International Business Machines Corporation

Peter Bendel

Knut Stolze

Namik Hrle

Oliver Benke

Oliver Draese

Nicole Finnie

Maryela Evelin Weihrauch

Ruiping Li

Daniel Martin

Claus Kempfert

Vijayshankar Raman

Thomas Schaeck

Roland Seiffert

Tianchao Li

Felix O Beier

Stefan Raspl

Roland Weber

Gregor Meyer

Christian W Hoerst

Hong Min

Ke Wei Wei

Qi Zhang

Heng Liu

Oliver Koeth

Shuang Ys Yu

Horst Henn

Sowmya Kameswaran

Meichi M Lin

Björn Broll

Oliver Harm

Marco Czech

Elmar Albinger

An approach is provided in which a method, system, and program product analyze, while training a machine learning model, a set of first data transformation operators in a first data preparation pipeline that generates a plurality of constructed features from a set of training data. The method, system, and program product create a plurality of second data preparation pipelines from the first data preparation pipeline, wherein the set of first data transformation operators are converted to a set of second data transformation operators and each assigned to one of the plurality of second data preparation pipelines. The method, system, and program product deploy the plurality of second data preparation pipelines to a runtime system.

Auto feature preparation for high performance online inferencing

The present disclosure relates to executing concurrent database operations in a database system during a time window. The database operations are configured to use storage units of a storage space of the database system. A first usage speed of free storage units is determined to be used by at least one first database operation and a second usage speed of free storage units to be used by a second database operation. The first and second usage speeds may be used for determining a maximum number of free storage units to be used by the second database operation during the time window. The second database operation may be executed during the time window in accordance with the maximum number. The first database operation may be executed, wherein the execution of the first database operation during the time window being limited to the storage units of the storage space.

Concurrent execution of database operations

A method for merging transactions for execution by a database management system. The method includes a computer processor receiving a database query that is comprised of a plurality of transactions. The method further includes a computer processor placing each of the plurality of transactions, of the database query, in respective chronological order, in a scheduling queue. The method further includes a computer processor determining that at least a first transaction and a second transaction within the plurality of transactions each contains one or more transaction delineation descriptions. The method further includes computer processor responding to the determination that the first transaction and the second transaction, within the plurality of transactions, each contains one or more transaction delineation descriptions, and merging the first transaction and the second transaction to create a merged transaction combination and merging also includes combining two or more table-scan operations.

Merging database operations for serializable transaction execution

A method, system and computer program product for providing consolidated access to data of a plurality of source databases. Tables of each of the source databases are replicated to a shared accelerator. The source DBMSs are configured to dispatch queries to the accelerator for accelerating query execution. The accelerator is configured such that the replicated tables can only be accessed by the source DBMS having provided said tables for executing a dispatched query. A user can select one of the source DBMSs to act as a consolidated DBMS&#x2014;C-DBMS. The C-DBMS provides the consolidated access. The user is enabled to select tables managed by another one of the DBMSs. In response to receiving the selection of the tables, the accelerator is re-configuring such that the C-DBMS is granted access also to the copies of the selected tables in the accelerator.

Accelerator based data integration

A distributed database system (or federated database system) where a catalogue is used to store metadata descriptive of data containers for the constituent database system(s) and/or accelerator system(s) of the federated database. In response to the generation of the trigger signal corresponding to a database definition language (DDL) statement, the accelerator system updates metadata in the catalogue.

Distributed system with accelerator and catalog

Aspects of the invention include processing queries in a database system having a first database engine and a second database engine. A first instance of a first table is stored in the first database engine in plaintext. At one predefined column of the first table is encrypted, resulting in a set of encrypted columns, using a cascade encryption scheme that includes a set of ordered encryption methods. A subset of the set of columns is stored in a second instance of the first table in the second database engine. An encryption method of the cascade encryption scheme that allows a query operation of a received query on data encrypted with the identified encryption method is identified. The identified encryption method is used to rewrite the query, and the rewritten query is executed using the second instance of the first table.

Processing analytical queries over encrypted data using dynamical decryption

Loading a set of data into a target database management system (DBMS) from a source DBMS to increase workload performance and decrease resource usage is provided. Using a size and a change rate of tables eligible to be offloaded to the target DBMS, a total central processor unit (CPU) cost corresponding to loading the set of data into to the target DBMS and workload cost savings corresponding to executing one or more workloads on the target DBMS is determined based on a set of one or more load strategies. The total CPU cost is compared with the workload cost savings of each load strategy. An optimal load strategy is selected based on comparing the total CPU cost with the workload cost savings of each load strategy. The set of data is automatically loaded into to the target DBMS from the source DBMS in accordance with the selected optimal load strategy.

Automatically optimizing resource usage on a target database management system to increase workload performance

A method for executing a computational task in a data management system is provided. The method includes storing a first stored procedure in a first database management system (DBMS) including first data containers. The first stored procedure receives names of one or more of the first data containers to act as input or output data containers and includes first statements for triggering resolution of features of a respective first input or output data container. The method also includes storing a second stored procedure in a second DBMS including second data containers. The second stored procedure implements the computational task and operates on one or more of the second data containers. The method also includes receiving, by the first DBMS, a request from a client application to perform the computational task.

Task-execution in a DBMS using stored procedures

Securing invocation of stored procedures is provided herein. A first database management system (DBMS) can include a first database with first tables, a first user management module configured to manage privileges of database users (DB-users) of the first DBMS, and at least one first stored procedure. A second DBMS can include a second database with second tables, a second user management module configured to manage privileges of DB-users of the second DBMS, and at least one second stored procedure, the at least one second stored procedure configured to perform a computational task in the second DBMS. A synchronization mapping can map at least a portion of the first tables to respective ones of the second tables. Thus, a transfer of data of at least some of the first tables to the respective ones of the second tables in accordance with the synchronization-mapping can be performed.

Secure invocation of stored procedures in database management systems

A distributed database system (or federated database system) where a catalog is used to store metadata descriptive of data containers for the constituent database system(s) and/or accelerator system(s) of the federated database. In response to the generation of the trigger signal corresponding to a database definition language (DDL) statement, the accelerator system updates metadata in the catalog.

Growing community of inventors

Holzgerlingen, Germany

Peter Bendel