pyspark mapreduce dataframe
df.rdd \
.filter(lambda x: x[1] == "france") \ # only french stations
.map(lambda x: (x[0], x[2])) \ # select station & temp
.mapValues(lambda x: (x, 1)) \ # generate count
.reduceByKey(lambda x, y: (x[0]+y[0], x[1]+y[1])) \ # calculate sum & count
.mapValues(lambda x: x[0]/x[1]) \ # calculate average
.sortBy(lambda x: x[1], ascending = False) \ # sort
.take(100)pyspark mapreduce dataframe
df.rdd \
.filter(lambda x: x[1] == "france") \ # only french stations
.map(lambda x: (x[0], x[2])) \ # select station & temp
.mapValues(lambda x: (x, 1)) \ # generate count
.reduceByKey(lambda x, y: (x[0]+y[0], x[1]+y[1])) \ # calculate sum & count
.mapValues(lambda x: x[0]/x[1]) \ # calculate average
.sortBy(lambda x: x[1], ascending = False) \ # sort
.take(100)Copyright © 2021 Codeinu
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