Abstract: A method, system and computer program product for clustered join graph generation based upon a log of previously executed database queries includes loading into memory of a computer, a log of a set of database queries previously executed against data in a database of the database management system, sequentially parsing each of the queries in the log to identify different semantically characterizable components of each of the queries, generating a join graph for each of the queries from corresponding ones of the components, clustering different generated join graphs according to semantic commonalities so as to form different clusters of join graphs, each for a different semantic commonality, combining the generated join graphs for each cluster into a combined join graph for the corresponding cluster and adding each of the combined join graphs to a set of join graphs in a data model for the data in the database.

Abstract: Disclosed are techniques for automating records related to devices coupled to a network, such as servers, clients and memory banks. The fingerprint-based configuration typing and classification described herein may identify a fingerprint for a first device located on a network, the first device having a plurality of hardware components and the fingerprint generated based on a combination of at least two hardware components of the first device. The fingerprint is assigned to the first device. If the device does not have a first identifier assigned to it that identifies the plurality of hardware components, the fingerprint is compared to a plurality of stored fingerprints, with at least some of the stored fingerprints having a respective identifier. If the fingerprint matches one of the plurality of stored fingerprints and that stored fingerprint has an identifier associated therewith, the identifier associated with the stored fingerprint is assigned to the first device as the first identifier.

Abstract: The present application is directed to techniques and processes for using various types of data to generate criminal statistics associated with a geographic area. For instance, a system may store first criminal statistics for a first geographical area. The system may further store image data generated by an electronic device and information describing the image data. Next, the system may determine a second geographic area for generating second criminal statistics, where at least a portion of the first geographic area is located within the second geographic area. The system may then determine that at least a portion of the first criminal statistics occurred in the second geographic area and the electronic device is located in the second geographic area. Based on the determinations, the system may generate the second criminal statistics, where the second criminal statistics includes at least a portion of the first criminal statistics and the information.

Abstract: In one aspect, provenance-based replication includes assigning a GUID to a first snap tree of a first storage array and another GUID to a second snap tree of a second storage array. The trees are peers of each other with respect to at least one volume replicated between the arrays. For each volume in the first array that is replicated to a volume in the second array, an aspect includes assigning a volume pairing identifier common to both volumes. Upon determining data for a volume (V1) in the first array has been lost/corrupted, an aspect includes identifying the peer tree from the GUID and using the pairing ID of V1 to search the peer tree for a volume (V2) in the second array, retrieving data for V2, computing a delta between the data of V1 and the data of V2, and reconstructing the lost/corrupted data for V1 using the delta.

Abstract: A software application may have access to: (i) an identification condition that indicates a first subset of configuration-element attributes that can be used to identify configuration elements, and (ii) an exception indicating a second subset of the attributes that a module does not support. The software application may be configured to: based on the identification condition and the exception, search representations of configuration elements in a persistent storage in attempt to find a matching representation that characterizes information from the module, where the matching representation is found when one of the representations and the information from the module contain identical values for all of the attributes in the first subset excluding those also in the second subset; based on the search, determine that the matching representation is not found; and write, to the persistent storage, a new representation specifying values for attribute(s) according to the information from the module.

Abstract: A parallel database system processes database queries invoking a user defined function (UDF). The database query is specified in a database query language, for example, the structured query language (SQL) and the UDF is specified in a programming language different from the database query language, for example, C/C++. The UDF may include multiple phases. The parallel database system generates optimized code for the UDF. The parallel database system includes a leader node and a plurality of compute nodes. The database query processes one or more database tables such that each compute node processes a slice of each database table. The leader node sets up a global context structure and provides it to each compute node. The global context may be shared across multiple executions of the query. The UDF may be used for efficient execution of extraction, transformation, and loading of data from external systems.

Abstract: The subject technology determines, using a stream object provided by a network-based database system separate from an external system, a set of offsets of each shard of a set of shards, the set of offsets being determined by executing a user defined function (UDF) included in the stream object, the stream object and the UDF being implemented in a particular programming language different than a database query language. The subject technology identifies an operation to perform on the set of shards. The subject technology, based on the set of shards and the set of offsets, performs, using the UDF included in the stream object, the operation on an external data source hosted by the external system. The subject technology increments a property indicating a different version of the stream object after performing the operation on the external data source, the property being included in the stream object.

Abstract: A method for managing semantic information on an M2M/IoT platform is provided. The method for managing semantic information according to an embodiment of the present invention stores semantic data in the first attribute of an M2M resource and updates a part of the semantic data stored in the first attribute. Accordingly, efficient management of semantic information on an M2M/IoT platform is possible, and particularly a partial update of the semantic information can be performed.

Abstract: A technique for performing writes in a storage system that supports data compression tests incoming writes to determine whether the amount of data to be written is less than a predetermined threshold. If so, the storage system avoids compression and stores the amount of data as received without compressing it. If not, the storage system performs compression and stores the incoming data as a compressed extent.

Abstract: Embodiments are provided for updating a playlist that has been added to a playback queue in response to changes to the playback queue. The playback queue may be associated with a zone of a network media system such that items in the playback queue are to be rendered by the zone. The playlist may include one or more items playable by the zone, and may be stored separately from where the playback queue is maintained. Embodiments are also provided for updating a playback queue in response to modifications to a playlist included in the playback queue.

