Abstract: One embodiment of the invention is directed to a method for performing efficient data searches in a distributed computing system. The method may comprise, receiving a search request including a key. The key may be provided to a block-based table manager via a programming interface external to a virtual machine executing on a computer system. The programming interface may provide a translation between a first programming framework of the virtual machine and a second programming framework of the block-based table manager. Providing the key may cause the block-based table manager to conduct a search for a value corresponding to the key. The value may be provided in response to the search request. Utilizing such block-based tables may enable a data search to be performed using on-board memory of computing node operating within a distributed computing system.

Abstract: Aggregation in a computing system can include receiving, at a service node of the computing system, a first query specifying aggregation and translating the first query into a second query having a first canonical format and specifying the aggregation. The method can include forwarding the second query to a first subset of a plurality of endpoint nodes and translating, at each endpoint node of the first subset, the second query into a third query having a format executable by a data source connected to the endpoint node. The third query can specify a level of the aggregation to be performed by the data source determined based upon a processing capability of the data source. The endpoint nodes can initiate execution of the third query by the data sources and provide an aggregated result including a result from the data source(s) to the service node.

Abstract: In one embodiment, the present disclosure includes a cloud based management system controlling a plurality of automated food production systems residing at different locations. A machine learning algorithm may be used to modify recipe data to customize recipes.

Abstract: A user may submit a search query to a search engine, which may process the search query and generate a set of results. Previous actions of the user or of other users may be used to identify recommended search queries. The recommended search queries may be presented to the user along with the search results for the query. The location of the recommended search queries may be fixed, set by the user, or determined on a query-by-query basis. A user interface element operable to cause the presentation of one or more recommended search queries may be presented after a delay. After an additional or independent delay, the recommended search queries may be presented automatically. The delays may be fixed, set by the user, or determined on a query-by-query basis.

Abstract: Methods, systems, and computing platforms for data communication are disclosed. The processor(s) may be configured to electronically receive a SQL query request for a relational computer readable database having plurality of computer readable records. The processor(s) may be configured to electronically process the SQL query request with a machine learning controller based on a set of machine learning training data so as to output at least one probable smart execution plan for executing the SQL query request. The processor(s) may be configured to electronically output the at least one probable smart execution plan for executing the SQL query request to a relational database management processing module.

Abstract: Methods and systems for querying application metadata objects are provided. The method may comprise receiving a query identifying an application; executing the query against a metadata model for the application to obtain a result, the result identifying a first metadata object satisfying the query, wherein the metadata model identifies a plurality of metadata objects and hierarchical relationships between the plurality of metadata objects, and wherein the metadata model comprises information about structure and semantics of data used by the application; determining, from the plurality of metadata objects, a second metadata object referenced by the first metadata object; determining, from the plurality of metadata objects, a third metadata object that is a parent object of the first metadata object; building a directed graph including the first metadata object, the second metadata object, and the third metadata object; and providing a response including the directed graph to the query.

Abstract: Systems and methods that offer significant improvements to current content processing management systems for heterogeneous and widely distributed content sources are disclosed. The proposed systems and methods are configured to provide a framework and libraries of extensible components that together are designed enable creation of solutions to acquire data from one or more content repositories, possibly distributed around the world across a wide range of operating systems and hardware, process said content, and publish the resulting processed information to a search engine or other target application. The proposed embodiments offer an improved architecture that incorporates manager nodes and worker (processing) nodes, where worker nodes are configured to scan and process data, while manager nodes are configured to handle all allocation of work (including throttling) and control state and failover. Such an arrangement enables the system to perform with greater scalability and reliability.

Abstract: Embodiments of the disclosure provide systems and methods for identifying hierarchically related files stored in a database. According to one embodiment, this can be accomplished using a pipeline of worker applications which each use a specific table stored in the database 35 and a sequence or series of queues. Generally speaking, each worker application can read a message identifying tasks to be performed from one queue in the sequence of queues, perform those tasks using the appropriate table from the database to identify a set of files, and write one or more messages to a subsequent queue in the sequence or series of queues to pass results and/or further tasks to be performed to a subsequent worker application in the pipeline of worker applications.

