Abstract: Techniques for performing machine learning inference calls in database query processing are described. A method for performing machine learning inference calls in database query processing may include generating a query plan to optimize a query for batch processing of data stored in a database service, the query plan including a batch mode operator to execute a function reference and an execution context associated with the batch mode operator, executing the query plan to invoke a function associated with the function reference, wherein the function sends a batch of requests, generated using the execution context, to a remote service and obtains a plurality of responses from the remote service, and generating a query response based on the plurality of responses.

Abstract: A system includes one or more processors and data storage containing instructions executable by the one or more processors to perform operations. The operations include detecting a first executed transaction causing a first modification to table data stored in a table. The table data is associated with a corresponding metadata file with metadata information of the table. A new metadata file is generated responsive to the first executed transaction. The new metadata file includes the metadata information and additional metadata associated with the first modification. A second executed transaction causing a second modification to the table data is detected. The table data is updated with a change tracking column. The change tracking column includes lineage of executed transactions on the table data. The lineage indicates at least the first transaction and the second transaction.

Abstract: A method includes parsing a query to determine a plurality of data processing operations associated with the query and including an AS OF JOIN operation between first time series data in a first table and second time series data in a second table. A query plan of the query is generated. The query plan includes a plurality of nodes corresponding to the plurality of data processing operations. At least one of the plurality of nodes corresponding to the AS OF JOIN operation is modified to generate a modified query plan of the query. The modifying is based on applying a UNION operation on at least a first portion of column data in the first table and the second table to obtain a combined table. Execution of the query by at least one of a plurality of computing nodes is scheduled based on the modified query plan.

Abstract: Examples described herein provide a computer-implemented method that includes training a machine learning model. The model is trained by generating a set of training queries using at least one of a query workload and relationships between tables in a database, building a query graph for each of the set of training queries, computing, for each training query of the set of training queries, a selectivity based at least in part on the query graph, and building, based at least in part on the set of training queries, an initial join result distribution as a collection of query graphs.

Abstract: Disclosed herein are system, method, and computer program product embodiments for accessing a data service using a data service Uniform Resource Identifier (URI) object. An embodiment operates extracting a name-value pair of each parameter stored in the data service class object. The embodiment generates a parameter context URI using the one or more extracted name-value pairs according to a data service specification of the data service. The embodiment extracts one or more filter range items for each filter option stored in the data service class object. The embodiment generates a filter context URI using the one or more extracted filter range items according to the data service specification of the data service. The embodiment generates a context URI using the parameter context URI and the filter context URI. The embodiment then accesses the data service according to the context URI.

Abstract: An object-backed block-based storage system may store data blocks in a block cache in a non-relational database and data block objects in an object data store. Access requests for a particular data block may be received at a storage protocol target that are formatted according to a network-based storage protocol. Translated access requests formatted according to respective programmatic interfaces may be generated and sent to the non-relational database or to the object data store in order to access the particular data block. A response indicating success or failure of the access request may be sent.

Abstract: A method may use a minimal set of indices for an input query including identifying the input query including primitive searches that are accelerated using indices, and computing a minimal set of indices for the input query using a polynomial-time algorithm by constructing a bi-partite graph comprising a first and a second vertex set. The first and the second vertex set may be a set of searches in both partitions of the bi-partite graph. Each edge of the edge set may connect a vertex in the first vertex set and a vertex in the second vertex set. The method may further include identifying an edge set as a strict subset relation between at least two searches of the set of searches showing up in the first and second vertex set of the bi-partite graph, and performing relational data analysis using the minimal set of indices for input queries.

Abstract: Disclosed is a method and system for processing skewed datasets. The processor 202 is configured to capture a broadcast size of non-skewed datasets to be loaded onto a memory associated with one or more nodes in a distributed system. The skewed dataset is identified from two or more datasets to be joined. Each of the non-skewed dataset is divided into a plurality of non-skewed data chunks at the node and each of the non-skewed data chunk is broadcasted to one or more nodes having the skewed dataset. The joining operation is then performed between each of the skewed dataset and the non-skewed data chunk till all the non-skewed data chunks are consumed in the join operation. Resultant joined dataset is then collected as a single joined dataset from the nodes involved in the joining operation.

