Abstract: Query integration across databases and file systems is disclosed. An example method may include streaming data managed by a first database file system for a query. The method may also include streaming data managed by a second database file system for the query. The method may also include joining the streaming data managed by the first database file system with the streaming data managed by the second database file system.

Abstract: A computer-implemented method for collecting files transmitted on a network for subsequent malware analysis is disclosed. The method comprises determining, by a sensor, that a file has been transmitted on the network; transmitting, from the sensor to an intermediate agent, the file; storing, by the intermediate agent, the file, pending a determination whether metadata of the file indicates an identical copy of the file has likely already been stored by a source collection subsystem; responsive to a determination that the file has not likely already been stored by the source collection subsystem, transmitting the file from the intermediate agent to the source collection subsystem; verifying, by the source collection subsystem, that the file has not likely already been stored by the source collection subsystem; and storing the file for future analysis.

Abstract: A method, system, and computer program product for transforming RDF quads to relational views. The method commences by receiving a named graph, the named graph comprising at least one RDF quad, and analyzing the named graph to produce analysis metadata. The method uses the analysis metadata to generate relational views. The method further comprises publishing a relational view in the form of a SPARQL query. The quality of the results can be quantitatively measured and reported by calculating a goodness score based at least in part on aspects of the relational view definitions. Several variants for transformation include generating relational view definitions formed using a named-graph strict variant, or a named-graph relaxed variant, or a named-graph agnostic variant. The transformations can form outputs responsive to characteristics or properties such as a number of classes, a number of single-valued properties, a number of nullability properties, or a number of type-uniformed ranges.

Abstract: Certain embodiments involve ranking search results from an information retrieval system using user query data to provide relevant search results to users of the information retrieval system. For example, a system determines a weight factor associated with a first user that provides a query to the information retrieval system based on a type or role of the first user. The system further determines a boost factor associated with the first user based on the weight factor and a number of consecutive search queries provided by the user. The system uses the boost factor to automatically tune a ranking algorithm to adjust a rank of a search result item resulting from a search query provided by a second user.

Abstract: A computer-implemented method according to one embodiment includes identifying a request to create a consumer within a converged system, defining the consumer within a hierarchy of consumers, where the consumer represents a function in an organization, setting a storage capacity attribute for the consumer, and conditionally defining a data volume for the consumer, based at least in part on the storage capacity attribute.

Abstract: Embodiments relate to generating database sequences in a replicated database environment. An aspect includes providing a group of nodes each hosting an instance of a replicated database, with one node in the group elected as a master node responsible for generating and distributing values for auto-generated values in a column or row of the replicated database. Another aspect includes dividing, by the master node, a sequence space of possible auto-generated values for the column or row into sub-ranges and assigning a sub-range to a particular node in the group of nodes. Another aspect includes distributing, by the master node, values of the assigned sub-range to a particular node of the group of nodes.

Abstract: Methods, including computer programs encoded on a computer storage medium, for indexing native application data. In one aspect, a method includes: receiving a partial search query, determining that the partial search query is classified as a symptom query, in response to determining that the partial search query is classified as a symptom query, identifying one or more differential diagnosis terms, generating a suggested search query based at least on (i) the partial search query, and (ii) one or more of the differential diagnosis terms, and providing the suggested search query in response to the partial search query.

Abstract: Real-time synchronization of data between disparate cloud data sources; local database receives data from various sources then supplies data to various destinations. A steady state database synchronization software module monitors local database for changes to data, reconciles any local change with changes to the same data in remote database, forwards reconciled data to a destination database, and monitors messages announcing that data in remote database has changed. Finally, the failsafe database synchronization software module polls the remote database periodically for changes, compares changes made to remote data and local data, outstanding changes are applied to local and remote databases as determined.

Abstract: The disclosed computer-implemented method for automatically linking data analytics to storage may include (1) identifying a request to provision storage for a data analytics task, (2) collecting information relating to the data analytics task, the information comprising at least one of a data type of the data being used as input for the data analytics task and a characteristic of the data analytics task, (3) using a self-service provisioning tool to automatically compute, based on the collected information, a suggested type and size of data storage for the data analytics task, and (4) automatically provisioning data storage for the data analytics task based on the suggested type and size. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A filesystem can be shared between containers. For example, a computing device having a host filesystem can launch a first container from an image file. Launching the first container can include creating an initialization directory for the first container on the host filesystem. The initialization directory can include a filesystem to be shared between containers. Launching the first container can also include creating a first filesystem directory for the first container on the host filesystem and mounting the initialization directory to the first filesystem directory. The computing device can also launch a second container from the image file. Launching the second container can include creating a second filesystem directory for the second container on the host filesystem and mounting the initialization directory to the second filesystem directory to enable the second container to access the filesystem.

