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show(truncate=False) #Drop duplicates on selected columns dropDisDF = df.dropDuplicates(["department","salary"]) print("Distinct count of department salary : "+str(dropDisDF.count())) dropDisDF.show(truncate=False) } Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Q6.
Map tasks deal with mapping and data splitting, whereas Reduce tasks shuffle and reduce data. Hadoop can execute MapReduce applications in various languages, including Java, Ruby, Python, and C++. Each daemon runs in a separate Java process in this mode, and all the master and slave services run on a single node.
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