Abstract: A data redistribution method, apparatus and a database cluster includes at least one first node, and an original table is stored on the at least one first node. A data redistribution process for redistributing the original table to the at least one first node and a second node is started, and the data redistribution process includes: starting a first transaction for creating a temporary table on the at least one first node and the second node, and associating an import operation for the original table with an import operation for the temporary table; starting a second transaction for selecting an old tuple from the original table based on a transaction identifier of the first transaction, and redistribute the selected old tuple to the temporary table. After the second transaction ends, metadata of the original table and metadata of the temporary table are exchanged.

Abstract: Aspects described herein may be used with local spreadsheet applications, web, and/or cloud-based spreadsheet solutions, to create complex custom software applications. Spreadsheets themselves lack the conceptual framework to be used as a platform tool to build custom or complex software applications. Using the methods and systems described herein using low-code/no-code techniques, a designer can create custom and/or complex software applications using one or more spreadsheets as the underlying blueprints for the software application. The resultant software application may be static/read-only, or may be interactive to allow users to dynamically add, delete, edit, or otherwise amend application data, e.g., via one or more online web pages or via a mobile application. Data transfer may be one-way or bi-directional between the blueprint spreadsheets and the resultant software application, thereby allowing amended data to be transferred from the software application back into spreadsheet form.

Abstract: In various example embodiments, a system and method for retrieving database records are presented. A method includes receiving an access request for database records, identifying a primary database record corresponding to the access request, and selecting a set of secondary database records corresponding to a portion of the access request. The method determines a set of differentiating elements within records of the set of secondary database records. Each differentiating element distinguishes at least one record of the set of secondary database records from one or more of the primary database record and a portion of the records included in the set of secondary database records. The method generates a formatted search interface including a set of selectable interface icons representing one or more differentiating elements and causes presentation of the formatted search interface at a client device associated with the access request.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for providing run-time querying of multi-tenant non-relational database objects. A database system maintains a multi-tenant non-relational database associated with a number of enterprises, a number of records, and a number of data objects for each of the enterprises, each data object having at least one composite key field. A request is received during runtime to query data related to a data object, and the system determines that the data object is defined to be used in associated with a non-relational database. The system then retrieves a metadata model of the data object, determines that the request includes at least one composite key field for the data object, and processes the requery to query data in synchronous fashion. Finally, a query response is provided to the user.

Abstract: Disclosed embodiments include a method performed by server computer(s). The method includes receiving a query and defining a query plan based on the received query. The query plan refers to datasets contained in data sources. The method further includes determining that the received query can be accelerated based on an optimized data structure contained in a memory, where the optimized data structure is derived from a dataset referred to in the query plan. The method further includes modifying the query plan to include the optimized data structure, and executing the modified query plan to obtain query results that satisfy the received query by reading the optimized data structure in lieu of reading at least some data from the data sources.

Abstract: A method for execution by a query processing module includes determining a query expression indicating a query for execution. An operator tree is generated based on a nested ordering of a plurality of operators indicated by the query expression. Conjunctive normal form (CNF) conversion cost data is generated based on the operator tree, and disjunctive normal form (DNF) conversion cost data is also generated based on the operator tree. Conversion selection data is generated based on the CNF conversion cost data and the DNF conversion cost data. The conversion selection data indicates a selection to perform either a CNF conversion or a DNF conversion. A normalized query expression is generated by performing either the CNF conversion or the DNF conversion upon the query expression based on the conversion selection data. Execution of the query is facilitated in accordance with the normalized query expression.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for inferring joins for data sets. In some implementations, a first data table and a second data table are identified. A first subset of records are selected from the first data table and a second subset of records are selected from the second data table. For fields of the first subset and the second subset, sets of feature values are generated indicating characteristics of the data in the fields. Based on the sets of feature values, one or more similarity score are determined, with each similarity score indicating a similarity of a column in the first data table with respect to a column in the second data table. Based on the one or more similarity scores, data indicating a recommendation to join one or more columns of the first data table with one or more columns of the second data table is provided for output by a computing device.

Abstract: Joining data using a disjunctive operator is described. An example computer-implemented method can include receiving a query that includes a first disjunctive predicate involving a first table and a second table. The method may also include determining a first set of rows from the first table and generating a filter from the first set of rows. The method may also further include applying the filter to the second table to generate a second set of rows. Additionally, the method may also include joining the first set of rows and the second set of rows using a first disjunctive operator of the first disjunctive predicate to generate a first results set.

Abstract: A query with a UNION ALL (UA) view is detected by a query optimizer. A query execution plan and cost for the query is obtained. The query is rewritten to push aggregates of the original query into the view. A query execution plan is generated for the rewritten query and a cost for executing the rewritten query is obtained. The lowest cost execution plan is selected for execution by a database engine of a database.