Abstract: Described are methods, systems and computer readable media for computer data distribution architecture connecting an update propagation graph through multiple remote query processors.

Abstract: This document describes techniques and devices for a refined search with machine learning. These techniques improve computer-aided searches through enabling selection of search criteria used in a prior search and providing a refined search result based on that selection. Furthermore, a machine-learning component of a search engine can be altered to improve future search results based on the selection and an indication of the desirability of the refined search result.

Abstract: According to various embodiments, the Query Context Translation Engine identifies a topic of a search query history received during a current user session. The search query history in a first language. The Query Context Translation Engine identifies, in a translation table, target text that corresponds with a query in the search query history, the target text comprising at least one word. The Query Context Translation Engine obtains at least one search result based on a translation of the target text in a second language.

Abstract: Techniques are described for responding to aggregate queries using optimizer statistics already available in the data dictionary of the database in which the database object targeting by the aggregate query resides, without the user creating any additional objects (e.g. materialized views) and without requiring the objects to be loaded into volatile memory in a columnar fashion. The user query is rewritten to produce a transformed query that targets the dictionary tables to form the aggregate result without scanning the user tables. “Accuracy indicators” may be maintained to indicate whether those statistics are accurate. Only accurate statistics are used to answer queries that require accurate answers. The accuracy check can be made during runtime, allowing the query plan of the transformed query to be used regardless of the accuracy of the statistics. For queries that request approximations, inaccurate statistics may be used so long as the statistics are “accurate enough”.

Abstract: Embodiments of the present disclosure describe systems, methods, and computer program products for executing and tuning a machine learning operation within a database. An example method can include receiving a data query referencing an input data set of a database, executing a plurality of machine learning operations to generate, in view of the input data set, a plurality of output data sets each having a respective accuracy value, wherein each of the plurality of machine learning operations is executed by a processing device according to one of a plurality of unique sets of hyperparameters, selecting a first output data set of the plurality of output data sets in view of the accuracy values, and returning the first output data set in response to the data query.

Abstract: Operations include halting a runaway query in response to determining that a performance metric of the query exceeds a performance threshold. The runaway query halting system receives a query execution plan associated with a query and divides the received execution plan into one or more components. For each component, the system determines a predicted resource usage associated with executing the component. The system further determines a predicted resource usage associated with the query execution plan based on the predicted resource usage associated with each component. The system executes the query associated with the received query execution plan and compares the predicted resource usage associated with the query to a resource usage threshold. In response to determining that the predicted resource usage of the query execution plan exceeds the resource usage threshold, the system halts execution of the query associated with the query execution plan.

Abstract: The present invention relates to a system and method of selling goods or services, or collecting recycle refuse using mechanized mobile merchantry, comprising positioning, by self-propelling, at least one of a mechanized mobile merchantry within a geographical boundary, allowing interaction with consumers, and effectuating selling of goods or services, or collection of recycle refuse with consumers. Other exemplary embodiments can include signaling a mechanized mobile merchantry with a consumer's mobile device to direct the merchantry to self-propel to the consumer's location, and utilizing usage logs and algorithms to optimize functionality of a fleet of merchantry and reposition the merchantry, as necessary, within a geographical boundary, to increase sales and consumer convenience.

Abstract: Methods and apparatus are provided for using machine learning to estimate query resource consumption in a massively parallel processing database (MPPDB). In various embodiments, the machine learning may jointly perform query resource consumption estimation for a query and resource extreme events detection together, utilize an adaptive kernel that is configured to learn most optimal similarity relation metric for data from each system settings, and utilize multi-level stacking technology configured to leverage outputs of diverse base classifier models. Advantages and benefits of the disclosed embodiments include providing faster and more reliable system performance and avoiding resource issues such as out of memory (OOM) occurrences.

