Hasso-plattner-institut Fur Softwaresystemtechnik Gmbh

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Hasso-plattner-institut F&#xfc;r Softwaresystemtechnik Gmbh

Hasso-plattner Institut Fuer Softwaresystemtechnik Gmbh

Hasso-plattner-institut F&#xfc;r Digital Engineering Ggmbh

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Hasso-platner-institut Fuer Softwaresystemtechnik Gmbh

Hasso-plattner-institut Fur Softwaresytemtechnik Gmbh

Hasso Plattner

Alexander Zeier

Jens Krueger

Jan Schaffner

Anja Bog

Stephan Mueller

Martin Grund

Matthieu-Patrick Schapranow

Rainer Schlosser

Matthias Uflacker

Mueller Juergen

Juergen Mueller

Emanuel Ziegler

Martin Boissier

Jan Kossmann

Christian Tinnefeld

Sebastian Hillig

Anisoara Nica

Tim Januschowski

John M Wilson, Iii

Michael Good

Michael Perscheid

Alexander Kastius

Keith Elliott

Johannes Wust

Kok Thim Chew

Janek Schumann

Cafer Tosun

Christian Schwarz

Matthieu Schapranow

John Iii Wilson

A system includes a relational database management system component and a column-oriented data processing component. The relational database system component stores database information in a row format. The column-oriented data processing component stores the database information in a column format. In response to a database update request, the relational database management system component updates the database information stored in the row format; the relational database management system component notifies the column-oriented data processing component of the database update request; and the column-oriented data processing component updates the database information stored in the column format. In response to a query request, the column-oriented data processing component generates a query response based on the database information stored in the column format. In this manner, the system is able to generate up-to-date reports without the need for extraction, translation and loading procedures.

ETL-less zero-redundancy system and method for reporting OLTP data

The inventors have implemented in a columnar in-memory database and studied access patterns of a large production enterprise system. To obtain accurate cost estimates for a configuration, the inventors have used the what-if capabilities of modern query optimizers. What-if calls, however, are the major bottleneck for most index selection approaches. Hence, a major constraint is to limit the number of what-if optimizer calls. And even though the inventive approach does not limit the index candidate set, it decreases the number of what-if calls because in each iteration step the number of possible (index) extensions is comparably small which results in a limited number of what-if calls.

Iterative multi-attribute index selection for large database systems

Embodiments relate to a method for training an index selection agent for iteratively determining an index set I to be used when running queries against a database, the method being implemented in a computer system. Preferably, the index selection agent is based on Reinforcement Learning.

Training an agent for iterative multi-attribute index selection

A system includes a relational database management system component and a column-oriented data processing component. The relational database system component stores database information in a row format. The column-oriented data processing component stores the database information in a column format. In response to a database update request, the relational database management system component updates the database information stored in the row format; the relational database management system component notifies the column-oriented data processing component of the database update request; and the column-oriented data processing component updates the database information stored in said column format. In response to a query request, the column-oriented data processing component generates a query response based on the database information stored in said column format. In this manner, the system is able to generate up-to-date reports without the need for extraction, translation and loading procedures.

Computer-implemented method for allocating columns of a table stored in a database system into at least two sets of columns, a first set and a second set, the data of the columns allocated to the first set being stored on a primary storage medium using a column-oriented data structure and the data of columns allocated to the second set being stored on a secondary storage medium using a row-oriented data structure, wherein the method comprises the step of allocating the columns of the table to the first and the second set autonomously on the basis of a performance-cost model.

Data placement in hybrid data layouts for tiered HTAP databases

A system and a method for analyzing and evaluating genome data in the course of personalized medicine. In-memory technology is provided for processing of genome data and its real-time analysis as a holistic process in the course of personalized medicine. The cloud application helps physicians and researchers to identify the genetic roots for certain tumor types in the treatment of diseases correlating to genomic variants or mutations, such as cancer diseases. The system combines the latest international research results with patient-specific genomic data while eliminating the need for long-lasting manual searches of all dispositions in distributed international research and literature data sources.