Abstract: A method for execution by a query processing system includes determining a query request that indicates a plurality of operators, where the plurality of operators includes at least one relational algebra operator and further includes at least one non-relational operator. A query operator execution flow is generated from the query request that indicates a serialized ordering of the plurality of operators. A query resultant of the query is generated by facilitating execution of the query via a set of nodes of a database system that each perform a plurality of operator executions in accordance with the query operator execution flow, where a subset of the set of nodes each execute at least one operator execution corresponding to the at least one non-relational operator in accordance with the execution of the query.

Abstract: A method may include inserting, into a hash trie, data records from a database table. The inserting may include traversing the hash trie to identify, for each data record included in the database table, a corresponding node at which to insert the data record. The hash trie may be traversed based on a hash of a key value associated with each data record. The node at which to insert a data record may be identified based on an offset forming a binary representation of the hash of a key value associated with that data record. The offset may include a portion of a plurality of binary digits forming the binary representation. A data record may be inserted at a corresponding node by updating a data structure included at the node. A database operation may be performed based on the hash trie filled with the data records from the database table.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and an edits dataset. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The edits dataset is the set of data that contains edits such as cell mutations, row appends and/or row deletions. The database system enables users to make cell or row-level edits to tables and observe those edits in analytical systems or downstream builds with minimal latency.

Abstract: Match rules for rewriting queries to use materialized views may be dynamically generated by a database system. A database system may generate rules that indicate whether a given query can use a materialized view and how to rewrite the given query to use the materialized view. A query may be received and the rules may be applied to the query to determine that the query can use the materialized view and to rewrite the query to use the materialized view. The rewritten query can then be executed.

Abstract: A method and a system include, for each predetermined time period in a plurality of predetermined time periods, writing a plurality of data rows comprising a set of data associated with a plurality of active entities, and updating an index table based on the plurality of data rows in the stats table, wherein the index table comprises an index row. The method further includes receiving from an electronic device via an interface a query corresponding to an entity, retrieving an index value from an index row included an index row, retrieving the current value from the stats table using the index value, generating a response to the query using the index value and the current value, and displaying the response on a display of the electronic device.

Abstract: Computer-implemented methods and systems are disclosed for receiving and indexing a plurality of files for later querying, for dynamically generating scripts to be executed during a query of a data store, and for horizontally distributing a query and aggregating results of the distributed query.

Abstract: A database platform can track changes using a stream that records changes made by database transactions. Streams on views can be implemented by applying a stream to source data, and applying the view to the streamed data. Users of the database platform can query the stream on the view to review recent changes to the view, such as changes made since the last database transaction.

Abstract: A system for executing a streaming query includes an interface and a processor. The interface is configured to receive a logical query plan. The processor is configured to determine a physical query plan based at least in part on the logical query plan. The physical query plan comprises an ordered set of operators. Each operator of the ordered set of operators comprises an operator input mode and an operator output mode. The processor is further configured to execute the physical query plan using the operator input mode and the operator output mode for each operator of the query.

Abstract: Methods and systems disclosed herein may optimize write operations in a transaction to reduce the number of operations to the point where each of the write operations may be performed in parallel. The writer optimizer may review a first write operation and a second write operation to determine whether the first write operation and the second write operation write to the same row in the same table. When the first write operation and the second write operation write to the same row in the same table, the first write operation and the second write operation may be combined to generate a functionally-equivalent third write operation. The third write operation may reduce the number of operations in the transaction by replacing both the first write operation and the second write operation.

Abstract: Techniques support graph pattern matching queries inside a relational database management system (RDBMS) that supports SQL execution. The techniques compile a graph pattern matching query into a SQL query that can then be executed by the relational engine. As a result, techniques enable execution of graph pattern matching queries on top of the relational engine by avoiding any change in the existing SQL engine.

Abstract: A method, a system, and a computer program product for rewriting queries. A received query is parsed into a plurality of subqueries, where each subquery has one or more query elements. One or more identical subqueries are identified and grouped into one or more groups. Based on the groups of subqueries, an alias parameter is assigned to each identical subquery. The identical subqueries in the received query are replaced with corresponding aliases. An expression language statement is generated based on the received query, where each identical subquery is replaced with the corresponding assigned alias parameter in the expression language. The generated expression language statement is executed.

Abstract: Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.

