Abstract: A first set of subconditions is obtained. Approximate matching of the first set of subconditions against a plurality of sets of subconditions is performed. A second set of subconditions among the plurality of sets of subconditions is accessed, wherein a representation of a subcondition in the first set and/or the second set of subconditions comprises a value having one of a plurality of states, and wherein the plurality of states comprises a state of “don't care”. The first set of subconditions is approximately matched against the second set of subconditions. The first set of subconditions is compared against the second set of subconditions. A matching criterion is determined to be met based on a result of the matching. Information indicating that the second set of subconditions is at least an approximate match for the first set of subconditions is output.

Abstract: A method for a multi-channel search includes receiving a specific post selection submitted in a first channel and query text associated with the specific post in the first channel, where the query text includes one or more words for performing a query evaluation. The method receives a query location which includes a plurality of channels for performing the query evaluation. Responsive to extracting one or more ranking factors from the specific post selection, the method performs the query evaluation at the query location to collect a plurality of potential matching posts based on the one or more ranking factors. The method reorders the plurality of potential matches according to a plurality of determined scores for the plurality of potential matches. The method displays two-dimensional search results based on a timeline and channel relevancy, where the plurality of channels is ordered according to channel relevancy compared to the first channel.

Abstract: A data storage system has multiple tiers of data storage including an upper tier having a lower access latency and a lower tier having a higher access latency. A storage controller of the data storage system receives, via an interface, an access request of a workload for a target file system object, where the target file system object has an associated temperature. In response to the access request for the target file system object, the storage controller accesses the target file system object in the data storage and conditions update of the associated temperature of the target file system object based on at least one of a set including the interface and the workload. The storage controller distributes a collection of file system objects including the target file system object among the multiple tiers based on respective heats of file system objects in the collection.

Abstract: Disclosed is a system, method, and computer program product to efficiently process multi-set operations in a database system. An approach is described to perform a group-by operation with a counter to efficiently process such queries. Techniques are described to optimize multi-set operations into regular-set operations.

Abstract: Enabling scripting language commands to backup/restore databases is described. A system outputs, to a user interface, a backup/restore option for a database. The system generates scripting language commands based on a selection of the backup/restore option received from the user interface. The system outputs, to the user interface, the scripting language commands based on the selection of the backup/restore option. The system enables a scripting language system to execute the scripting language commands based on the selection of the backup/restore option.

Abstract: An approach for implementing function semantic based partition-wise SQL execution and partition pruning in a data processing system is provided. The system receives a query directed to a range-partitioned table and determines if operation key(s) of the query include function(s) over the table partitioning key(s). If so, the system obtains a set of values corresponding to each partition by evaluating the function(s) on a low bound and/or a high bound table partitioning key value corresponding to the partition. The system may then compare the sets of values corresponding to different partitions and determine whether to aggregate results obtained by executing the query over the partitions based on the comparison. The system may also determine whether to prune any partitions from processing based on a set of correlations between the set of values for each partition and predicate(s) of the query including function(s) over the table partitioning key(s).

Abstract: The present application discloses a data read and write method and a distributed storage system. A specific implementation of the method includes: receiving, from a client, by a shard server, a processing request on shard data, the processing request comprising a data identifier of the shard data; processing the processing request based on a hash table pre-loaded in a memory and indicating a correspondence between the data identifier of the shard data and a data index to obtain a processing result; and sending the processing result to the client.

Abstract: User devices are used to access data ranging from calendar items to Internet searches. A unified search interface provided by a unified search module enables a user of the user device to search data associated with one or more applications across applications on the user device as well as data in remote locations, such as on a server via a network connection. The unified search module may be provided as part of the operating system module, and accessible without special configuration of the applications.

Abstract: Disclosed is a data deduplication method for an edge computer. The method is performed in a key-value store, and may include receiving a compaction request occurred from the key-value store to a metadata layer, checking whether deduplication for removing duplicated data is required when compaction of a metadata file is performed in response to the received compaction request, and removing the duplicated data by checking whether the deduplication is required.

Abstract: This disclosure relates generally to decentralized storage and more particularly to method and system for blockchain based decentralized storage with dynamic data operations. Conventional decentralized storage are limited in capacity thereof to enable dynamic data operations on the sectors stored at them. In an embodiment, the disclosed method and system enabled dynamic data operations such as modification, insertion, and deletion on the stored sectors by leveraging blockchain to achieve publicly verifiable fully stateless Provable Data Possession. Moreover, the disclosed system enables data integrity in decentralized storage with dynamic operations using scheme based on Merkle hash tree and blockchain to provide a transparent verification framework with high detection probability of malicious hosts.

Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media for dynamically augmenting relevance rankings using data from external ratings sources.

