Abstract: A method, computer program product, and computer system are disclosed. The method includes determining probability of high data flow event, memory requirements for the high data flow and time to high data flow event by using pattern recognition based on natural language Processing (NLP), machine learning and statistical algorithms. The method applies a configuration to the edge device and network system when the probability of high data flow event is above a predetermined threshold for handling the high data flow event.

Abstract: A method, a computer program product, and a computer system determine a schedule of a sale event for a retailer. The method includes determining a respective gross revenue gain from launching the sale event at a plurality of times. For each time, the method includes determining respective offsetting factors that introduce a respective cost that reduces the respective gross revenue gain and determining a respective net revenue gain based on the respective gross revenue gain and the respective cost associated with the respective offsetting factors. The method includes generating a recommendation of a select one of the times having a highest one of the net revenue gains.

Abstract: A method, computer program product, and computer system are disclosed. The method includes determining probability of high data flow event, memory requirements for the high data flow and time to high data flow event by using pattern recognition based on natural language Processing (NLP), machine learning and statistical algorithms. The method applies a configuration to the edge device and network system when the probability of high data flow event is above a predetermined threshold for handling the high data flow event.

Abstract: A mechanism is provided in a stream computing platform for data stream change detection and model swapping. The mechanism builds a model for each input data stream in a stream computing platform. Each tuple of each given input data stream is tagged with a key corresponding to the given input data stream. The mechanism performs an operation on each input data stream using its corresponding model. The mechanism detects a misdirected input data stream, which is tagged with a key that does not correspond to the misdirected input data stream. The mechanism pauses the misdirected input data stream swaps a model corresponding to the misdirected input data stream with another model corresponding to another paused input data stream.

Abstract: A mechanism is provided in a stream computing platform for data stream change detection and model swapping. The mechanism builds a model for each input data stream in a stream computing platform. Each tuple of each given input data stream is tagged with a key corresponding to the given input data stream. The mechanism performs an operation on each input data stream using its corresponding model. The mechanism detects a misdirected input data stream, which is tagged with a key that does not correspond to the misdirected input data stream. The mechanism pauses the misdirected input data stream swaps a model corresponding to the misdirected input data stream with another model corresponding to another paused input data stream.

Abstract: A mechanism is provided in a stream computing platform for data stream change detection and model swapping. The mechanism builds a model for each input data stream in a stream computing platform. Each tuple of each given input data stream is tagged with a key corresponding to the given input data stream. The mechanism performs an operation on each input data stream using its corresponding model. The mechanism detects a misdirected input data stream, which is tagged with a key that does not correspond to the misdirected input data stream. The mechanism pauses the misdirected input data. stream swaps a model corresponding to the misdirected input data stream with another model corresponding to another paused input data stream.

Abstract: A mechanism is provided in a stream computing platform for data stream change detection and model swapping. The mechanism builds a model for each input data stream in a stream computing platform. Each tuple of each given input data stream is tagged with a key corresponding to the given input data stream. The mechanism performs an operation on each input data stream using its corresponding model. The mechanism detects a misdirected input data stream, which is tagged with a key that does not correspond to the misdirected input data stream. The mechanism pauses the misdirected input data. stream swaps a model corresponding to the misdirected input data stream with another model corresponding to another paused input data stream.