The disclosed technology relates to a system configured to detect a modification to a node in a tree data structure. The node is associated with a content item managed by a content management service as well as a filename. The system may append the filename and a separator to a filename array, determine a location of the filename in the filename array, and store the location of the filename in the node.

One example method includes, in a data buffer that includes one or more words and whitespaces, calculating a hash value of data in a window that is movable within the data buffer, comparing the hash value to a mask, and when the hash value matches the mask, identifying a position of the window in the data buffer as a chunk anchor position, searching for a whitespace nearest the chunk anchor position, and designating an offset of the whitespace as a segment boundary.

A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

A data layout model generation system generates, with reinforcement learning, a node configuration and a data layout key in a distributed parallel database. This system includes a sample acquisition processor that acquires, on the basis of a predetermined acquisition method, sample data from data stored in the distributed parallel database, a data layout estimator having, as states in the reinforcement learning, the node configuration and the data layout key including information regarding an order of sorting columns that constitute the data and information regarding a method for distribution between nodes, the data layout estimator estimating layout of the data on the basis of the state and the sample data, a reward calculator that calculates a reward in the reinforcement learning on the basis of a result obtained by estimating the layout of the data, the node configuration, and a processing cost of a query executed on the distributed parallel database.

In one embodiment, a computer networking device calculates a first hash value for an identifier of a group of computing devices, as well as a second hash value for the identifier of the group of computing devices, with each hash value being at least in part on the identifier of the group of computing devices and an identifier of the respective interface. The computer networking device may also analyze the first hash value with respect to the second hash value and select the first interface for association with the identifier of the group of computing devices based at in part on the analyzing. The computer networking device may further store an indication that the identifier of the group of computing devices is associated with the first interface.

In one embodiment, a method includes receiving at a head-mounted device a speech input from a user and a visual input captured by cameras of the head-mounted device, wherein the visual input comprises subjects and attributes associated with the subjects, and wherein the speech input comprises a co-reference to one or more of the subjects, resolving entities corresponding to the subjects associated with the co-reference based on the attributes and the co-reference, and presenting a communication content responsive to the speech input and the visual input at the head-mounted device, wherein the communication content comprises information associated with executing results of tasks corresponding to the resolved entities.

A method, computer system, and a computer program product for ensuring integrity of records in a NoSQL database including a first table and a second table is provided. The present invention may include the first table having first records representing respective first entities and the second table having second records representing respective second entities. The present invention may include using a hash table associating each second entity of the second table with the respective hash or summary hash values of first records for reading the second records of the second table.

In accordance with an embodiment, described herein is a system and method for use of lock-less data structures and processes with a multidimensional database computing environment. Lock-less algorithms or processes can be implemented with specific hardware-level instructions so as to provide atomicity. A memory stores an index cache retaining a plurality of index pages of the multidimensional database. A hash table indexes index pages in the index cache, wherein the hash table is accessible by a plurality of threads in parallel through application of the lock-less process.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.

A service computing system (server) has a storage stored thereon multiple records associated with multiple items. Each item has a piece of smart fabric fixed thereon. Each record stores at least a unique identifier of a piece of smart fabric and a unique identifier of a verification and authentication device associated with the item. The server is configured to receive a verification request from a mobile device containing at least one of a unique identifier of a piece of smart fabric associated with an item, or a unique identifier of a verification and authentication device associated with the item. In response to determining that the identifier of the smart fabric or the identifier of the verification and authentication device is associated with a record, the server generates a token and causes the token to be received by the verification and authentication device, causing the verification and authentication device to transmit data associated with the token to the piece of smart fabric for authentication.