Abstract: System and method to display PIM application content in one or more PIM application display panes of a graphical user interface (GUI), select the displayed PIM application content for which to obtain a one or more record overviews of a CRM record related to the PIM application content, receive PIM application context data related to selected PIM application content, generate the one or more record overviews of the CRM record related to the PIM application content to display in a context-specific display pane based on the received PIM application content or PIM application context data, and display the generated one or more record overviews in the context-specific display pane.

Abstract: A selective database rollback method includes identifying a table, identifying a root key, storing a target rollback date, retrieving schema information including keys, ordering the table, iterating over the table, storing the current table state, obtaining a transaction journal, and reverse-applying the transaction journal to generate an output file. A method for identifying database key includes iterating over a table's columns and rows, generating similarity metrics by comparing column-wise and/or row-wise data, and comparing the generated similarity metrics to a threshold value. A server includes a processor and a memory storing instructions that, when executed by the one or more processors, cause the server to identify a table, identify a root key, store a target rollback date, retrieve schema information including keys, order the table, iterate over the table, store the current table state, obtain a transaction journal, and reverse-apply the transaction journal to generate an output file.

Abstract: The manner in which tables are joined can affect the outcome of the query and database performance. Example types of join operations include semi-join and inner-join. The techniques described herein are approaches that may be used to substitute a semi-join operator with an inner-join operator and may be used to transform and optimize representations of queries.

Abstract: The present disclosure relates to a subscription server, a subscription terminal and an information subscription method and system. The method includes establishing content information of a request from a first entity as first information of an event after determining that request information of the request satisfies an event notification rule in a subscription resource, obtaining second information of the event according to an associated object of the subscription resource, and sending a notification message containing the first information and the second information to a notified party of the subscription resource. The present disclosure may be applied to avoid increasing the network load of a requester and a notifying party, and ensure that an event will be handled in time after the notification message of the event is received.

Abstract: An information providing method of an electronic apparatus is disclosed. The information providing method may include acquiring a search term from a user, identifying a product list corresponding to the search term, identifying one or more categories corresponding to the search term to filter the product list, and displaying the product list in a first area and displaying the one or more categories in a second area distinguished from the first area.

Abstract: This disclosure proposes systems, methods, and apparatus that identify raw SQL queries that are likely to cause a double counting error, and if such a SQL query is identified, then convert the raw SQL query into SQL queries that account for and avoid double counting. In some embodiments, this process uses queries and subqueries that refer back to a common table expression (CTE) in order to reduce code length and increase query execution speed.

Abstract: An approach is provided for optimizing a join operation that includes receiving, by one or more processors of a computer system, a join request associated with a fact table and a plurality of related dimension tables; identifying, by the one or more processors of the computer system, a join relationship from the fact table and the plurality of related dimension tables; matching, by the one or more processors of the computer system, different tables of the fact table and the plurality of related dimension tables; filtering, by the one or more processors of the computer system using data parallelism, the fact table and the plurality of related dimension tables, wherein the filtering occurs prior to performing the join request; and performing, by the one or more processors of the computer system, the join operation pursuant to the join request.

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 calculation engine of a database management system is described. The calculation engine may receive a query associated with a calculation scenario that defines a data flow model. The data flow model may include one or more calculation nodes, each of which corresponding to an operation performed on one or more database tables stored at a database. The one or more calculation nodes may include at least one calculation node corresponding to a ranking filter operation. The calculation engine may execute the query including by executing the calculation scenario. The executing of the calculation scenario may include performing the ranking filter operation to generate a result corresponding to at least a portion of rows included in a first partition of a database table stored at the database. Related systems, methods, and articles of manufacture are provided.

Abstract: The storage device includes a first memory, a process device that stores data in the first memory and reads the data from the first memory, and an accelerator that includes a second memory different from the first memory. The accelerator stores compressed data stored in one or more storage drives storing data, in the second memory, decompresses the compressed data stored in the second memory to generate plaintext data, extracts data designated in the process device from the plaintext data, and transmits the extracted designated data to the first memory.

Abstract: A method and software tool for identifying relationships between columns of one or more data tables are disclosed. In the disclosed method, a relationship indicator is computed for each of a plurality of column pairs, each column pair comprising respective first and second columns selected from the one or more data tables. The relationship indicator comprises a measure of a relationship (e.g. indicating a strength or likelihood of a relationship) between data of the first column and data of the second column. Relationships between columns of the data tables are then identified in dependence on the computed relationship indicators. The identified relationships may be used to create and execute data queries.

