An autonomous futures contract orchestration platform includes processors programmed with non-transitory computer-readable instructions to collectively execute receiving, from a data source, an indication associated with a product that relates to an entity that at least one of purchases or sells the product. The instructions include predicting a baseline cost of at least one of purchasing or selling the product at a future point in time based on the indication. The instructions include retrieving a futures cost, at a current point in time, of a futures contract for the product. The instructions include generating a risk threshold based on a specified risk tolerance of the entity indicating a difference between the baseline cost and the futures cost. The instructions include executing a smart contract for the futures contract based on the baseline cost, the futures cost, and the risk threshold.

In accordance with an embodiment, described herein is a system and method for providing cross-microservice query processing. The system provides an object service framework that supports the use of microservices that may be loosely-coupled but related in some way, for example in that they interoperate together or require access to each other's data in order to process queries. Each microservice can be developed, deployed and evolve independently, and interact with the other microservices through contracts or interfaces that are defined as public APIs and are then exposed via the framework. The object service framework can be used, for example to provide a cross-microservice layer that automatically transforms queries that join objects in different microservices into a single database query that is optimized for use with the database.

A system for generating a mixed query plan including operator alternatives. A method may include generating a mixed query plan including a first operator selected as a pre-compiled operator; generating the mixed query plan including a second operator selected as operator alternatives, the operator alternatives configuring the second operator as pre-compiled or code-generating alternatives; delaying selection of one of the operator alternatives until additional information regarding the mixed query plan becomes available; generating the mixed query plan including a third operator selected as a code-generating operator; and selecting, given the third operator representing the additional information, one of the operator alternatives to enable execution of the mixed query plan using the selected operator alternative. Related methods and articles of manufacture are also described.

Techniques for improving system performance based on data characteristics are disclosed. A system may receive updates to a first data set at a first frequency. The system selects a first storage configuration, from a plurality of storage configurations, for storing the first data set based on the first frequency, and stores the first data set in accordance with the first storage configuration. The system may further receive updates to a second data set at a second frequency. The system selects a second storage configuration, from the plurality of storage configurations, for storing the second data set based on the second frequency, and stores the second data set in accordance with the second storage configuration. The second storage configuration is different than the first storage configuration.

A system includes reception of a query execution plan associated with a plurality of query execution pipelines, estimated execution costs and estimated intermediate result cardinalities, determination of one or more precedence relationships of the plurality of query execution pipelines, determination of an execution order of the plurality of query execution pipelines based on the estimated execution costs, the estimated intermediate result cardinalities, and the one or more precedence relationships, and providing of the execution order of the plurality of query execution pipelines and the query execution plan to a query execution engine.

Aspects of the disclosure are directed to late materialization of attributes in response to queries to a database implementing a database cache. Queried data is materialized in temporary memory before the data is projected as part of generating a result to the query. Instead of materializing all of the attributes referenced in a query before executing the query, a database management system materializes attributes as “late” as possible—when the operation needing the attributes is executed. The operation needing the attributes can be performed sooner, as opposed to materializing all referenced attributes are materialized before executing the query.

Computer implemented methods for database hierarch-independent data drilling are presented including: a. selecting one of at least two database structures each having data, where the at least two database structures include, at least two distinct paths that lead from a first of the at least two database structures to a second of the at least two database structures, where a path logically relates at least two data structures which are otherwise directly unrelated using data structures and data structures' relations, and a database information schema that provides information about the at least two database structures including information regarding relations between data structures; b. setting the selected database structure as a current data drilling state; and c. finding at least one related data structure corresponding with the selected database structure for the current data drilling state utilizing the database information schema.

Storing a subset of a database on a mobile device. The subset of the database stored on the mobile device being based on privilege information associated with the mobile device and/or a user of the mobile device. One of more mobile applications can access the subset of the database stored on the mobile device when the mobile device is offline and unconnected to a database management system associated with the database. A set of queries can be performed on the subset of the database stored on the mobile device.

A computer-implemented method, system, and/or computer program product optimizes an order of execution of column join operations. A first partitioning of the first data column splits the first data column into first subsets of rows. A second partitioning of the second data column splits the second data column into a second subsets of rows. A first value frequency information indicates a frequency of attribute values within a subset of rows of the first data column processed. A second value frequency information indicates a frequency of attribute values within a subset of rows of the second data column. Cardinalities of sub-tables derived by a respective joining of the subsets of rows of the first and second data columns are estimated, based on the first and second value frequency information. An order of execution of multiple join operations is then optimized based on the estimated cardinalities of the sub-tables.

A computer-implemented method for efficiently performing a database join in a distributed data processing system comprising multiple computational nodes, the method comprising determining a first set of one or more columns of a first database table and a second set of one or more columns of a second database table on which the join is to be performed; estimating a size of the rows of the first table which have a particular combination of values in the first set of columns; computing a salt factor n based on the estimated size of rows and further based on a processing capacity of a computational node of the distributed data processing system; assigning one of n different salt values to each row of the first table having the particular combination of values in the first set of columns; for each row of the second table having the particular combination of values in the second set of columns into n rows, expanding the row into n row, and assigning to each expanded row a different one of the n salt values; and performing a join operation on the modified first and second tables, wherein the rows of the first and second tables have the same combination of values in the first and second sets of columns and the same salt value are joined on the same computational node.