Transform data in spark scala column to row -


this question has answer here:

input dataset: 

customerid customername sun mon tue    1          abc        0   12  10    2          def        10   0   0

required output dataset:

customerid customername day  value     1         abc       sun   0     1         abc       mon   12     1         abc       tue   10     2         def       sun   10     2         def       mon   0     2         def       tue   0

please note, number of "sun mon tue" columns 82 in dataset!

assuming input dataset generated using case class as

case class infos(customerid: int, customername: string, sun: int, mon: int, tue: int)

for testing purpose creating dataset as

import sqlcontext.implicits._ val ds = seq(   infos(1, "abc", 0, 12, 10),   infos(2, "def", 10, 0, 0) ).tods

which should give input dataset

+----------+------------+---+---+---+ |customerid|customername|sun|mon|tue| +----------+------------+---+---+---+ |1         |abc         |0  |12 |10 | |2         |def         |10 |0  |0  | +----------+------------+---+---+---+

getting final required dataset requires create case class as

case class finalinfos(customerid: int, customername: string, day: string, value: int)

final required dataset can achieved doing following

val names = ds.schema.fieldnames  ds.flatmap(row => array(finalinfos(row.customerid, row.customername, names(2), row.sun),   finalinfos(row.customerid, row.customername, names(3), row.mon),   finalinfos(row.customerid, row.customername, names(4), row.tue)))

which should give dataset 

+----------+------------+---+-----+ |customerid|customername|day|value| +----------+------------+---+-----+ |1         |abc         |sun|0    | |1         |abc         |mon|12   | |1         |abc         |tue|10   | |2         |def         |sun|10   | |2         |def         |mon|0    | |2         |def         |tue|0    | +----------+------------+---+-----+

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