Sap Se

Sap Ag

Gregor Hackenbroich

Johannes Meinecke

Lars Dannecker

Hong-Hai Do

Juergen Anke

Jeremie Brunet

Simon Moscrop

Paul Binks

Dave Parsons

Anisoara Nica

Zbigniew Jerzak

Jan Rittinger

Yuanzhen Ji

Richard Pilz

Anja Klein

Franz Josef Grueneberger

Katja Pfeifer

Mario Neugebauer

Bernhard Wolf

Tom Spiegler

Adrian Mocan

Marlo Neugebauer

Thomas Beck

Anja Jugel

Sead Pozderac

Jan Schole

Julian Harttung

Eric Peuckert

Jürgen Anke

The present disclosure involves systems, software, and computer implemented methods for automatically extending a partially-editable dataset copy. One example method includes identifying, for a data set, extension filter criteria that extends a current filter that defines an editable portion of the data set. An extended filter is automatically generated for the data set based on the extension filter criteria and the current filter. Additional data is copied into the partially-editable copy of the data set based on the extended filter and the current filter to generate an updated partially-editable copy of the data set. The current filter is replaced with the extended filter to create a new current filter. An updated exposed view is generated using the new current filter that exposes the updated partially-editable copy of the data set and an updated non-editable portion of the data set.

Automatic extension of a partially-editable dataset copy

The present disclosure involves systems, software, and computer implemented methods for automatically generating a partially-editable dataset copy. One example method includes receiving an edit request from a user to edit a data set. A filter for the data set is determined, based on a context of the edit request. The filter is used to generate a partially-editable copy of the data set that includes the editable portion of the data set. An exposed view of the data set is generated that exposes the partially-editable copy of the data set and a non-editable portion of the data set. The exposed view of the data set is provided to the user and a change to a data item in the editable portion of the data set is received. The data item in the partially-editable copy of the data set is updated based on the change.

Efficient support for automatic generation of a partially-editable dataset copy

The present disclosure involves systems, software, and computer implemented methods for providing quality-driven processing of out-of-order data streams based on a configurable quality metric. In one example, the method includes identifying a configurable quality metric defined by a user or application for executing continuous queries over a sliding window, the metric specifying a user requirement for the quality of the continuous query result. A quality threshold metric is calculated based on the configurable quality metric, the configurable quality metric associated with a size of an adaptation buffer for incoming tuples of the query. In response to receiving a signal indicating a new query result, a sliding window prior to a current time is identified. A runtime quality metric associated with the incoming tuples for the sliding window is measured, and the adaptation buffer is modified based on a difference between the quality threshold metric and the measured runtime quality metric.

Quality-driven processing of out-of-order data streams

The present disclosure involves systems, software, and computer implemented methods for optimizing continuous queries for hybrid execution over a stream processing engine and an in-memory database. In one example, a method may include identifying a continuous query executed at a stream processing engine, the continuous query including a plurality of operators. An optimal plan for execution of the identified continuous query at the stream processing engine is determined. For each of the plurality of operators in the determined optimal plan, an optimized placement decision for executing a particular operator in the stream processing engine or at a database system is determined. An optimized continuous query is generated from the identified continuous query based on the determined optimal placement decisions for each of the plurality of operators in the determined optimal plan. The optimized continuous query is then executed at the stream processing engine and the database system.

Optimization of continuous queries in hybrid database and stream processing systems

Allocation within a database environment is performed by processing a sequence of steps, each of which is described by an allocation processing block. The allocation processing block receives three inputs (input tables or input view) and computes a result. Related apparatus, systems, techniques and articles are also described.

Flexibly performing allocations in databases

A reallocation processing block including a computing system including one or more data processors receives a base table, a reference table, and at least one assignment path table. Subsequently, rules from the at least one assignment path table are applied to the base table and the reference table by reallocating values between at least two existing data objects. A results table is generated with the reallocated values in the at least two existing data objects. A reallocated value is compared with a threshold value to determine the need for an iteration. At least one of the activities described is implemented using at least one data processor. Related apparatus, systems, techniques and articles are also described.

Flexibly performing reallocations in databases

An enhanced data conversion framework, in which a data record in each of first and second data sources is populated with manually selected, representative sample data, the first and second data sources using different data storage schemas to store the representative sample data as instance values of instance elements. Parameters for afunction or anfunction are automatically determined based on a selected succession graph, and non-sample data is converted between the different data storage schemas of the first and second data sources, using thefunction or thefunction.

Enhanced data conversion framework

A method and system are described for including data quality in data streams. An example method may include obtaining a first group of data items, each data item including one or more data attribute values. A first group of data quality items may be determined, each data quality item including one or more data quality attribute values associated with one of the data items of the first group. A first aggregated data quality value may be determined based on the first group of data quality items. A first data stream interval including the first group of data items and the first aggregated data quality value may be output.

Method and system for including data quality in data streams

A method and system are described for managing data quality. An example method may include obtaining a first data stream interval including a first group of data items and a first aggregated data quality value associated with a quality of obtaining the first group, each data item including data attribute values, each data quality item including data quality attribute values associated with one of the data items. The first aggregated data quality value, a first indicator associating the first aggregated data quality value with the first group, and the first group may be selected. The first group and the first indicator may be stored in a user table of a database. A data quality table associated with the user table may be determined based on an entry in a system table. The first aggregated data quality value and the first indicator may be stored in the data quality table.

Method and system for managing data quality

A remote device having the ability to transmit data across a plurality of wireless channels selects the transmission channel for transmitting the data message. The remote device prioritizes the data message based on an examination of the data message relative to predetermined priority settings. Based on this prioritization and in relation to a transmission prediction term, the remote device assigns the data message to a message queue associated with the selected transmission channel. When the remote device enters the transmission range of the selected channel, the data message may thereupon be wirelessly transmitted.

Channel selection for wireless transmission from a remote device

Prioritized transmission of data from a mobile device, where the mobile device includes the ability to transmit data using more than one transmission medium, includes generating data packets from sensor data. The data packet is then assigned a priority level based on the sensor data and various factors relating to the transmission mediums. The priority level may be assigned based on the transmission availability, bandwidth and cost of using the medium. The data packets, based on the assigned priority level, are then stored in a corresponding priority buffer associated with a transmission device using one of the transmission mediums. When available, the transmission device may then readily transmit the data packet from the priority buffer. Therefore, the data is transferred in a prioritized order based, in part, on the transmission medium and factors relating to the medium, as well as the sensor data being transmitted.

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Dresden, Germany

Gregor Hackenbroich