Abstract: The present disclosure involves systems, software, and computer implemented methods for managing database query plans with dynamic conditions. One example method includes receiving a request to process a query based on at least one dynamic condition. A serialized abstract query plan is identified, deserialized, and converted into a query optimizer tree. A condition provider procedure is invoked to generate a first filter string for each view in the query optimizer tree. Comparisons are made to determine matches between first filter strings and corresponding second filter string stored in the query optimizer tree. In response to determining that a first filter string does not match the corresponding second filter string, query plan compilation is triggered. In response to determining that each filter string matches each corresponding second filter string, a query plan is generated based on the converted query optimizer tree and the query is executed using the query plan.

Abstract: An accelerated database management system including at least one processor including circuitry and a memory. The memory includes instructions that when executed by the circuitry cause the at least one processor to: receive an initial database query: generate a main query based on the initial database query; analyze the main query, and based on the analysis of the main query, generate at least a first sub-query and a second sub-query, wherein the second sub-query differs from the first sub-query; process the first sub-query along a first processing path to provide a first input to an execution module; process the second sub-query along a second processing path, different from the first processing path, to provide a second input to the execution module; and based on the first input and the second input received by the execution module, generate a main query result.

Abstract: In some embodiments, reducing usage of cache memory in connection with user queries may be facilitated. In some embodiments, in connection with a first query, (i) a first set of results received during a user session and (ii) a first output generated from the first set of results are stored in a session cache associated with the user session. In response to determining that a second query parameter of a second query corresponds to a first query parameter of the first query but fails to satisfy a match criterion: a cache lookup is performed on the session cache to retrieve a matching result subset of the first set of results, in lieu of retrieving the first output generated from the first set of results, where the matching result subset does not include a result corresponding to the first query parameter. A second output is then generated.

Abstract: Computer-implemented prediction methods, in accordance with various embodiments, involve storing key-value pairs each including a key tuple and an associated value in a data store, building a prediction model associated with at least a subset of the key-value pairs, and in response to receipt of a prediction query that specifies a key tuple, generating a prediction response based on the prediction model that includes a predicted value for the specified key tuple. In one example application, the key tuples each include an operation specifying a purchase and a two-part identifier specifying a customer and a product.

Abstract: A system and method for non-invasively monitoring and troubleshooting a massive parallel processing environment that may include a digital ecosystem having a data lake. The system may include a data transporter, a data ingester, a data chef, and a separate message producer at each of the data transporter, data ingester, and data chef. Log data from the message producers may be transmitted to a memory associated with a processor for organization of the log data by topic, such as a Kafka topic, into instrumentation data that may indicate performance of different portions of the system. The system may further include a message consumer, such as Kafka message consumer, to enable the presentation of the instrumentation data to be interactively displayed to a user on one or more electronic dashboards for monitoring and troubleshooting of performance issues.

Abstract: In an example embodiment, a specialized execution process for a Disk Group-By operator with at least one distinct or ordered aggregation is provided. This specialized execution process involves writing all linked lists to disk (optionally this is performed only if the memory budget is coming close to being surpassed). Initially, a separate disk partition can be created per group, but once a partition becomes too large a new partition for the group is created. A partition is considered too large if it would not be able to be loaded into memory without surpassing the memory budget. As a result, every group can have a list of one or more disk partitions attached to it. The data belonging to each group is sorted using a sorted merge from disk.

Abstract: A method, computer system, and a computer program product are provided for query management optimization in a distributed data management system. In one embodiment, at least one query is received. The query is then analyzed and related information associated with the query is obtained. When information exists in a database relating to previously executed queries similar to the received query, that information is obtained. A query execution plan is then formulated using any existing information and information relating to the similarly previously executed queries.

Abstract: An exemplary machine-learning-based method for generating a response to a natural-language query from an entity associated with an organization comprises: obtaining a sub-query from the natural-language query; determining if a cache associated with the organization stores a matching historical sub-query: if the cache stores the matching historical sub-query, retrieving a historical sub-response associated with the historical sub-query from the cache as a sub-query response; if the cache does not store any matching historical sub-query: inputting the sub-query into a cache-based enhancement machine-learning model to enhance the sub-query, wherein the cache-based enhancement machine-learning model is trained based on historical query data stored in the cache associated with the organization; and inputting the enhanced sub-query into a language model to generate the sub-query response; and generating the response to the natural-language query based on the sub-query response.

Abstract: In some implementations, a device may obtain the relational statement associated with a query of a database. The device may parse the relational statement to identify one or more temporary queries included in the relational statement. The device may modify the relational statement to include segment indicators for respective segments of the relational statement associated with respective temporary queries from the one or more temporary queries. The device may execute the relational statement. The device may determine, based on executing the relational statement and based on the segment indicators, one or more execution performance parameters for each segment included in the relational statement, wherein the one or more execution performance parameters indicate performance levels of the one or more temporary queries. The device may store the one or more execution performance parameters for each segment.

