Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: A database system detects an operation to move a first database object from an in-memory store to a persistence store, wherein the first database object is in either a page-loadable or column-loadable format in the in-memory store, and wherein the first database object comprises a plurality of subcomponents. Each subcomponent of the first database object is examined separately from other subcomponents of the plurality of subcomponents. In response to determining that a first subcomponent of the plurality of subcomponents has a datatype and a compression type supported by a unified persistence format, the first subcomponent is stored in a unified persistence format in the persistence store. In response to determining that a second subcomponent of the plurality of subcomponents has either a datatype or a compression type which is not supported by the unified persistence format, the second subcomponent is stored in a serial persistence format in the persistence store.

Abstract: A method may include receiving a first transaction inserting a record into a database and a second transaction deleting the record from the database. A validity period for the record may be determined based on a first commit time at which the first transaction is committed and a second commit time at which the second transaction is committed. A current table and/or a history table of a system versioned table may be updated to include the record based on the validity period of the record. One or more temporal operations may be performed based on the system versioned table. For example, a time travel operation may be performed to retrieve, based on the system versioned table, one or more records that are valid at a given point in time. Related systems and computer program products are also provided.

Abstract: A database system detects an operation to move a first database object from an in-memory store to a persistence store, wherein the first database object is in either a page-loadable or column-loadable format in the in-memory store, and wherein the first database object comprises a plurality of subcomponents. Each subcomponent of the first database object is examined separately from other subcomponents of the plurality of subcomponents. In response to determining that a first subcomponent of the plurality of subcomponents has a datatype and a compression type supported by a unified persistence format, the first subcomponent is stored in a unified persistence format in the persistence store. In response to determining that a second subcomponent of the plurality of subcomponents has either a datatype or a compression type which is not supported by the unified persistence format, the second subcomponent is stored in a serial persistence format in the persistence store.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: A quick clamping device for securing at least one rail-monitoring element on a rail includes two clamping units that each have two clamping brackets and one clamp. In each case the two clamping brackets are connectable at a first end by the clamp along a clamping axis, such that the clamp, when secured on the rail, engages under the rail foot of the rail. The clamping brackets each have, at a second end, a clamping region which is designed for force-locking arrangement on a rail web of the rail and/or on the rail-monitoring element. The clamping units, as separate elements, can be arranged on the rail to be mutually spaced along a longitudinal extent of the rail. The clamping brackets each have at least one curvature portion that is curved in a plane orthogonal with respect to the clamping axis.

Abstract: A database management system is described that can encode data to generate a plurality of data vectors. The database management system can perform the encoding by using a dictionary. The database management system can adaptively reorder the plurality of data vectors to prepare for compression of the plurality of data vectors. During a forward pass of the adaptive reordering, most frequent values of a data vector of the plurality of data vectors can be moved-up in the data vector. During a backward pass of the adaptive reordering, content within a rest range of a plurality of rest ranges can be rearranged within the plurality of data vectors according to frequencies of the content. The reordering according to frequency can further sort the rest range by value. Related apparatuses, systems, methods, techniques, computer programmable products, computer readable media, and articles are also described.

Abstract: A device determines an intensity of a corrosive ambient atmosphere in a protective housing. The device includes at least two internal sensors designed to detect changes over time in different ambient parameters inside the protective housing, and to generate sensor signals reflecting the changes over time in the different ambient parameters; an evaluation device designed to receive the sensor signals and to evaluate the sensor signals in correlation with one another in order to determine the intensity of the corrosive ambient atmosphere on basis of deviations of the sensor signals, or of a parameter correlated with the sensor signals, from a reference value or reference value range, taking into account a time duration and/or frequency of the deviations; and an output device designed to generate an output signal reflecting the determined intensity of the corrosive ambient atmosphere.

Abstract: A method may include receiving a first transaction inserting a record into a database and a second transaction deleting the record from the database. A validity period for the record may be determined based on a first commit time at which the first transaction is committed and a second commit time at which the second transaction is committed. A current table and/or a history table of a system versioned table may be updated to include the record based on the validity period of the record. One or more temporal operations may be performed based on the system versioned table. For example, a time travel operation may be performed to retrieve, based on the system versioned table, one or more records that are valid at a given point in time. Related systems and computer program products are also provided.

Abstract: In some example embodiments, there may be provided a method including detecting a query operator of a predetermined type requiring a sorting or a scanning responsive to the query operator at a column-oriented database; determining a sorted dictionary at the column-oriented database is eligible for direct access by at least checking that the column-oriented database provides sorted dictionary access and that dictionary collation and a collation of the query operator are the same; when the sorted dictionary is eligible, reading directly from the sorted dictionary a batch of sorted values; and processing, based on the batch sorted values read from the sorted dictionary, the query operator.

Abstract: A system and method for faster access for compressed time series data. A set of blocks are generated based on a table stored in a database of the data platform. The table stores data associated with multiple sources of data provided as consecutive values, each block containing index vectors having a range of the consecutive values. A block index is generated for each block having a field start vector representing a starting position of the block relative to the range of consecutive values, and a starting value vector representing a value of the block at the starting position. The field start vector of the block index is accessed to obtain the starting position of a field corresponding to a first block and to the range of the consecutive values of the first block. The starting value vector is then determined from the block index to determine an end and a length of the field of the first block.

Abstract: A method may include receiving a first transaction inserting a record into a database and a second transaction deleting the record from the database. A validity period for the record may be determined based on a first commit time at which the first transaction is committed and a second commit time at which the second transaction is committed. A current table and/or a history table of a system versioned table may be updated to include the record based on the validity period of the record. One or more temporal operations may be performed based on the system versioned table. For example, a time travel operation may be performed to retrieve, based on the system versioned table, one or more records that are valid at a given point in time. Related systems and computer program products are also provided.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: A method, a system, and a computer program product for placement or storage of data structures in memory/storage locations. A type of a data structure for storing data and a type of data access to the data structure are determined. The type of data access includes a first and a second type of data access. A frequency of each type of access to each type of data structure accessed by a query is determined. Using the determined frequency, a number of first type of data accesses to the data structure is compared to a number of second type of accesses to the data structure. The numbers of first and second types of data access are compared to a predetermined threshold percentage of a total number of data accesses to the data structure. Based on the comparisons, a physical memory location for storing data is determined.

Abstract: System, method, and various embodiments for providing a data access and recommendation system are described herein. An embodiment operates by identifying a column access of one or more data values of a first column of a plurality of columns of a table of a database during a sampling period. A count of how many of the one or more data values are accessed during the column access are recorded. A first counter is incremented by the count. The sampling period is determined to have expired. A load recommendation on how to load data values into the first column based on the first counter is computed. The load recommendation for implementation into the database for one or more subsequent column accesses is provided.

Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Abstract: Disclosed herein are system, method, and computer-program product embodiments for generating a paged and in-memory representation of a database object. An embodiment operates by maintaining in-memory and paged form primitives unique to the database object or a substructure thereof in a database such that the in-memory and paged form primitives are capable of providing the in-memory and paged representations of the database objects, respectively. Thereafter, a load configuration for the database object is determined. Based on the load configuration, the in-memory and/or paged representations of the database object are generated using the in-memory form primitive or the paged form primitive unique to the database object, respectively. Subsequently, the in-memory and/or paged representations of the database object are stored in the database.