Abstract: Stored procedures are generated to perform incremental updates to a materialized view for a database. When a request to create a materialized view is received, one or more internal tables are created from the database. A stored procedure is generated that when executed will update the materialized view of the database. The stored procedure may obtain changes to the database that were not included in the internal tables and update the internal tables to include the obtained changes. The stored procedure may be performed automatically and in response to requests.

Abstract: A computer system executes a user-supplied query across multiple relational database tables linked by a common key. A new query form, called a composite join, takes a user-supplied query including one or more terms optionally joined by logical operations, an identification of two or more tables and an identification of a common join key shared across the tables. The composite join applies the query across the tables such that any of the query terms can be matched by any of the tables. A query is performed across all tables for each query term and any join keys associated with matching records from the tables are identified in a set of join keys associated with the respective term. The logical operations are then performed on the resulting sets of join keys to combine the results of the term queries according to the user query.

Abstract: A data analytics system may receive query definitions from which relationships between datasets may be identified. The query definitions may be analyzed to determine estimated costs and frequencies of combining a first and second dataset. Based on the cost and frequency, a combined dataset may be generated to by joining data from the first and second datasets. The combined dataset may be stored. Queries that comprise instructions to combine the first and second datasets may be processed by instead accessing the combined dataset.

Abstract: A query that references nested data may have sub-expressions included in a subquery for nested data to perform the query. A first query engine may rewrite the query to include one or more sub-expressions that reference the nested data into a subquery for the nested data as part of generating a plan to perform the query. A second query engine may then be caused to perform the subquery for the nested data. A result of the query may be inclusive of the performance of the subquery at the second query engine.

Abstract: A lightweight database-management system (DBMS) is based on a dynamic microservices architecture that implements each granular DBMS feature or function as a distinct, independently executable microservice. The DBMS's Parser front-end responds to each incoming query by selecting the first bind-time database feature needed to process the query. The Parser forwards its selection through a Channel-Binding subsystem to an Event Services Activation subsystem that activates a corresponding microservice to perform the selected feature. The first feature then selects the next required bind-time feature for activation, and this process continues sequentially until all required bind-time microservices have been identified, activated, and run. Runtime query-processing features are then sequentially selected in a similar manner. However, each selected runtime microservice is preloaded but not run.

Abstract: Techniques described herein proposes a Dependent Grouping Column Rewrite that simplifies a grouping operation by excluding dependent grouping columns from a group by clause. A non-blocking aggregation function is applied to dependent grouping columns in at least select clauses. Such a simplified grouping operation reduces memory pressure, speeds up grouping operations, and saves compute time, as grouping columns that have no additional effect on the grouping operation are excluded from processing (e.g., hashing and key matching).

Abstract: Efficient large column values storage in columnar databases is disclosed, including: providing a database comprising a write storage, a read storage, and an auxiliary storage, and wherein the auxiliary storage is used to store a large column value of a row that is associated with either the write storage or the read storage, wherein the large column value comprises a column value that meets a set of large column value criteria; and operating the database using the write storage, the read storage, and the auxiliary storage.

Abstract: An index update method, including: receiving an index update request, where the index update request is used to instruct to create or delete a target index that is associated with a field in a logic table of a tenant; updating metadata information of the logic table in a database in response to the index update request; notifying a coordination service, where the coordination service is used to notify a second data access node to perform a local synchronization update; and after all second data access nodes finish local synchronization updates, performing a data asynchronization update. After the metadata information is updated in the database, an index is updated in two steps. In a first step, a local synchronization update is performed. In a second step, after all data access nodes finish local synchronization updates, a data asynchronization update is performed.

Abstract: A database query processor includes a database join prefetcher that prefetches N next join column values in order to execute the query more efficiently. The prefetched next join column values for an inner table are used to skip rows in an outer table, thereby increasing the performance of executing the query. The number N of prefetches can be dynamically determined and adjusted to improve the performance of executing the query.

Abstract: A system includes determination, for a first partitioned physical query operator in a query operator tree, of a partition-wise placement cost based on a cost of each table partition associated with the first partitioned physical query operator and a partition-wise placement cost of any child physical query operator of the first partitioned physical query operator, determination of a placement cost for the first partitioned physical query operator physical query operator for each of a plurality of operator execution locations based on the determined partition-wise placement cost, determination, for a logical query operator associated with the first partitioned physical query operator, of a merged placement cost for each of the plurality of operator execution locations, and determination an execution location for the first partitioned physical query operator based on the determined partition-wise placement cost.