Abstract: Compiling optimized database statements including receiving, by a query compiler from a client computing system, a state specification of a graphical user interface in response to a user manipulating the graphical user interface on the client computing system, wherein the state specification is in a standard file format and describes modifications to a plurality of visual elements of the graphical user interface; compiling, by the query compiler, a database statement from the state specification such that a limit clause within the database statement is processed by a database before at least one join clause; and sending, by the query compiler, the optimized database statement to a database on a cloud-based data warehouse.

Abstract: An embodiment may receive observed data from a monitored system. The embodiment may receive a request to generate a contextual report based on the observed data. The embodiment may identify a relevant persona corresponding to the request based on a series of linguistic cues. The embodiment may identify a list of suitable keywords based on the identified relevant persona. The embodiment may generate a persona-based contextual report for the observed data based on the identified relevant persona and the list of suitable keywords.

Abstract: Various embodiments can implement a multi-system or node architecture that can be deployed on-demand and augment existing systems with pre-configured nodes that can be installed within existing architecture. The multi-node architecture is flexible for integration into many systems and can also stand alone to provide data validation and assurance. Various embodiments of the multi-node architecture enable private and public distributed ledgers (e.g., blockchains) that enhance security, enhance confidentiality, and eliminate the need to trust the provider/hosts of the data validation information and/or the hosts of the confidential information.

Abstract: A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: receiving a new notification; determining, using a binary search algorithm, a number of one or more notifications, wherein an interval of the binary search algorithm comprises a time period between a reclamation pointer and an ingestion pointer; when the number of the one or more notifications is greater than a maximum number of notifications, removing, from a central data store, at least one notification of the one or more notifications; and storing the new notification in the central data store. Other embodiments are described.

Abstract: A hybrid query execution plan is generated for executing queries on database systems implementing a columnar cache. A hybrid query execution plan combines a query execution plan for querying and retrieving data from a columnar cache and a base table. A columnar cache stores cached data in column-major format, which is logically represented by the database management system in row-major format. A database management system as described herein can scan valid blocks of column data according to a column scan operation. The system can identify invalidated blocks and execute a different sub-execution plan of the hybrid query execution plan to scan corresponding rows in tables corresponding to the location of data for the invalidated blocks.

Abstract: A technique partitions a user's original query into plural smaller component queries, each of which has a common part and an instance-specific part. The technique distributes the component queries to plural processor instances of a processor. The plural processor instances transform the respective component queries into query-component responses by acting in parallel, independent of each other. The technique generates a final response based on the query-component responses, e.g., by assembling the component-query responses into the final response. The technique reduces latency because the processor instances work on parts of the user's original query at the same time, rather than as a single stream of consecutive tokens. The plural processor instances have access to a shared cache memory, and utilize relevant data that has been computed in response to previous queries.

Abstract: A method for determining a spatial relationship, includes: obtaining a calculation request for the spatial relationship, the calculation request including a polygonal region and a set of report points; determining a plurality of first coded values corresponding to the polygonal region; determining a plurality of second coded values corresponding to the set of report points and a group of report points corresponding to each of the plurality of second coded values; determining a second coded value matching each of the plurality of first coded values by sorting and matching the plurality of first coded values and the plurality of second coded values respectively; and determining a relationship between the polygonal region and each report point in the set of report points according to a group of report points corresponding to the second coded value matching each of the plurality of first coded values.

Abstract: A system for data partitioning based on discovery of discrete partitioning information. The system can receive data sets in table format from source system. The data can be stored in the source system to be partitioned and transmitted from the source system to a target system. The system can determine a respective partitioning column for each data set. The system can determine a number of partitions. The system can determine, for each data set, a respective set of discrete values from the plurality of discrete values of the respective partitioning column. The number of the discrete values of the set of discrete values can be based at least in part on the number of partitions. The system can the discrete value sets with each other. The system can determine a final set of discrete values based at least in part on the comparison.

Abstract: A document repository may be searched for documents that are similar to a source document. Multiple queries may be generated based on a type of the source document, and the results may be combined in a unified response. User behavior may then be monitored, and implicit and explicit feedback may be gathered to evaluate the performance of the search. The gathered feedback may indicate how relevant each of the result documents are in comparison to the original source document. This feedback may then be used to adjust search parameters for the source document type, such that the performance of subsequent searches may be improved. A model may also be trained to classify implicit feedback using explicit feedback received from users.

Abstract: A query coordinator can receive a query and identify a first portion of the query to be processed by a first data processing system and a second portion of the query to be processed by a second data processing system. The query coordinator can obtain a modified query based on identifying the first portion and the second portion of the query. The query coordinator can define a query processing scheme according to the modified query and provide the query processing scheme to the second data processing system. Based on providing the query processing scheme, the query coordinator can obtain an output of the second data processing system. The query coordinator can identify a second query based on the output and provide the second query to a component of the first data processing system.

Abstract: In some implementations, a redundancy system may receive, from a log storage, a plurality of log files that were generated by a plurality of monitoring programs. The redundancy system may apply a machine learning model to the plurality of log files to detect one or more redundancies. The redundancy system may determine at least one monitoring program, in the plurality of monitoring programs, that is a candidate for removal based on the one or more redundancies. The redundancy system may transmit, to a ticket system, a command to open a ticket associated with the at least one monitoring program.