Abstract: Example embodiments relate to parallelizing structured query language (SQL) on distributed file systems. In example embodiments, a subquery of a distributed file system is received from a query engine, where the subquery is one of multiple subqueries that are scheduled to execute on a cluster of server nodes. At this stage, a user defined function that comprises local, role-based functionality is executed, where the partitioned magic table triggers parallel execution of the user defined function. The execution of the UDF determines a sequence number based on a quantity of the cluster of server nodes and retrieve nonconsecutive chunks from a file of the distributed file system, where each of the nonconsecutive chunks is offset by the sequence number.

Abstract: Examples disclosed herein relate to parallel transfers of electronic data. Some examples disclosed herein may include executing, by a processing node of a computation engine, a computation task among a plurality of computation tasks generated by the computation engine for transferring an electronic data table to a target table. The computation task, when executed by the processing node, may cause the processing node to transfer a segment of the electronic data table to a staging table, update a task status table upon completing the transfer of the segment to the staging table, in response to determining that the plurality of computation tasks have completed, update a last committer table with a task identifier associated with the computation task, and in response to determining that the last committer table includes the task identifier associated with the computation task, transfer the staging table to the target table.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to manage a cache. An example method includes in response to receiving a request to retrieve received data, retrieving first data from a cache, the first data received during a first time period, and retrieving second data from a storage device, the second data received during a second time period prior to the first time period; and providing the first data and second data as combined data, the combined data being combined based on the first time period and the second period.

Abstract: A method includes binding a stationed operator to a database query engine, wherein the stationed operator comprises system utilities and an open executor to execute user-supplied application logic. The method further includes receiving an unbounded input stream of input tuples by the stationed operator, the stream of input tuples comprising a succession of chunks. The method also includes applying a query defined by the application logic to each successive chunk of the input stream to produce an output packet for each such chunk, and generating an unbounded output stream comprising the output packets.

Abstract: In one example in accordance with the present disclosure, a method for dynamic lexer object construction includes receiving a grammar rule including a variable and a Boolean function to be performed on a character sequence using the variable. The method includes receiving the character sequence and a value corresponding to the character sequence and constructing a lexer object that includes the value as the variable used by the Boolean function. The method includes parsing the character sequence using the lexer object.

Abstract: An example technique for defining a user function can include receiving a user defined function that gathers data from a data source external to a database and returns the data to the database. The example technique for defining the user function can also include creating an instance of a programming class that extends from an application programming interface (API). The instance of the programming class including the user defined function. The example technique for defining the user function can also include executing the user defined function provided by the instance of the programming class.

Abstract: In-database parallel analytics is disclosed. An example method includes receiving a function in a functional programming environment. The example method includes pushing operations for the function to a database layer for executing the operations. The example method also includes returning results of the operations to the functional programming environment.

Abstract: A technique includes in a relational database query engine, receiving a query associated with a relational data structure. The received query includes a database graph query. The technique includes using the relational database query engine to integrate a result acquired from the graph database engine into a result provided by the relational database query engine to the received query.

Abstract: In one example in accordance with the present disclosure, a method may include separating a list of keywords into a set of word tokens and a set of wildcard tokens. The method may also include removing each wildcard token in the set of wildcard tokens that is inferred by at least one word token in the set of word tokens and removing each wildcard token in the set of wildcard tokens that is inferred by at least one other wildcard token in the set of wildcard tokens. The method may also include executing a search query comprising a new list of keywords that includes each wildcard token not removed from the set of wildcard tokens.

Abstract: A technique of batching tuples can include determining a plurality of key-attributes for a plurality of tuples, creating a batch tuple, and calculating a hash value for the batch tuple.

Abstract: A pattern of geocoded pixels is generated by accessing data point values, where each data point value includes an attribute value and coordinates of a geographic location. Each data point value corresponds to a geocoded pixel that is positioned on the pattern based on the coordinates of the data point value such some geocoded pixels overlap other geocoded pixels. Different levels of the pattern of geocoded pixels correspond to a different degree of overlap between the geocoded pixels. The different levels of the pattern of geocoded pixels are associated with different magnification levels of a geographic map such that changing a magnification level of the geographic map causes a degree of overlap between the geocoded pixels of the pattern to change.