Abstract: Database-aware snapshotting is disclosed. It is determined that a first snapshot of a database having a plurality of shards should be taken. Each shard has a corresponding snapshot sidecar container of a plurality of snapshot sidecar containers. A consensus state among the plurality of snapshot sidecar containers that the first snapshot should be taken is determined. A snapshot controller is directed to take the first snapshot of the database, the first snapshot generating a shard volume snapshot for each shard of a plurality of shards. Subsequent to the snapshot controller taking the first snapshot of the database, each snapshot sidecar container is informed to allow activity on the corresponding shard.

Abstract: A method may include obtaining multiple electronic documents and multiple topics associated with the electronic documents. The method may further include determining a similarity between a first topic and a second topic. The first topic may be associated with a first set of electronic documents. The method may further include refining the multiple topics based on the similarity between the first topic and the second topic by associating the first set of the electronic documents with the second topic and removing the first topic from the multiple topics. The method may further include building a document-classifier model by applying machine learning to at least one electronic document associated with each of the refined topics. The method may further include obtaining an electronic document and classifying the electronic document into one of the refined topics using the document-classifier model.

Abstract: The systems, methods, and devices of the present disclosure may provide, among other features, high-performance, interactive geographical and/or data object map capabilities in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. In various embodiments, an interactive geographical map display system may enable rapid and deep analysis of various objects, features, and/or metadata by the user by aggregating and clustering large sets of data into aggregate values and clusters. The user can select various clusters, via the user interface, to interact with the data, clusters, and map.

Abstract: A DBMS query-optimization module receives a corpus of training data that contains data-access requests, such as SQL queries. Each request specifies data to be accessed but does not specify a query plan that the database should use to generate the requested data. The module identifies, in each received request, parameters, such as join methods and access methods, that can vary among query plans; and variables that cannot be assigned values until the query is actually processed. The system generates a set of queries, each of which implements a distinct query plan, that specify every viable permutation of values of the parameters and of the variables. The generated queries are added to the received corpus, which is forwarded to a machine-learning module in order to train the query-optimizer to select query plans that incur the lowest resource costs when servicing a particular type of query.

Abstract: Methods and systems for coordinated data collection through one or more vehicles. The methods and systems can include presenting a data request for sensor data to one or more vehicles, receiving data samples from the vehicles, selecting a target data sample from the data samples, creating a selection range using the target data sample, transmitting the selection range to the vehicles to create a selected data set, identifying excluded data for deletion, and receiving the selected data set from the vehicles to respond to the data request.

Abstract: A method, a device, and a computer apparatus for merging regions of a HBase table are provided. The method includes acquiring attribute information of HDFS files corresponding to each region in a plurality of regions in the HBase table, where the attribute information of the HDFS files corresponding to one region includes storage space occupied by the files corresponding to the one region, and performing merging processing on every two adjacent regions in the plurality of regions at least according to the storage space occupied by the files corresponding to each region in the plurality of regions. Performing the merging based on the storage space occupied by the files corresponding to the regions in the embodiments of the present disclosure may be beneficial for improving the precision of merging two adjacent regions.

Abstract: In order to facilitate entity resolution, systems and methods include a processor receiving first records associated with one or more entities, and second records associated with the one or more entities. The processor generates candidate pairs based on a similarity between first entity data and second entity data. The processor generates features for each candidate pair based on similarity measures between the first entity record and the second entity record. The processor utilizes a scoring machine learning model to determine a match score for each candidate pair based on each feature. The processor determines clusters of candidate pairs based on the match score of each feature for each candidate pair. The processor merges records of candidate pairs of each cluster into a respective entity record. The processor determines an entity associated with each entity record and updates an entity database with the entity record.

Abstract: This disclosure relates to increasing performance of database queries. A proxy server receives an input query string and a parameter value for first parameter name in the query string. The proxy server determines a second parameter name based on the parameter value and different to the first parameter name. The proxy server then determines an output query string based on the input query string. The output query string comprises a filter clause with a field name and a second field value, the second field value of the output query string being based on the second parameter name. The proxy server finally sends the output query string to a database management system to cause the database management system to execute a database query using an execution plan based on the second parameter name in the output query string.

Abstract: A system and method may aggregate into a data structure property information from multiple databases, e.g., from all records included in those databases, and upon selection of any subject property or a characteristic thereof curates the often imperfect and discrepant property information to create suggested values. Similarly, the system and method may perform an on-the-fly evaluation of any characteristic of a selected record, when the property information for that characteristic includes an unlikely value, by triggering from the data structure a dynamic extraction of property information corresponding to a subject property of the selected record, where the dynamic extraction further generates and compares a suggested value to the unlikely value.