Systems and techniques for searching multiple data sources are described herein. Users may specify searches of multiple data sources to occur on a periodic basis. The searches may be configured to search time or date ranges that have not previously been searched. A user may select the data sources of interest and specify search terms, review and edit previously created searches, and review results of searches. The system automatically performs the specified searches, and notifies the user and/or a team of the user each time new results are found. The system may efficiently search the data sources by storing previous search results and comparing the previous results to current search results to identify new search results.

A system including a data center hosting a representational state transfer (REST) server in communication with a client network, wherein the REST server includes a GraphQL schema describing tables and fields of a communicatively coupled database. The REST server is configured to: receive a request that includes a GraphQL query; open a streaming connection to the client network; and output a beginning of a response via the streaming connection. The REST server is also configured to process the GraphQL query based on the GraphQL schema to generate a GraphQL result, and to output the GraphQL result in a body of the response via the streaming connection. The REST server is further configured to output an end of the response via the streaming connection, such that the response is correctly formatted in JavaScript Object Notation (JSON).

Filtering apparatus and methods associated with filtering large time series of data are described. A filtering process containing recursive dependencies can be organized as a series of computational tasks, at least some of which can be performed in parallel. Because of parallel execution of some tasks, an amount of time for filtering large time series of data with a filter exhibiting recursive data dependencies can be reduced significantly.

Multidimensional data analysis applications, including OLAP applications, simultaneously aggregate across many sets of dimensions. However, computing multidimensional aggregates is a performance bottleneck for OLAP data analysis applications. In order to improve the speed of interactive analysis, OLAP databases often precompute aggregates at various levels of detail and on various combinations of data attributes. However, the cost and speed of precomputation influences how frequently the aggregates can be brought up-to-date. Systems and methods disclosed herein provide graph based multidimensional analysis processing without pre-aggregating or precomputing the data along dimensional hierarchies, and by providing the results to the end user on-demand. Since preaggregation or precomputation of data along dimensional hierarchies is not necessary, implementations allow the end user to perform data analysis as soon as the data is available.

Methods, systems, and apparatuses, including computer programs for generating and using a hash table configured to improve mapping of reads are disclosed that include obtaining a first seed of K nucleotides from a reference sequence, generating a seed extension tree having a nodes, wherein each node of the nodes corresponds to (i) an extended seed that is an extension of the first seed and has a nucleotide length of K* and (ii) one or more locations, in a seed extension table, that include data describing reference sequence locations that match the extended seed, and for each node: storing interval information at a location of the hash table that corresponds to an index key for the extended seed, wherein the interval information references one or more locations in the seed extension table that include reference sequence locations that match the extended seed associated with the node.

A computer implemented method for debugging computer instructions is provided. The method comprises using a number processors to receive a computer program, including a source code and generate a number of information records associated with a number of computer instructions in the source code, wherein at least one of the computer instructions comprises a function enclosed by a macro. The processors create a data structure based on the information records and generate an index of identifiers in the data structure based on debug information of the computer instructions, wherein the index comprises respective identifying entries for the computer instructions. The processors update information records according to the identifying entries in the data structure.

Recursive endorsements in a decentralized database minimize validation effort for a smart contract because there are fewer signatures to verify. Collected endorsements required by an endorsement policy are verified and signed by a set of trusted peers representing different organizations, the set of trusted peers being fewer than the number of endorsing peers. Prior to validation, the target transaction is submitted with all required endorsements and the signatures of the set of trusted peers. Validation is performed by verifying only the signatures of the set of trusted peers.

Systems, methods, and non-transitory storage media are provided for replication of data and/or retrieval of (replicated) data using recursive tree structure searching. For instance, a system may use one or more self join operations to expand a tree graph in fewer iterations that are taken with typical tree graph expansion methods. Once the tree graph is expanded, the system can respond to a query by providing a list of child paths of a node referenced in the query or a list of parent nodes of a node referenced in the query.

The disclosure relates to technology for mining data in a database by recursively mining a conditional frequent pattern tree (FP-tree) for frequent items of each conditional pattern base for each node in an FP-tree to obtain frequent patterns. For each branch in the FP-tree, a single-item node table (NT) is generated for which a selected one of the frequent items appears in the node of the branch. The single-item NT including a list of all of the frequent items appearing in the FP-tree and a corresponding frequent item count. For each single-item NT of each branch generated for the selected one of the frequent items, the frequent item count of each frequent item is summed in the single-item NT formed for each branch to generate a combined single-item NT, and association rules based on the frequent patterns are generated for each of the frequent items and the combined single-item NT.

A method for implementing access controls for items of data belonging to a self-describing data structure including obtaining a query definition specifying a requested item of data in the self-describing data structure, determining domains associated with the requested item, the domains including a set of items within the self-describing data structure on an execution path of a query executed according to the query definition. For each respective domain associated with the requested item, the method includes determining subdomains associated with the requested item, determining a role of the user for the respective domain, the role is associated with a set of access permissions to items of data within the domain, and generating an output corresponding to whether access to the requested item is granted based on a policy for each of the subdomains associated with the requested item and the role of the user for the domain.