Abstract: A system, a method, and a computer program product for performing deduplication of data using a scalable deduplication grid are disclosed. A listing of a plurality of zone stamps is generated, where each zone stamp represents a zone in the plurality of zones in a data stream. The listing contains a logical arrangement of the plurality of zone stamps obtained from each storage location and being accessible by a plurality of servers. A first zone stamp in the listing is compared to a second zone stamp in the listing. The first and second zones are delta-compressed based on a determination that the first zone stamp is substantially similar to the second zone stamp. A server is selected to perform the comparison and delta-compression.

Abstract: In one aspect, there is provided a method. The method may include adding a tuple phrase to a phrase index as part of a lazy creation of the phrase index. The adding may include adding the tuple phrase to a dictionary mapped to the phrase index, adding to the phrase index a document identifier and a positional information for the tuple phrase, and adapting a first threshold and a second threshold value, the first threshold representing a threshold lower estimate of query processing burden associated with a least burdensome tuple phrase in the dictionary and the second threshold representing a top estimate of query processing burden associated with a most burdensome tuple phrase in the dictionary. The method may further include sending a query response including a generated query result corresponding to the tuple phrase.

Abstract: A method and system for improving an Internet based search is provided. The method includes generating an intent domain associated with a subject based intent classification. An unstructured data analysis process is executed with respect to a content corpus being associated with the subject based intent classification and a search phase entered in a search field of a graphical user interface with respect to a domain specific search query for specified subject matter. In response the subject based intent classification is determined to be associated with the search query and the subject based intent classification is compared to search results data. A subset of search results of the search results data correlating to the subject based intent classification is determined and ranked resulting in a ranked list. The subject based intent classification and the ranked list are presented to a user.

Abstract: Disclosed is a smart factory platform for processing data obtained in a continuous process including a first process and a second process following the first process. The smart factory platform includes a distributed parallel processing system including at least one processing unit that generates mapping data by mapping a process identification (ID) to collection data collected from the continuous process and sorts the mapping data to generate sorting data, the process ID defining a process where the collection data occurs and the sorting data being generated for association processing between pieces of collection data collected from different processes; and a big data analysis system storing the sorting data with respect to the process ID.

Abstract: A concept discovery method, system, and computer program product include preparing a concept index for concepts built over a set of input data having input terms, building a vector representation of the concepts in the input data, receiving a set of query terms as an additional input, mapping the set of query terms to the concepts in the concept index, calculating at least one of a co-occurrence score for each of the concepts in the concept index by measuring their frequency of co-occurrence with the input terms' concepts and a similarity score for each of the concepts in the concept index by measuring the similarity of their vector representations according to a vector similarity measure, and ranking the concepts with respect to their relevance to the input terms by the at least one of the co-occurrence score and the similarity score.

Abstract: Methods and systems for topology-based clinical data mining are provided. An example system includes a pre-processing module to process the clinical datasets to generate a table of outcomes and a table of predictors of trial subjects. The system includes a graph construction module to generate metric graphs based on the table of outcomes. The metric graphs include nodes representing the subjects and edges selectively connecting the nodes according to pre-determined criteria. The graph construction module may select a graph of interest from the metric graphs and generate a compressed version of the graph of interest. The system may further include an interactive visualization module to display a graphical representation of the graph of interest or the compressed version, receive selection of groups of the trial subjects, automatically highlight groups of related subjects, and perform, using the table of predictors, a statistical analysis of predictors of subjects within the selected groups.

Abstract: Systems, devices, instructions, and methods are provided for a computing device comprising a display screen, with the computing device configured to display on the display screen a content feed interface for communication cells for a plurality of user accounts associated with a first user account, and at least one high-signal suggestion cell of a user account not associated with the first user account. Each of the communication cells is associated with a communication from a corresponding user account of the plurality of user accounts and a direct user interface target area for display of one or more content elements. The high-signal suggestion cell is associated with a set number of actionless impression displays within the content feed interface before the high-signal suggestion cell is removed from the content feed interface.

Abstract: The subject technology determines a set of shards corresponding to an external data source accessible via a network, the external data source being hosted by an external system separate from a network-based database system. The subject technology determines, using a stream object, a set of offsets of each shard of the set of shards. The subject technology identifies an operation to perform on the set of shards, the operation comprising a read operation or a write operation. The subject technology, based on the set of shards and the set of offsets, performs the operation on the external data source.

Abstract: A computing device is configured to identify a concept of a good or service for an unmet market potential. A Global User Search Data file (GUSD) comprising information related to a search object is read. A morpheme combination in in the search object from the GUSD is identified. The morpheme combination is compared to a first set of pre-existing terms. A first score is assigned to the search object based on the comparison, wherein a higher first score is assigned if the morpheme combination is not found in the first set of pre-existing terms. An un-successfulness of the search object is determined and a second score is assigned, wherein a higher second score is assigned the more un-successful the search object is. An aggregate of all the scores for a search term is compared to a predetermined threshold. If the aggregate score is above the predetermined threshold, the search term is identified as a concept of a good or service for an unmet market potential.

Abstract: Aspects of the present disclosure involve, a customizable system and infrastructure which can used to retrieve and scout metadata on a distributed file system for data management. In one embodiment, a system is introduced which can be used to scout metadata from a distributed file system using an isolated node which can enable the determination and response to customized queries. The customizable system can include a NameNodeAnalytics module which can stream, filter, and process client queries without locking the NameNode in the distributed file system. In another embodiment, the analytics distributed file system can communicate with a streaming API and other time-series module for the reporting and visual representation of the metrics obtained.