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:
A method for processing a data stream may comprise retrieving a first window from a distributed cache platform based on a first window key, executing a first task and a second task in parallel on a processor resource, and merging a first result and a second result into a stream result based on a relationship between a first task key and a second task key.
Abstract:
Example embodiments relate to parallelizing structured query language (SQL) user defined transformation functions. In example embodiments, a subquery of a query is received from a query engine, where each of the subqueries is associated with a distinct magic number in a magic table. A user defined transformation function that includes local, role-based functionality may then be executed, where the magic number triggers parallel execution of the user defined transformation function. At this stage, the results of the user defined transformation function are sent to the query engine, where the query engine unions the results with other results that are obtained from the other database nodes.
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.
Abstract:
Examples disclosed herein relate to accessing electronic databases. Some examples disclosed herein may include partitioning a computation task into subtasks. A processing node of a computation engine may generate a database query for retrieving an electronic data segment associated with at least one of the subtasks from a database. The database query may include pre-processing instructions for a database management system (DBMS) associated with the database to pre-process the electronic data segment before providing the electronic data segment to the processing node. The pre-processing instructions may include at least one of: filtering, projection, join, aggregation, count, and user-defined instructions. The generated query may be provided to the DBMS.
Abstract:
A system includes a distributed file system to control storage of data across storage nodes and a database query engine to receive a database query for access of data, the database query engine to process the database query using an index, and using a buffer pool to cache data retrieved in response to the database query and to store updated data. An abstraction layer is provided between the database query engine and the distributed file system, the abstraction layer to read and write data of the distributed file system in response to the database query.
Abstract:
A technique for analyzing a parallel data stream using a sliding FP tree can include create a sliding FP tree using input tuples belonging to a parallel sliding window boundary and analyze patterns of the parallel data stream in the parallel sliding window boundary.