Abstract: The data transformation system in one embodiment, comprises a capability to receive data, a data destination and a capability to store transformed data, and a data transformation pipeline that constructs complex end-to-end data transformation functionality by pipelining data flowing from one or more sources to one or more destinations through various interconnected nodes for transforming the data as it flows. Each component in the pipeline possesses predefined data transformation functionality, and the logical connections between components define the data flow pathway in an operational sense. The data transformation pipeline enables a user to develop complex end-to-end data transformation functionality by graphically describing and representing, via a GUI, a desired data flow from one or more sources to one or more destinations through various interconnected nodes (graph).

Abstract: The data transformation system in one embodiment, comprises a capability to receive data, a data destination and a capability to store transformed data, and a data transformation pipeline that constructs complex end-to-end data transformation functionality by pipelining data flowing from one or more sources to one or more destinations through various interconnected nodes for transforming the data as it flows. Each component in the pipeline possesses predefined data transformation functionality, and the logical connections between components define the data flow pathway in an operational sense. The data transformation pipeline enables a user to develop complex end-to-end data transformation functionality by graphically describing and representing, via a GUI, a desired data flow from one or more sources to one or more destinations through various interconnected nodes (graph).

Abstract: The data transformation system in one embodiment, comprises a capability to receive data, a data destination and a capability to store transformed data, and a data transformation pipeline that constructs complex end-to-end data transformation functionality by pipelining data flowing from one or more sources to one or more destinations through various interconnected nodes for transforming the data as it flows. Each component in the pipeline possesses predefined data transformation functionality, and the logical connections between components define the data flow pathway in an operational sense. The data transformation pipeline enables a user to develop complex end-to-end data transformation functionality by graphically describing and representing, via a GUI,a desired data flow from one or more sources to one or more destinations through various interconnected nodes (graph).

Abstract: Various embodiments of the present invention are directed to the creation of multiple redundant chains of transforms, each on a separate processing thread, for a data flow execution (DFE) of a data transformation pipeline (DTP). For certain of these embodiments, a “distributor” receives a buffer as input and directs that buffer to one of several parallel identical threads to process that buffer. A scheduler would create each of these multiple threads, each thread having an identical (redundant) strings of transforms (chains) downstream from the distributor, and all of which would lead even further downstream to a collector that is responsible for collecting and, if necessary, ordering the buffers processed by the previous redundant chains. In this way, the distributors and collectors provide increased scalability for the pipeline by implicitly partitioning (distributing) individual buffers to one of many threads for at least a part of their execution/processing.

Abstract: Various embodiments of the present invention are directed to a unique memory management scheme utilized by the DTP whereby data extracted from an external source is placed in a memory buffer and is then manipulated by the components without the need for copying the data to any other location in memory. While logically the data moves from component to component in the DFE for the various embodiments described herein, the data does not in fact change locations but, instead, the data resides in the buffer and is operated upon by a series of components that, in turn, access the data in the buffer via pointers and manipulate same.

Abstract: Various embodiments of the present invention are directed to the creation of multiple redundant chains of transforms, each on a separate processing thread, for a data flow execution (DFE) of a data transformation pipeline (DTP). For certain of these embodiments, a “distributor” receives a buffer as input and directs that buffer to one of several parallel identical threads to process that buffer. A scheduler would create each of these multiple threads, each thread having an identical (redundant) strings of transforms (chains) downstream from the distributor, and all of which would lead even further downstream to a collector that is responsible for collecting and, if necessary, ordering the buffers processed by the previous redundant chains. In this way, the distributors and collectors provide increased scalability for the pipeline by implicitly partitioning (distributing) individual buffers to one of many threads for at least a part of their execution/processing.

Abstract: Various embodiments of the present invention are directed to a unique memory management scheme utilized by the DTP whereby data extracted from an external source is placed in a memory buffer and is then manipulated by the components without the need for copying the data to any other location in memory. While logically the data moves from component to component in the DFE for the various embodiments described herein, the data does not in fact change locations but, instead, the data resides in the buffer and is operated upon by a series of components that, in turn, access the data in the buffer via pointers and manipulate same.

Abstract: The data transformation system (DTS) in one embodiment of the present invention comprises a capability to receive data from a data source, a data destination and a capability to store transformed data therein, and a data transformation pipeline (DTP) that constructs complex end-to-end data transformation functionality (data flow executions or DFEs) by pipelining data flowing from one or more sources to one or more destinations through various interconnected nodes (that, when instantiated, become components in the pipeline) for transforming the data as it flows by (where the term transforming is used herein to broadly describe the universe of interactions that can be conducted to, with, by, or on data). Each component in the pipeline possesses specific predefined data transformation functionality, and the logical connections between components define the data flow pathway in an operational sense.