or ablating IDVCs are described, including inhibiting IDO1 and/or integrated response nodes.

Abstract: Methods, systems, and devices for techniques to balance log structured merge trees are described. A computing system may rebalance a tree structure having an ordered set of leaf nodes by splitting or joining leaf nodes of the tree structure. To split a leaf node, the computing system may select a key to evenly partition key and value data stored in the leaf. The computing system may place each key block of the leaf node having keys less than or equal to the selected key in a first new leaf node, and may place each key block of the leaf node having keys greater than the selected key in a second new leaf node. To join leaf nodes of the tree structure, the computing system may place each key block and each value block of the leaf node and the adjacent leaf node in a new leaf node.

Abstract: An event trigger to flush key-value data from a volatile memory device is detected. In response to detection of the event trigger, a determination is made whether the key-value data comprises uncommitted data for one or more active database transactions. If the key-value data comprises uncommitted data for one or more active database transactions, the uncommitted data is moved to a hold aside buffer in the volatile memory device, and committed data in the key-value data is stored on a non-volatile memory device.

Abstract: Aspects of the present disclosure provide for operations for a tree data structure that provides order-based node traversal. For some embodiments, the tree data structure stores one or more key-value pairs, implements at least one linked-list data structure, and enables traversal of nodes within the tree data structure based on a key order (e.g., forward or reverse key order).

Abstract: Aspects of the present disclosure provide for operations of a key-value tree data structure that merges key-value pair data of a node, in a key-value tree data structure using counter values.

Abstract: Systems and techniques for reducing probabilistic filter query latency are described herein. A query for a probabilistic filter that is stored on a first media may be received from a caller. In response to receiving the query, cached segments of the probabilistic filter stored on a second media may be obtained. Here, the probabilistic filter provides a set membership determination that is conclusive in a determination that an element is not in a set. The query may be executed on the cached segments resulting in a partial query result. Retrieval of remaining data of the probabilistic filter from the first media to the second media may be initiated without intervention from the caller. Here, the remaining data corresponds to the query and data that is not in the cached segment. The partial query results may then be returned to the caller.

Abstract: Systems and techniques for reducing probabilistic filter query latency are described herein. A query for a probabilistic filter that is stored on a first media may be received from a caller. In response to receiving the query, cached segments of the probabilistic filter stored on a second media may be obtained. Here, the probabilistic filter provides a set membership determination that is conclusive in a determination that an element is not in a set. The query may be executed on the cached segments resulting in a partial query result. Retrieval of remaining data of the probabilistic filter from the first media to the second media may be initiated without intervention from the caller. Here, the remaining data corresponds to the query and data that is not in the cached segment. The partial query results may then be returned to the caller.

Abstract: Aspects of the present disclosure provide for operations of a key-value store (KVS) that uses journaling with storage of data (e.g., key data or value data of a key-value pair) in different types of data storage objects (e.g., data storage formats) selected based on one or more criteria.

Abstract: A KVS tree database and operations thereon are described herein. A KVS tree database is a multilevel tree that includes a base level and subsequent levels. The base level includes a heterogeneous kvset in a node, The heterogeneous kvset including entries for multiple KVS trees, such as a first entry for a first KVS tree and a second entry for a second KVS tree, The subsequent level includes a first node including a first homogeneous kvset for the first KVS tree and a second node including a second homogeneous kvset for the second KVS tree. Here, a homogeneous kvset includes nodes from only one KVS tree. The KVS tree database also includes a first determinative mapping of entries between the base level and the subsequent level and a second determinative mapping of entries between subsequent levels.

Abstract: Aspects of the present disclosure provide for operations of a key-value tree data structure that: merge key-value sets within a given node by merging and rewriting key blocks of the key-value sets while rewriting or deferring rewrite of value blocks of the merged key-value sets based on whether one or more child nodes of the given node comprise a leaf node; and move one or more portions of the merged key-value set into one or more child nodes of the given node.

Abstract: Aspects of the present disclosure provide various embodiments for selective use of a portion of a key, such as a prefix of the key (also referred to as a key prefix of a key), with respect to a key-value store (KVS) tree data structure, such as when storing a key-value pair (associated with the key) within the KVS tree data structure or navigating through the KVS tree data structure. For some embodiments, when navigating a KVS tree based on a key, a first set of levels (e.g., a first series of levels) of the KVS tree is navigated by a first portion (e.g., a prefix) of the key, and a second set of levels (e.g., a second series of levels) of the KVS tree is navigated by a second portion (e.g., an entire portion) of the key.

Abstract: Aspects of the present disclosure provide for operations for a tree data structure that provides order-based node traversal. For some embodiments, the tree data structure stores one or more key-value pairs, implements at least one linked-list data structure, and enables traversal of nodes within the tree data structure based on a key order (e.g., forward or reverse key order).

Abstract: Aspects of the present disclosure provide for operations of a key-value tree data structure that merges key-value pair data of a node, in a key-value tree data structure using counter values.

Abstract: Aspects of the present disclosure provide for operations of a key-value store (KVS) that uses journaling with storage of data (e.g., key data or value data of a key-value pair) in different types of data storage objects (e.g., data storage formats) selected based on one or more criteria.

Abstract: Aspects of the present disclosure provide for operations for a tree data structure that provides order-based node traversal. For some embodiments, the tree data structure stores one or more key-value pairs, implements at least one linked-list data structure, and enables traversal of nodes within the tree data structure based on a key order (e.g., forward or reverse key order).

Abstract: Aspects of the present disclosure provide for operations of a key-value tree data structure that merges key-value pair data of a node, in a key-value tree data structure using counter values.

Abstract: A KVS tree database and operations thereon are described herein. A KVS tree database is a multilevel tree that includes a base level and subsequent levels. The base level includes a heterogeneous kvset in a node, The heterogeneous kvset including entries for multiple KVS trees, such as a first entry for a first KVS tree and a second entry for a second KVS tree. The subsequent level includes a first node including a first homogeneous kvset for the first KVS tree and a second node including a second homogeneous kvset for the second KVS tree. Here, a homogeneous kvset includes nodes from only one KVS tree. The KVS tree database also includes a first determinative mapping of entries between the base level and the subsequent level and a second determinative mapping of entries between subsequent levels.

Abstract: Aspects of the present disclosure provide for operations of a key-value store (KVS) that uses journaling with storage of data (e.g., key data or value data of a key-value pair) in different types of data storage objects (e.g., data storage formats) selected based on one or more criteria.

Abstract: Systems and techniques for stream selection from multi-stream storage devices. Notification of a KVS tree write request for a multi-stream storage device is received. The notification includes a KVS tree scope corresponding to data in the write request. A stream identifier (ID) is assigned to the write request based on the KVS tree scope and a stability value of the write request. The stream ID is returned to govern stream assignment to the write request, the stream assignment modifying a write operation of the multi-stream storage device.

Abstract: Systems and techniques for collecting and using merge tree garbage metrics are described herein. A kvset is created for a node in a KVS tree. Here, a set of kvset metrics for the kvset are computed as part of the node creation. The kvset is added to the node. The node is selected for a compaction operation based on a metric in the set of kvset metrics. The compaction operation is performed on the node.