Abstract: A database system may store data at a primary database and replicate the data to one or more disaster recover (DR) databases. The database system may determine which DR database to use for data replication based on an identifier of the data. A method for data storage may include receiving and storing a first data block and a second data block at a first database server. The method may further include transmitting a first backup request for the first data block to a second database server based on an identifier of the first data block and transmitting a second backup request for the second data block to a third database server based on an identifier of the second data block.

Abstract: A system for backup comprises an input interface configured to receive a request to back up a file. The system for backup additionally comprises a processor configured to determine whether the file comprises an indicator to back up without deduplication, and in the event the file comprises an indicator to back up without deduplication, process the file for deduplication storage without deduplication.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset having a data format into a dataset ingestion controller configured to form a collaborative dataset, interpreting data of the dataset against data classifications at an inference engine to derive at least an inferred attribute, associating the data with annotative data identifying the inferred attribute, and converting the dataset at a format converter to form an atomized dataset.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset having a data format into a dataset ingestion controller configured to form a collaborative dataset, interpreting data of the dataset against data classifications at an inference engine to derive at least an inferred attribute, associating the data with annotative data identifying the inferred attribute, and converting the dataset at a format converter to form an atomized dataset.

Abstract: A method for indexing semantic, non-transitory, computer-stored data comprising the following steps: storing the data in a database; representing the data in a structured framework having at least three elements derived from an ontology; expressing each element as a hierarchical-index value based on an ontology such that semantic information is embedded therein; combining the elements in a multi-dimensional index; and converting the multi-dimensional index into a one-dimensional index.

Abstract: A system for determining a response to a query includes a receiver to receive a query along with a plurality of potential responses to the query. A detector detects a topic and a type of the query based on information extracted from text and structure. Further, a selector selects at least one of a plurality of techniques for processing the query and the plurality of potential responses, based on the topic and the type of the query. An obtainer obtains an answer by execution of each of the selected techniques for processing the query and the plurality of potential responses along with an associated confidence score. A determinator determines one of obtained answers as a correct response to the query, based on a comparison between confidence scores associated with the answers.

Abstract: An enhanced resource reconciliation process is disclosed to examine the metadata hierarchy of unidentified instances of configuration objects within a particular “data partition” (sometimes called a dataset) of an enterprise configuration management database (CMDB) and perform reconciliation against a target dataset, such as a golden, i.e., production, dataset. The enhanced reconciliation process could identify against instances in the production dataset that are of the same class as the unidentified instance—as well as instances that come from any “candidate” classes. Candidate classes could consist of, e.g., classes upstream or downstream from the unidentified instance in the metadata hierarchy.

Abstract: In one embodiment, a method for providing alternate keys in a keyed index includes creating a first base record in a keyed index of a database, the first base record including a first unique key and a first data record, wherein the first data record includes at least one sub key and at least one first value, each sub key being correlated with a different one of the at least one first value in a sub key/value pair, and creating one or more alternate key records in the database, each of the alternate key records including one of the at least one sub key which is correlated with the first base record and the first unique key of the first base record. The database adheres to virtual storage access method (VSAM) in some approaches. In other approaches, a number of alternate key records created is equal to a number of first sub keys in the first data record.

Abstract: A system for managing database logging, the comprises a processor; and a user task executing in a database server process and executable by the processor, the user task to: receive in a database management system on a database server, a command to manipulate a portion of a database managed by the database management system; obtain a lock on the portion of the database; create a first log record in a first private log cache associated with the user task, the first log record recording a data manipulation to the portion of the database; enqueue the first log record to a queue; and release the lock on the portion of the database after copying the first log record to the queue.

Abstract: A system and method for processing source data, which includes a translation processor configured on a server to translate a stream of source data received at the server into a stream of formatted data types based on one or more of parameter definitions for the source data and new parameter information for the source data having an unknown data type. The source data can be received at the server from multiple sources and the data format may not be consistent from one source to another. An analytics processor on the server can be configured to operate on the out-of-tolerance data type to perform one or more of trend data analytics, associated data analytics and preventative action analytics.