Clone the repository into CloudxLab directory under your home directory in the web console. To stop the computation we define ssc.awaitTermination() To start the computation we define, ssc.start(). Up to this point, we have just defined the computation steps. Now we print words and their count to the console, which are calculated every 10 seconds. Next, we map the "word" DStream to a DStream of (word, 1) pairs and reduce it to get the frequency of the word in each batch of data. Please note that since we have applied high-level DStream operation flatMap to "lines" DStream, "words" will also be a DStream. Next, we split each line in each batch into words. Each record in line DStream is a line of text It represents batches of data with each batch having 10 seconds of data. "lines" DStream represents the stream of data that will be received from the server. Using this context, we create a DStream that represents streaming data from a server, which runs on localhost and port 9999. Streaming context is the main entry point for all streaming functionality.
#Download spark and run wordcount example code
Since we will run this code in spark-shell, spark context will be available as "sc" variable. Batch interval of 10 seconds means spark streaming creates batches with 10 seconds of data from input stream. Then we create a local StreamingContext with a batch interval of 10 seconds. Let's look at the code.įirst, we import the Spark Streaming libraries.
We've provided the code on CloudxLab GitHub repository. To simulate the above scenario, on one console, we run a server which generates data and on the second console we run Spark streaming code which listens to this server and count the words.
This data becomes input data stream to Spark streaming and then spark engine count the words in the batches. There is a data server which runs on a port and produces data.
How do we write such a program? Let's understand it. Let's say we want to count the number of words continuously in the text data received from a server listening on a host and a port Let's take a quick look at what a Spark Streaming program looks like and do a hands-on. Apache Spark - Streaming - Wordcount Hands-On
0 kommentar(er)
