Growing Rate Of Incoming Streaming Data Essay - 922 Words

1.4.5 SCALABILITY Growing rate of incoming streaming data is indefinite. Even though the arrival rate of update transactions are not predefined, system processor has to adapt the stream data flow as it grows continuously. Adaptive Stream Query Processor is designed and implemented to execute continuous queries and to adapt indefinite data flow by clustering, proper indexing so as to reduce the storage space and fast retrieval of streaming data. STREAM PROCESSOR Streaming processing is the ideal platform to process data streams. Stream processing is designed to analyze and act on real-time streaming data, using continuous queries i.e. SQL-type queries that operate over time and buffer windows. Essential to stream analytics is Stream Processing, or the ability to continuously calculate mathematical or statistical analytics on the fly within the stream. Stream processing solutions are designed to handle high volume in real time with a scalable, highly available and fault tolerant architecture. This enables analysis of data in motion. Finally query processing is used to retrieve useful information from the stream data. A Stream Query Processor is proposed to achieve fast retrieval of streaming data. Stream Query Processor architecture is represented in Fig. 1.2. volume Figure 1.2 Stream Processor Input data are arriving as stream continuously. The incoming data are time-variant and embedded with timestamp. Hence, timestamp is used as one of the attribute along withShow MoreRelatedMiddleware Framework For Streaming Data Essay998 Words   |  4 PagesMiddleware framework for Streaming data Online Stock market data has taken as streaming data for experimentation. Web produces continuous stream of data through online financial trading. Streaming data has collected in the form of web interface. Timestamp is embedded with incoming data. 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