Given your understanding that streaming algorithms can be either stateless or stateful. Drag and drop the answers that best suit the question. The processing is said to be stateful when An example of statelul processing is An example of stateless processing is A streaming computation is one where no influence on other computation and no tater is maintained in between the procrsing of different data tuples the function will run on each tuple of data as they are ingested Given your understanding of stream processing and its difference with micro-batching. Drag and drop the answers that best suit the question. Mirco batch processing is best suited for applications requiring In pure stream processing, the function will be involved The best example of scenarios for pure streaming versus micro-batching is Pure steam processing is best suited for applications requiring in micro-batch processing, the function will be invoked on each tuple of data as they arrive by the ingestion stage High throughput (procesting a lage number of data in a short period) after a sufficient number of data, tuples have been buflered to form a batch micro-batching for processing live logr of alert systems, while pure streaming for analysing a day's worth of financial events pure streaming for processing He logs or alent systems, while mice-batching analyaing a day's worth of finaticial events Please answer all parts of the question. Given the code snippet below which processes a stream of Twitter feeds, what is the expected output of this streaming program? SSc = new StreamingContext(sc, 1) tweets = TwitterUtils,createStream(ssc, None) status = tweets. mapilambdastatus status. get ext0) words = status. flatMap(lambda status: status.split("7)) hashtags = words filter(lambda word: word.starts With(")") ) hashtagCounts =hashtags: map ( lambda t:(t,1)),reduce . y KeyAndWindow (t+ambdaa,b:a+b),1800,60) sseistart 0 a. Generates, every 30 minutes, the aggregate count of the hashtags over a window of 1 minute. b. Generates the aggregate count of the hashtags over all time c. Generates, every 1 minute, the aggregate count of the hashtags over a window of 30 minutes d. Generates the most popular tweets over all time Given the code snippet below which processes a stream of Twitter feeds, what is the expected output of this streaming program? Note that reduceByKeyAndWindow duration inputs are in seconds ssc = new StreamingContextisc,1) tweets = TwitterUtils. createStream(ssc, None) status e tweets.mapilambdastatus: status. getText0) words = status: flatMap(lambda status: status.split" 7) hashtags = words. filter(lambda word: word startsWith("e a )). hashtagCounts =hashtags map ( lambda t:(t,1)), reduceByKeyAndWindowi(lambda a,b: a+b),3600,300) ssc.start0 a. Generates the aggregate count of the hashtags over all time b. Generates, every 1 hour, the aggregate count of the hashtags over a window of 5 minutes c. Generates, every 5 minutes, the aggregate count of the hashitags over a window of 1 hour d. Generates the most popular tweets over all time
