I want to make a request to find the most busy time of the day on average in 1-hour intervals.
I have on my dataframe the row date in format "%d/%b/%Y:%H:%M:%S".
I begin like that:
mostBusyTimeDF = logDF.groupBy("date") ...
For example input:
date
2015-12-01 21:04:00
2015-12-01 10:04:00
2015-12-01 21:07:00
2015-12-01 21:34:00
In output :
date count(1 hour interval)
2015-12-01 21:04:00 3
2015-12-01 10:04:00 1
After I don't know how can I do it..
Can you help me?
Thanks a lot
You can use built-in Spark date functions:
from pyspark.sql.functions import *
logDF = sqlContext.createDataFrame([("2015-12-01 21:04:00", 1), ("2015-12-01 10:04:00", 2), ("2015-12-01 21:07:00", 9), ("2015-12-01 21:34:00", 1)], ['somedate', 'someother'])
busyTimeDF = logDF.groupBy(year("somedate").alias("cnt_year"), \
month("somedate").alias("cnt_month"), \
dayofmonth("somedate").alias("cnt_day"), \
hour('somedate').alias("cnt_hour")) \
.agg(functions.count("*").alias("cntHour"))
cond = [busyTimeDF.cnt_year == year(logDF.somedate), \
busyTimeDF.cnt_month == month(logDF.somedate), \
busyTimeDF.cnt_day == dayofmonth(logDF.somedate), \
busyTimeDF.cnt_hour == hour(logDF.somedate)]
busyTimeDF.join(logDF, cond).select('somedate', 'cntHour').show()