Abstract: A device may receive source code from a source data structure, and may receive information associated with a target data structure. The device may analyze the source code to extract statements, and may utilize natural language processing on the statements to identify functions and keywords associated with the source data structure. The device may train a machine learning model with the functions and the keywords to generate a trained machine learning model, and may process the information associated with the target data structure, with the trained machine learning model, to transform a source query to a target query compatible with the target data structure. The device may process the target query, with a neural network model, to generate an optimized target query, and may cause data from the source data structure to be migrated to the target data structure based on the optimized target query.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining query refinements using search data. In one aspect, a method includes receiving a first query and a second query each comprising one or more n-grams for a user session, determining a first set of query refinements for the first query, determining a second set of query refinements from the first set of query refinements, each query refinement in the second set of query refinements including at least one n-gram that is similar to an n-gram from the first query and at least on n-gram that is similar to an n-gram from the second query, scoring each query refinement in the second set of query refinements, selecting a third query from a group consisting of the second set of query refinements and the second query, and providing the third query as input to a search operation.

Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.

Abstract: A method, a computer program product, and a computer system co-assign operators to service an incident with a first operator educating a second operator of skills used in servicing the incident. The method includes determining a type of incident and determining a command group used for the type of incident according to a first mapping based on historical resolutions of historical incidents. The method includes determining the first operator for co-assignment according to a second mapping based on successful historical resolutions of historical incidents by the first operator. The method includes determining the second operator for the co-assignment according to the second mapping that further maps the command group and the second operator based on a lack of experience in using the command group. The method includes co-assigning the incident to the first operator and the second operator.

Abstract: Various examples are directed to systems and methods optimizing database queries. A database management system may receive a first query comprising a plurality of query expressions. The database management system may determine that a first expression of the first query is nullable and that the first expression is null preserving. The database management system may generate optimized query code for the first query. The optimized query code may comprise a first code segment and a conditional jump instruction. The first code segment that, when executed by a processor, may cause the processor to perform operations comprising determining a value of the first expression. The conditional jump instruction may, when executed by the processor, cause the processor to perform operations comprising: skipping execution of at least a portion of the first code segment and returning null for the first expression.

Abstract: A database engine includes one or more computing devices, each having one or more processors and memory. The memory stores programs configured for execution by the processors. The database engine receives a database query from a client, and parses the database query to build a query operator tree. The query operator tree includes a plurality of query operators. The database engine performs one or more optimization passes on the query operator tree, including a deduplication optimization pass, to form an optimized execution plan. The deduplication optimization pass includes determining that a first query operator is equivalent to a second query operator during a traversal of the query operator tree, and replacing the second query operator with a link to reuse results from the first query operator. The database engine executes the optimized execution plan to retrieve a result set from the database and returns the result set to the client.

Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.

Abstract: A system and method for creating and editing graph schema data structures in a collaborative, real time graphical editing environment is disclosed. The system and method further operates to integrate external sources of data as components of the graph schema. The system and method outputs definition files for the graph schema data structure and mapping files.that enable the population of a graph database.

Abstract: Systems, methods, and computer-readable media for pinning query execution plans are described. A database system may obtain a query, and determine a organization identifier and/or user identifier associated with the query. The database system may identify an optimized plan among a set of query plans that correspond with the query, and may generate a query execution plan based on the query and the optimized plan. The database system may determine a pinned plan that is associated with the optimized plan, and may generate a query execution plan based on the pinned plan when the pinned plan is associated with the optimized plan and corresponds with the organization identifier and/or the user identifier. The database system may generate a query execution plan using optimization functions when the pinned plan is not associated with the pinned plan, or the organization identifier and/or the user identifier. Other embodiments may be described and/or claimed.

Abstract: The present invention relates to optimized access of a database. Herein are techniques to accelerate execution of any combination of ad hoc query, heterogenous hardware, and fluctuating workload. In an embodiment, a computer receives a data access request for data tuples and compiles the data access request into relational operators. A particular implementation of a particular relational operator is dynamically selected from multiple interchangeable implementations. Each interchangeable implementation contains respective physical operators. A particular hardware operator for a particular physical operator is selected from multiple interchangeable hardware operators that include: a first hardware operator that executes on first processing hardware, and a second hardware operator that executes on second processing hardware that is functionally different from the first processing hardware.

