Abstract: Some embodiments provide a program executable by a first device in a distributed system. The program publishes a first request for a collaborative operation to a first log of the first device. The program further receives, at the first log, a second request for the same collaborative operation. The second request is requested by a second device in the distributed system. The program also publishes a command to a second log of the first device. The command specifies the collaborative operation, the first device and the second device as participants of the collaborative operation, a first set of operations to be performed by the first device as part of the collaborative operations, and a second set of operations to be performed by the second device as part of the collaborative operation. The program further performs the first set of operations as part of the collaborative operation.

Abstract: Various examples are directed to systems and methods optimizing database queries. A database management system may receive a first query comprising a plurality of query expressions. The database management system may determine that a first expression of the first query is nullable and that the first expression is null preserving. The database management system may generate optimized query code for the first query. The optimized query code may comprise a first code segment and a conditional jump instruction. The first code segment that, when executed by a processor, may cause the processor to perform operations comprising determining a value of the first expression. The conditional jump instruction may, when executed by the processor, cause the processor to perform operations comprising: skipping execution of at least a portion of the first code segment and returning null for the first expression.

Abstract: Disclosed embodiments include generating code from a database query and providing a framework to develop complex data structures and the functions that access those data structures outside of the generated code to access the complex data structures. These data structure functions can be precompiled in order to save compilation time at query runtime, and linked to the generated code in a way that the framework can still inline function calls and apply various optimizations on the linked code.

Abstract: Various examples are directed to systems and methods for utilizing local identifiers in a distributed database system. A database management system server may receive first execution unit data describing a first execution unit of a first database query. The first execution unit data may comprise first operand data describing a set of operands for the first execution unit. The database management system server may determine that the first operand data describes at least one operand from a first partition and at least one operand from a second partition. The database management system server may generate a first set of local identifiers describing rows at the first partition and a first set of local identifiers describing rows at the second partition. The database management system server may execute the first execution unit based at least in part on the first set of local identifiers describing rows at the first partition and the first set of local identifiers describing rows at the second partition.

Abstract: Some embodiments provide a program executable by a first device in a distributed system. The program publishes a first request for a collaborative operation to a first log of the first device. The program further receives, at the first log, a second request for the same collaborative operation. The second request is requested by a second device in the distributed system. The program also publishes a command to a second log of the first device. The command specifies the collaborative operation, the first device and the second device as participants of the collaborative operation, a first set of operations to be performed by the first device as part of the collaborative operations, and a second set of operations to be performed by the second device as part of the collaborative operation. The program further performs the first set of operations as part of the collaborative operation.

Abstract: Executable code is generated for processing a data set in an in-memory database system. The executable code is based on program instructions including a predicate associated with a first part of the data set. The first part of the data set is divided into data sections. A data section comprises a number of data elements corresponding to a number of bit values to be allocated into a register at a processor. The register at the processor is associated with performing single instructions on multiple data. At the processor, the data sections are evaluated iteratively to determine bit vectors to be stored iteratively into the SIMD register. Based on the iteratively stored bit vectors at SIMD register at the processor, result data sets are iteratively determined through invoking data from the data set. The result data sets are provided through the processor for further consumption.

Abstract: Disclosed embodiments include generating code from a database query and providing a framework to develop complex data structures and the functions that access those data structures outside of the generated code to access the complex data structures. These data structure functions can be precompiled in order to save compilation time at query runtime, and linked to the generated code in a way that the framework can still inline function calls and apply various optimizations on the linked code.

Abstract: Various examples are directed to systems and methods for utilizing local identifiers in a distributed database system. A database management system server may receive first execution unit data describing a first execution unit of a first database query. The first execution unit data may comprise first operand data describing a set of operands for the first execution unit. The database management system server may determine that the first operand data describes at least one operand from a first partition and at least one operand from a second partition. The database management system server may generate a first set of local identifiers describing rows at the first partition and a first set of local identifiers describing rows at the second partition. The database management system server may execute the first execution unit based at least in part on the first set of local identifiers describing rows at the first partition and the first set of local identifiers describing rows at the second partition.