Abstract: A system and method for a text search of a database. A text search expression is converted to a query plan having multiple search tokens. A one-pass indexing of an invested word index filters the inverted word index based on a search condition and identifies the applicable documents having the multiple search tokens.

Abstract: In one example in accordance with the present disclosure, a method for dynamic schema typing may include receiving a host query with a function defining data to be retrieved. The function may include a dynamically definable schema. The method may also include receiving, at function invocation time, a data type schema defining a type of the data to be retrieved and generating a query using the data type schema as a value for the dynamically definable schema. The method may also include retrieving the data, converting the retrieved data into a form defined by the data type schema and providing the transformed data to the host query.

Abstract: Examples disclosed herein relate to a database comparison operation to identify an object. For example, a processor may enroll a set of object templates in a storage based on objects within input content and enroll a target object template in the storage based on a target object in target content. The processor may identify an object within the input content associated with the target object based on a database comparison operation of the stored set of object templates to the stored target object template. The processor may output object recognition information related to the identified object.

Abstract: A system includes a database client, and a distributed database comprising database nodes. The distributed database may receive a database query from the client, determine that the query comprises a range of hash values of a table partition stored by a node of the distributed database, and determine that the range of hash values is not stored by other nodes of the distributed database. Responsive to determining that the range of hash values of the query is stored by the node and not by the other nodes, the database may generate an optimized distributed execution plan that includes the node that stores the range of hash values and excludes the nodes that do not include the range of hash values.

Abstract: In one example in accordance with the present disclosure, a method for dynamic lexer object construction includes receiving a grammar rule including a variable and a Boolean function to be performed on a character sequence using the variable. The method includes receiving the character sequence and a value corresponding to the character sequence and constructing a lexer object that includes the value as the variable used by the Boolean function. The method includes parsing the character sequence using the lexer object.

Abstract: Examples disclosed herein relate to distributed computing in R. Some examples disclosed herein may include identifying a distributed multivariate apply (dmapply) operation and an invocation of a distributed computing backend and determining a function referenced in the dmapply operation. A distributed backend driver associated with the invoked distributed computing backend may translate the determined function to a function native to an R application programming interface (API) of the invoked distributed computing backend and may provide the translated function to the invoked distributed computing backend to perform the translated function on a distributed data set referenced in the dmapply operation.

Abstract: In one example in accordance with the present disclosure, a system comprises a computing node. The computing node comprises: a memory, and a processor to: execute a database in the memory, and invoke, with the database, singular value decomposition (SVD) on a data set. To invoke SVD, the processor may sparsify, with the database, the data set to produce a sparse data set, iteratively decompose, with the database, the data set to produce a set of eigenvalues, solve, with the database a linear system to produce a set of eigenvectors, and multiply, with the database, the eigenvectors with the data set to produce a data set of reduced dimension.

Abstract: According to an example, dynamic function invocation may include ascertaining a query for a database management system (DBMS). Dynamic function invocation may further include implementing a dynamic function as a meta user defined function to invoke a plurality of different coded functions including a coded function that is to be invoked by the query to perform an operation related to the DBMS, and executing the dynamic function by the query to load and invoke the coded function to perform the operation related to the DBMS.

Abstract: Methods, devices, and techniques for base user defined functions in a database management system are discussed herein. For example, in one aspect, a query request is received from a computer device. The query request may include a query operator representing a specialized user defined function (SUDF). The SUDF may then be executed. Executing the SUDF may include executing a base operation of a base user defined function (BUDF). The base operation may interact with an application programming interface (API) of the query engine to obtain a tuple stored in the database. Executing the SUDF may further include executing a specialized operation that processes the tuple according to an analytics function. The specialized operation may generate a result. Then, a query result may be returned to the computer device. The query result can include the result.