Abstract: Systems and methods are provided for automatically orchestrating the handling of events through a processing pipeline without limitation (or without a substantial limitation) as to the size of the event payload associated with the event. The event pipeline system stores event payloads in data stores and generates notifications regarding the events. The notifications may be placed into event streams for handling by various processing components of the event pipeline system. The processing components may receive notifications or events that they are to process, and may separately access event payloads from the data stores. The processing components may generate and save processed event payloads to the data stores in a streaming fashion such that the computing resources of the processing components do not limit (or substantially limit) the size of the event payloads that the processing components may handle.

Abstract: In one aspect, a method includes generating a design space for a peptide for an application. The generating includes identifying sequences for the peptide, and updating the sequences by determining, for each of the sequences, a respective set of activities pertaining to the application. The updating produces updated sequences each having updated respective activities. The method includes generating, based on the updated sequences, a solution space within the design space. The solution space includes a target subset of the updated sequences. The method includes performing, using a machine learning model to process the solution space, trials to identify a candidate drug compound that represents a sequence having a level of activity that exceeds a threshold level, and transmitting information describing the candidate drug compound to a computing device.

Abstract: Techniques are described herein for building a framework for declarative query compilation using both rule-based and cost-based approaches for database management. The framework involves constructing and using: a set of rule-based properties tables that contain optimization parameters for both logical and physical optimization, a recursive algorithm to form candidate physical query plans that is based on the rule based tables, and a cost model for estimating the cost of a generated physical query plan that is used with the rule based properties tables to prune inferior query plans.

Abstract: A user interface (UI) for visualizing search data provides techniques for grouping and organizing aggregate data that shows the categories of topics included in search queries from a large number of individual users. Raw search queries are categorized into one of a number of topical categories. The search queries are assigned to a geographic location based on geolocations of computing devices generating the search queries. The UI presents a map that shows the number of search queries per topical category for each geographic location displayed in the current UI view. As a result of this UI design, a user can easily understand the interaction between geographic location and frequency of search query topics. Trends in the geographic distribution of searches and in the categories of topics searched are also easily understood from this UI design by changing the time range of the search queries displayed.

Abstract: Technologies for dynamic accelerator selection include a compute sled. The compute sled includes a network interface controller to communicate with a remote accelerator of an accelerator sled over a network, where the network interface controller includes a local accelerator and a compute engine. The compute engine is to obtain network telemetry data indicative of a level of bandwidth saturation of the network. The compute engine is also to determine whether to accelerate a function managed by the compute sled. The compute engine is further to determine, in response to a determination to accelerate the function, whether to offload the function to the remote accelerator of the accelerator sled based on the telemetry data. Also the compute engine is to assign, in response a determination not to offload the function to the remote accelerator, the function to the local accelerator of the network interface controller.

Abstract: A large highly parallel database management system includes thousands of nodes storing huge volume of data. The database management system includes multiple query optimizers for determining low cost execution plans for queries. The database management system is adapted to receive a data query. An execution plan generator component of the database management system generates an initial execution plan for the query. The initial execution plan is fed as input to more than one query optimizers. Each optimizer starts with the initial execution plan, generates alternative execution plans, and determines a satisfactory execution plan that incurs the lowest cost. The database management system compares the selected execution plans by the optimizers and selects one with the lowest cost. The multiple query optimizers run in parallel.

Abstract: Systems and methods provide techniques for reviewing content, such as reviewing video on a mobile device. A computing device with a touch screen interface, e.g., a tablet computer, executes a reviewing tool, e.g., a computer program, that causes the device to display video content and information about the video content. The tool provides an interface for selecting video, images, and information, for review and for annotation. The tool uses remote and/or local data to display video, images, and information for review.