System for genomic data processing with an in-memory database system and real-time analysis

A high performance, low-cost, gapped read alignment algorithm is disclosed that produces high quality alignments of a complete human genome in a few minutes. Additionally, the algorithm is more than an order of magnitude faster than previous approaches using a low-cost workstation. The results are obtained via careful algorithm engineering of the seeding based approach. The use of non-hashed seeds in combination with techniques from search engine ranking achieves fast cache-efficient processing. The algorithm can also be efficiently parallelized. Integration into an in-memory database infrastructure (IMDB) leads to low overhead for data management and further analysis.

Efficient genomic read alignment in an in-memory database

The present invention provides methods and system, including computer program products, implementing and using techniques for providing tasks of different classes with access to CPU time provided by worker threads of a database system. In particular, the invention relates to such a database-system-implemented method comprising the following steps: inserting the tasks to a queue of the database system; and executing the tasks inserted to the queue by worker threads of the database system according to their order in the queue; characterized in that the queue is a priority queue; and in that the method further comprises the following steps: assigning each class to a respective priority; and in that the step of inserting the tasks to the queue includes: associating each task with the respective priority assigned to its class.

Dynamic task prioritization for in-memory databases

A federated in-memory database system (FIMDB) and a method for operating the same. The system comprises: A plurality of interconnected computing sites (LS), each installed with a local in-memory database instance, which is configured to connect to a FIMDB landscape instance; central computing infrastructure, provided by a service provider (SP), which grants access to algorithms managed by the service provider (SP) for execution on local data of the respective consuming computing site (LS); one or more communication channels (LSG, LSG), which are specifically adapted for connecting local and remote computing hard- and software via a digital communication channel; and configuration adjuster (CM), which are specifically adapted for configuring local hard- and software to connect to the FIMDB system (FIMDB) and for configuring local hard- and software in order to access algorithms managed by the service provider (SP) and execute them on the local computing hardware.

Cloud-based hardware architecture

The invention relates to a computer system for both online transaction processing and online analytical processing, comprising: a processor coupled to a database, the database comprising the database comprising: a main store () for storing records, a differential buffer () for receiving and buffering added or deleted or modified records, the differential buffer being coupled to the main store, a schema comprising records stored in the main store and records stored in the differential buffer, and a cache store () for caching a result of a query against the schema; and a cache controller () executable by the processor and communicatively coupled to the database, the cache controller being configured for: storing the result of the query in the cache store; receiving an analytical request; and determining, in response to the received request, an up-to-date result of the query by (): accessing the cache store to obtain the cached result; determining the records of the schema that have been added or deleted or modified since the step of storing the cached result in the cache store on the basis of the records stored in the differential buffer; and incrementally deriving the up-to-date result from the cached result and from the records determined in the previous step.

Aggregate query-caching in databases architectures with a differential buffer and a main store

A system includes a relational database management system component and a column-oriented data processing component. The relational database system component stores database information in a row format. The column oriented data processing component stores the database information in a column format. In response to a database update request, the relational database management system component updates the database information stored in the row format; the relational database management system component notifies the column-oriented data processing component of the database update request; and the column-oriented data processing component updates the database information stored in said column format. In response to a query request, the column-oriented data processing component generates a query response based on the database information stored in said column format. In this manner, the system is able to generate up-to-date reports without the need for extraction, translation and loading procedures.

The invention relates to a computer-implemented method for dynamically and horizontally partitioning a table of a relational database, wherein the table comprises records, wherein the records are mapped to a plurality of states, wherein the table is horizontally partitioned into a plurality of partitions, and wherein the plurality of states is mapped to the plurality of partitions. The method comprises the steps of changing the assignment of a first record from a first state to a second state, wherein the first state is mapped to a first partition, wherein the second state is mapped to a second partition, wherein the first partition is not the second partition, and storing the first record in the second partition. The invention further relates to a computer system implementing the abovementioned method for dynamically and horizontally partitioning a table of a relational database.

Lifecycle-based horizontal partitioning

The invention relates to a computer system and a corresponding method and a corresponding computer-readable medium. The computer system is suitable for determining the result of a join. Based on the access pattern of an application, the computer system infers that a particular subjoin is empty. The computer system then excludes the inferred-empty subjoin when performing the join, performing a more efficient and faster database join operation.

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Schriesheim, Germany

Hasso Plattner