Abstract: Systems and methods for generating distributed dataflow graphs and processing data elements in parallel utilizing the distributed dataflow graphs are provided. A sequential dataflow graph is formed from incoming data elements, and a variety of heuristics is applied to the sequential dataflow graph to determine which of the data transformation steps within the graph are capable of being processed multiple times in parallel. Once determined, the sequential dataflow graph is divided into subgraphs, which are then replicated, e.g., based on available resources and.or external constraints. The resulting subgraphs are connected, based on the semantics of each vertex, and a distributed dataflow graph is generated, which can efficiently process data elements, for instance, for data warehousing and the like.

Abstract: A system, method, and related techniques are disclosed for processing data across a distributed network to a plurality of machines. The method may include receiving a first user-supplied transform and generating a first package based on the first user-supplied transform. The method may further include receiving a designated key and generating a second package based on the key. Furthermore, the method may include receiving a second user-supplied transform and generating a third package based on the second user-supplied transform. Moreover, the method may include distributing the first, second, and third packages to a plurality of machines using a cluster API.

Abstract: Systems and methods for generating distributed dataflow graphs and processing data elements in parallel utilizing the distributed dataflow graphs are provided. A sequential dataflow graph is formed from incoming data elements, and a variety of heuristics is applied to the sequential dataflow graph to determine which of the data transformation steps within the graph are capable of being processed multiple times in parallel. Once determined, the sequential dataflow graph is divided into subgraphs, which are then replicated, e.g., based on available resources and.or external constraints. The resulting subgraphs are connected, based on the semantics of each vertex, and a distributed dataflow graph is generated, which can efficiently process data elements, for instance, for data warehousing and the like.

Abstract: A system, method, and related techniques are disclosed for processing data across a distributed network to a plurality of machines. The method may include receiving a first user-supplied transform and generating a first package based on the first user-supplied transform. The method may further include receiving a designated key and generating a second package based on the key. Furthermore, the method may include receiving a second user-supplied transform and generating a third package based on the second user-supplied transform. Moreover, the method may include distributing the first, second, and third packages to a plurality of machines using a cluster API.