Abstract: A method and system is disclosed that generates a dictionary of terms comprising terms associated with games of a collaboration platform. The method further identifies search terms associated with previous search queries. The method compares the search terms with the terms of the dictionary to determine whether the search terms associated with the previous search queries are in the dictionary of terms. The method identifies a first set of the search terms that are candidates to receive search suggestions and a second set of the search terms that are to be the search suggestions based on the comparison. The method also generates a record that associates candidate search terms of the first set of the search terms with respective search suggestions of the second set of the search terms. The record is used to provide a search suggestion for a search term of a new search query.

Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: A computer-implemented method of evaluating a set of filter parameters being represented by a filter tree comprising a plurality of nodes. The method can include identifying whether a node is a root of a sub-tree comprising other nodes of the filter tree; generating a cost for said node by processing a sample input comprising a plurality of data items of a data source using the filter parameter and measuring the time taken for the plurality of data items to be processed; and determining a selectivity of said node based on an output of its filter parameter as a result of processing the sample input using the filter parameter; then ordering at least some of the plurality of nodes of the filter tree having the same parent node based on their relative costs and selectivities, for use in generating an ordered filter tree.

Abstract: An embodiment may involve: (i) obtaining a set of data records that include respective pluralities of tuples characterizing operation of communication sessions in a network and that identify hardware or software components related to the network that were involved in the communication sessions, (ii) determining degrees to which signatures in the pluralities of tuples are associated with communication problems in the network; (iii) identifying, from the degrees, a subset of the signatures most associated with the communication problems; (iv) grouping specific pairs from the subset of the signatures into equivalence classes based on co-occurrence of signatures of the specific pairs within the data records; (v) generating and pruning a dependency graph between the equivalence classes; (vi) from the equivalence classes remaining in the dependency graph, selecting a subset of the hardware or software components related to the network that are candidates for involvement with the communication problems.

Abstract: The disclosed embodiments provide a system for processing a query for a ranking of candidates for an opportunity. During operation, the system obtains parameters associated with a query for a ranking of candidates for an opportunity, wherein the parameters include a candidate and the opportunity. Next, the system matches one or more of the parameters to a fixed number of quantile thresholds calculated from a distribution of scores for the candidates. The system then estimates, based on the fixed number of quantile thresholds, a quantile for a score of the candidate. Finally, the system outputs a position of the candidate within the ranking based on the estimated quantile.

Abstract: An apparatus and techniques for constructing and utilizing a “dynamic dictionary” that is not a compiled dictionary, and therefore does not need to be recompiled in order to be updated. The dynamic dictionary includes respective data structures that represent (i) a management automaton that includes a plurality of management nodes, and (ii) a runtime automaton that is derived from the management automaton and includes a plurality of runtime nodes. The runtime automaton may be used to search input data, such as communication traffic over a network, for keywords of interest, while the management automaton manages the addition of keywords to the dynamic dictionary. Typically, at least two (e.g., exactly two) such dynamic dictionaries are used in combination with a static dictionary.

Abstract: A data providing apparatus includes circuitry configured to store a query as a candidate query in a first memory in association with an execution plan and store data in a second memory when receiving the execution plan and the data from a database server in response to transmitting the query to the database server, perform searching the first memory for a first candidate query having content corresponding to content of a first query in response to receiving the first query from a first request source, when the first candidate query is detected by the searching, select a first execution plan associated with the first candidate query by referring to the first memory, extract specific data from the second memory on the basis of the selected first execution plan, and transmit the specific data to the first request source.

Abstract: The present disclosure provides a shopping recommendation method, a client, and a server. The method includes: acquiring voice information of a user, and performing voice recognition and keyword extraction on the voice information, to obtain shopping keyword information; transmitting the shopping keyword information to a server, so that the server performs interest prediction according to the shopping keyword information and shopping related information of the user, to generate recommendation information; and receiving the recommendation information, and generating shopping recommendation content according to the recommendation information to be displayed by a display.