Abstract: Various examples are directed to systems and methods optimizing database queries. A database management system may receive a first query comprising a plurality of query expressions. The database management system may determine that a first expression of the first query is nullable and that the first expression is null preserving. The database management system may generate optimized query code for the first query. The optimized query code may comprise a first code segment and a conditional jump instruction. The first code segment that, when executed by a processor, may cause the processor to perform operations comprising determining a value of the first expression. The conditional jump instruction may, when executed by the processor, cause the processor to perform operations comprising: skipping execution of at least a portion of the first code segment and returning null for the first expression.

Abstract: Executable code is generated for processing a request including a predicate associated with a column of a database table. The executable code defines how to process data through a register at the processor associated with single instructions on multiple data. When a number of bit values of the register at the processor is not an aliquot part of a count of rows in the column of the database table, a new column is loaded in the main memory to include the column of the database table and additional number of data elements. The number of bit values of a register section of the register is an aliquot part of a number of elements of the new column. The new loaded column is evaluated iteratively to determine result bit vectors to be loaded in the register. At the processor, result data is determined to correspond to the evaluated section.

Abstract: Executable code is generated for processing a request including a predicate associated with a column of a database table. The executable code defines how to process data through a register at the processor associated with single instructions on multiple data. When a number of bit values of the register at the processor is not an aliquot part of a count of rows in the column of the database table, a new column is loaded in the main memory to include the column of the database table and additional number of data elements. The number of bit values of a register section of the register is an aliquot part of a number of elements of the new column. The new loaded column is evaluated iteratively to determine result bit vectors to be loaded in the register. At the processor, result data is determined to correspond to the evaluated section.

Abstract: Executable code is generated for processing a data set in an in-memory database system. The executable code is based on program instructions including a predicate associated with a first part of the data set. The first part of the data set is divided into data sections. A data section comprises a number of data elements corresponding to a number of bit values to be allocated into a register at a processor. The register at the processor is associated with performing single instructions on multiple data. At the processor, the data sections are evaluated iteratively to determine bit vectors to be stored iteratively into the SIMD register. Based on the iteratively stored bit vectors at SIMD register at the processor, result data sets are iteratively determined through invoking data from the data set. The result data sets are provided through the processor for further consumption.

Abstract: Method, apparatus, and system, including computer program products, implementing and using techniques for time series analysis, wherein the time series exhibit trend and/or seasonality. Model parameters of the time series data are determined by selecting and/or suggesting a most appropriate combination of trend and seasonality of the time series data based on analysis of variances of transformed time series data.

Abstract: Method, apparatus, and system, including computer program products, implementing and using techniques for determining a periodic cycle of time series data. A frequency spectrum of the data is provided. The frequency spectrum is processed using at least one of the following steps, resulting in a processed frequency spectrum: filtering the frequency spectrum for reducing noise of the data, truncating the frequency spectrum at low frequencies, and weighting high frequency contributions over low frequency contributions of the frequency spectrum. A periodic cycle is extracted based on the processed frequency spectrum.

Abstract: Method, apparatus, and system, including computer program products, implementing and using techniques for time series analysis, wherein the time series exhibit trend and/or seasonality. Model parameters of the time series data are determined by selecting and/or suggesting a most appropriate combination of trend and seasonality of the time series data based on analysis of variances of transformed time series data.

Abstract: Method, apparatus, and system, including computer program products, implementing and using techniques for determining a periodic cycle of time series data. A frequency spectrum of the data is provided. The frequency spectrum is processed using at least one of the following steps, resulting in a processed frequency spectrum: filtering the frequency spectrum for reducing noise of the data, truncating the frequency spectrum at low frequencies, and weighting high frequency contributions over low frequency contributions of the frequency spectrum. A periodic cycle is extracted based on the processed frequency spectrum.