Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: A powered handle for a surgical stapler can have a drive system including an electric motor. The powered handle can include a manual return mechanism. The powered handle can also include a retention mechanism to prevent unintentional movement of drivetrain components upon actuation of the manual return mechanism. For example, the retention mechanism can apply a direction-dependent frictional force on an actuation shaft of the handle assembly to prevent unintentional movement of the actuation shaft towards a distal end of the handle assembly. The retention mechanism can include a featherboard-like configuration with a plurality of ribs oriented transversely to the actuation shaft to restrict movement of the actuation shaft in one direction while allowing movement of the shaft in the opposite direction.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: A method includes receiving data corresponding one of streaming data or batch data and a content of the received data for computation. The method also includes determining an event time of the data for slicing the data, determining a processing time to output results of the received data, and emitting at least a portion of the results of the received data based on the processing time and the event time.

Abstract: A job that receives as input a data stream is executed. For the job, it is iteratively determined a backlog growth over a first period of time; a backlog volume; and whether to adjust a quantity of processing resources. For each iteration for which the quantity of processing resources allocated to the job are determined to be adjusted, adjusting the quantity of processing resources allocated to the job. For each iteration for which the quantity of processing resources allocated to the job are determined not to be adjusted, maintaining the quantity of processing resources allocated to the job.

Abstract: An earth-boring tool includes a body having a shank and a crown, a plurality of blades protruding from the crown of the body and extending at least substantially along a longitudinal length of the crown of the body, each blade extending radially outward and defining a respective radially outermost gage surface. The earth-boring tool further includes at least one rotatable cutting structure assembly including a leg and a rotatable cutting structure rotatably coupled to the leg. The earth-boring tool also includes at least one stabilizing structure secured to the crown of the body between an end of the leg opposite the rotatable cutting structure and the shank of the body, the at least one stabilizing structure being at least substantially circumferentially aligned with the leg of the at least one rotatable cutting structure assembly along a circumference of the crown of the body.

Abstract: One example method includes identifying synchronous code including instructions specifying a computing operation to be performed on a set of data; transforming the synchronous code into a pipeline application including one or more pipeline objects; identifying a first input data set on which to execute the pipeline application; executing the pipeline application on a first input data set to produce a first output data set; after executing the pipeline application on the first input data set, identifying a second input data set on which to execute the pipeline application; determining a set of differences between the first input data set and second input data set; and executing the pipeline application on the set of differences to produce a second output data set.

Abstract: A job that receives as input a data stream is executed. For the job, it is iteratively determined a backlog growth over a first period of time; a backlog volume; and whether to adjust a quantity of processing resources. For each iteration for which the quantity of processing resources allocated to the job are determined to be adjusted, adjusting the quantity of processing resources allocated to the job. For each iteration for which the quantity of processing resources allocated to the job are determined not to be adjusted, maintaining the quantity of processing resources allocated to the job.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: An earth-boring tool includes a body having a shank and a crown, a plurality of blades protruding from the crown of the body and extending at least substantially along a longitudinal length of the crown of the body, each blade extending radially outward and defining a respective radially outermost gage surface. The earth-boring tool further includes at least one rotatable cutting structure assembly including a leg and a rotatable cutting structure rotatably coupled to the leg. The earth-boring tool also includes at least one stabilizing structure secured to the crown of the body between an end of the leg opposite the rotatable cutting structure and the shank of the body, the at least one stabilizing structure being at least substantially circumferentially aligned with the leg of the at least one rotatable cutting structure assembly along a circumference of the crown of the body.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: A data parallel pipeline may specify multiple parallel data objects that contain multiple elements and multiple parallel operations that operate on the parallel data objects. Based on the data parallel pipeline, a dataflow graph of deferred parallel data objects and deferred parallel operations corresponding to the data parallel pipeline may be generated and one or more graph transformations may be applied to the dataflow graph to generate a revised dataflow graph that includes one or more of the deferred parallel data objects and deferred, combined parallel data operations. The deferred, combined parallel operations may be executed to produce materialized parallel data objects corresponding to the deferred parallel data objects.

Abstract: One example method includes identifying synchronous code including instructions specifying a computing operation to be performed on a set of data; transforming the synchronous code into a pipeline application including one or more pipeline objects; identifying a first input data set on which to execute the pipeline application; executing the pipeline application on a first input data set to produce a first output data set; after executing the pipeline application on the first input data set, identifying a second input data set on which to execute the pipeline application; determining a set of differences between the first input data set and second input data set; and executing the pipeline application on the set of differences to produce a second output data set.

Abstract: A method includes receiving data corresponding one of streaming data or batch data and a content of the received data for computation. The method also includes determining an event time of the data for slicing the data, determining a processing time to output results of the received data, and emitting at least a portion of the results of the received data based on the processing time and the event time.

Abstract: One example method includes identifying synchronous code including instructions specifying a computing operation to be performed on a set of data; transforming the synchronous code into a pipeline application including one or more pipeline objects; identifying a first input data set on which to execute the pipeline application; executing the pipeline application on a first input data set to produce a first output data set; after executing the pipeline application on the first input data set, identifying a second input data set on which to execute the pipeline application; determining a set of differences between the first input data set and second input data set; and executing the pipeline application on the set of differences to produce a second output data set.