Abstract: A word extraction method according to at least one embodiment of the present disclosure includes: converting, with at least one processor operating with a memory device in a device, received speech information into text data; converting the text data into a string of words including a plurality of words; extracting, with the at least one processor operating with the memory device in the device, a keyword included in a keyword database from the plurality of words; and calculating, with the at least one processor operating with the memory device in the device, importance levels of the plurality of words based on timing of utterance of the keyword and timing of utterance of each of the plurality of words.

Abstract: Disclosed aspects relate to transforming a user-defined table function (UDTF) to a derived table in a database management system (DBMS). It may be detected by the DBMS that a query indicates the UDTF. A derived table may be constructed from the UDTF. The derived table may be derived from a set of statements of the UDTF. The derived table may be introduced to the query to fulfill the UDTF. A query plan may be generated for the query by the DBMS. The query plan may be generated in response to introducing the derived table in the query.

Abstract: A system comprises at least one hardware processor and a memory storing instructions. When executed, the instructions cause the at least one hardware processor to perform operations comprising receiving, in a computing process, a Java user-defined table function (Java UDTF), the Java UDTF including code related to a process method to be performed that includes receiving one or more input tables and transforming the one or more input tables to an output table; determining, using at least a security policy, whether performing one or more portions of the process method are permitted; and performing portions of the process method determined to be permitted.

Abstract: A method, system, apparatus, and a computer program product are provided for optimizing database query plans generated from a received database query at a database management system by monitoring a global cost estimation function for one or more steps of the received database query to identify a first low-performing cost metric and collaboratively optimizing a query plan for the database query by comparing differences between the first low-performing cost metric and a second cost metric at an additional database management system, thereby generating an optimized query plan for the database management system that may be stored at the database management system along with corresponding information identifying a reason for rewriting the optimized query plan.

Abstract: A system extracts data from one or more sources of data and displays information regarding the data using interactive visualizations that allow a user to interact directly with the visualizations of the data, without necessarily requiring the user to utilize a menu-driven interface.

Abstract: Methods for cardinality estimation feedback loops in query processing are performed by systems and devices. A query host executes queries against data sources via an engine based on estimated cardinalities, and query monitors generate event signals during and at completion of execution. Event signals include indicia of actual data cardinality, runtime statistics, and query parameters in query plans, and are routed to analyzers of a feedback optimizer where event signal information is analyzed. The feedback optimizer utilizes analysis results to generate change recommendations as feedback for later executions of the queries, or similar queries, performed by a query optimizer of the query host. The query host stores change recommendations, and subsequent queries are monitored for the same or similar queries to which change recommendations are applied to query plans for execution and observance by the query monitors. Change recommendations are optionally viewed and selected via a user interface.

Abstract: Included are a vector estimation means that estimates, in response to receiving input of a plurality of pieces of relational data each including a plurality of objects and a relationship between the objects, for each piece of relational data, a latent vector for characterizing a structure of the relational data by using the objects and the relationship included in the relational data; and a matching means that matches, for each set of first relational data and second relational data different from each other of the received pieces of relational data, a first object and a second object by using a first latent vector corresponding to the first object included in the first relational data and a second latent vector corresponding to the second object included in the second relational data.

Abstract: Query content-based data generation includes obtaining a query having an outer query and one or more subqueries, performing subquery transformation on each subquery, which converts predicates of the subqueries to be predicates of the outer query, and thereby obtain a transformed query, generate from the transformed query block(s) each having a list of predicates selected from the transformed query, processing each query block for column information, including column range information and column relationship information, and generating data and populating a dataset having table(s) and respective column(s) for each of the table(s). Generating the data uses the column range information and the column relationship information to select data for the dataset such that data records from the dataset are produced as results to executing the obtained query against the dataset.

Abstract: The subject technology receives a first query plan corresponding to a first query, the first query plan comprising a new query plan different than a previous query plan for the first query. The subject technology determines a value indicating an estimated improvement in execution time of the first query plan in comparison to a previous execution time of the previous query plan. The subject technology determines that the value is greater than a threshold value. The subject technology, in response to the value being greater than the threshold value, executes the first query using the first query plan.