Abstract: In an example embodiment performance is optimized in a complex event stream (CEP) system. Information about a plurality of CEP threads is obtained. Then nearness among the plurality of CEP threads is determined, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread. Based on the determined nearness, the plurality of CEP threads are organized into a plurality of CEP thread groups. Then, each of the plurality of CEP thread groups are assigned to a different processing node, with each processing node having one or more processors and a memory.

Abstract: Methods, systems, computer program products, and articles of manufacture for processing events are described. An event is obtained and the event is processed to generate data using a first set of one or more operators. The generated data is stored in a first column store with a first row/transaction identifier and the first row/transaction identifier is stored in one or more first processing queues to enable further processing of the event using a second set of one or more operators.

Abstract: In an example embodiment performance is optimized in a complex event stream (CEP) system. Information about a plurality of CEP threads is obtained. Then nearness among the plurality of CEP threads is determined, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread. Based on the determined nearness, the plurality of CEP threads are organized into a plurality of CEP thread groups. Then, each of the plurality of CEP thread groups are assigned to a different processing node, with each processing node having one or more processors and a memory.

Abstract: Disclosed herein are system, method, and computer program product embodiments for stream optimized data processing. An embodiment operates by receive a stream of data in a streaming data format. A query associated both with the stream of data and one or more records of a database is determined. It is determined whether the one or more records of the database are stored in a local cache. Those records not stored in the local cache are retrieved from the database and converted into the streaming data format. A query response, including references to each of the one or more records stored in the local cache in the streaming data format, is provided for execution of the query.

Abstract: In an example embodiment, performance is optimized in a complex event stream (CEP) system. Information about a plurality of CEP threads is obtained. Then nearness among the plurality of CEP threads is determined, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread. Based on the determined nearness, the plurality of CEP threads are organized into a plurality of CEP thread groups. Then, each of the plurality of CEP thread groups are assigned to a different processing node, with each processing node having one or more processors and a memory.

Abstract: Disclosed herein are system, method, and computer program product embodiments for stream optimized data processing. An embodiment operates by receive a stream of data in a streaming data format. A query associated both with the stream of data and one or more records of a database is determined. It is determined whether the one or more records of the database are stored in a local cache. Those records not stored in the local cache are retrieved from the database and converted into the streaming data format. A query response, including references to each of the one or more records stored in the local cache in the streaming data format, is provided for execution of the query.

Abstract: In an example embodiment, event stream processing is performed by first parsing an input query into a directed acyclic graph (DAG) including a plurality of operator nodes. Then a grouping of one or more of the operator nodes is created. One or more partitions are created, either by the user or automatically, in the DAG by forming one or more duplicates of the grouping. A splitter node is created in the DAG, the splitter node splits data from one or more event streams and distributes it among the grouping and the duplicates of the grouping. Then, the input query is resolved by processing data from one or more event streams using the DAG.

Abstract: Methods, systems, computer program products, and articles of manufacture for processing events and managing a database, are described. The events may be processed and the database may be managed using the same administrative tools. A database operation is performed based on a database query statement being a database operation statement type and an event processing project is managed based on the database query statement being a non-database operation statement type.

Abstract: Methods, systems, computer program products, and articles of manufacture for processing events are described. An event is obtained and the event is processed to generate data using a first set of one or more operators. The generated data is stored in a first column store with a first row/transaction identifier and the first row/transaction identifier is stored in one or more first processing queues to enable further processing of the event using a second set of one or more operators.

Abstract: In an example embodiment, performance is optimized in a complex event stream (CEP) system. Information about a plurality of CEP threads is obtained. Then nearness among the plurality of CEP threads is determined, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread. Based on the determined nearness, the plurality of CEP threads are organized into a plurality of CEP thread groups. Then, each of the plurality of CEP thread groups are assigned to a different processing node, with each processing node having one or more processors and a memory.

Abstract: In an example embodiment, event stream processing is performed by first parsing an input query into a directed acyclic graph (DAG) including a plurality of operator nodes. Then a grouping of one or more of the operator nodes is created. One or more partitions are created, either by the user or automatically, in the DAG by forming one or more duplicates of the grouping. A splitter node is created in the DAG, the splitter node splits data from one or more event streams and distributes it among the grouping and the duplicates of the grouping. Then, the input query is resolved by processing data from one or more event streams using the DAG.

Abstract: Methods, systems, and computer program products for generating executable computer code in an extensible format are provided. A computer-implemented method may include receiving computer source code for compilation and compiling the source code, to generate executable computer code in an extensible format that includes instructions for execution by a computer system configured to process the instructions in the extensible format.

Abstract: Methods, systems, and computer program products for generating executable computer code in an extensible format are provided. A computer-implemented method may include receiving computer source code for compilation and compiling the source code, to generate executable computer code in an extensible format that includes instructions for execution by a computer system configured to process the instructions in the extensible format.