Transform CSV Column Values into Single Row









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My data in CSV is like this(Expected Image):
Actual Data



And I want to convert this Data into:
Expected Data
(hivetablename.hivecolumnname = dbtablename.dbtablecolumn)



By joining the multiple Row values into a Single row value like above.



Please note that 'AND' is a Literal between the condition to be built, which would appear until the second last record.



Once the Last Record is reached, Only the condition would appear(xx=yy)



I wish the result to be in SCALA SPARK.

Many thanks in advance!










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  • Could you please share what have you tried so far?
    – ulubeyn
    Nov 9 at 14:40











  • Many thanks for the response. Im a learner so couldnt go much further. Heres what Ive been able to achieve val dfconf= spark.read.option("header", "true").csv("file:///conf.csv").alias("conf"); dfconf.show(10, false) val newDF1 = dfconf.withColumn("Y",lit("1")) val newDF2 = newDF1.withColumn("Z",lit(",")) val newDF3 = newDF2.withColumn("comb",concat($"hivetablename",lit("."),$"hivetablecolumn",lit("="),$"dbtablename",lit("."),$"dbtablecolumn")) newDF3.show() val newDF4 = newDF3.groupBy("Y").agg(collect_set("z").as("combined"))
    – Farhan Soomro
    Nov 9 at 14:51















up vote
0
down vote

favorite












My data in CSV is like this(Expected Image):
Actual Data



And I want to convert this Data into:
Expected Data
(hivetablename.hivecolumnname = dbtablename.dbtablecolumn)



By joining the multiple Row values into a Single row value like above.



Please note that 'AND' is a Literal between the condition to be built, which would appear until the second last record.



Once the Last Record is reached, Only the condition would appear(xx=yy)



I wish the result to be in SCALA SPARK.

Many thanks in advance!










share|improve this question









New contributor




Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.



















  • Could you please share what have you tried so far?
    – ulubeyn
    Nov 9 at 14:40











  • Many thanks for the response. Im a learner so couldnt go much further. Heres what Ive been able to achieve val dfconf= spark.read.option("header", "true").csv("file:///conf.csv").alias("conf"); dfconf.show(10, false) val newDF1 = dfconf.withColumn("Y",lit("1")) val newDF2 = newDF1.withColumn("Z",lit(",")) val newDF3 = newDF2.withColumn("comb",concat($"hivetablename",lit("."),$"hivetablecolumn",lit("="),$"dbtablename",lit("."),$"dbtablecolumn")) newDF3.show() val newDF4 = newDF3.groupBy("Y").agg(collect_set("z").as("combined"))
    – Farhan Soomro
    Nov 9 at 14:51













up vote
0
down vote

favorite









up vote
0
down vote

favorite











My data in CSV is like this(Expected Image):
Actual Data



And I want to convert this Data into:
Expected Data
(hivetablename.hivecolumnname = dbtablename.dbtablecolumn)



By joining the multiple Row values into a Single row value like above.



Please note that 'AND' is a Literal between the condition to be built, which would appear until the second last record.



Once the Last Record is reached, Only the condition would appear(xx=yy)



I wish the result to be in SCALA SPARK.

Many thanks in advance!










share|improve this question









New contributor




Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











My data in CSV is like this(Expected Image):
Actual Data



And I want to convert this Data into:
Expected Data
(hivetablename.hivecolumnname = dbtablename.dbtablecolumn)



By joining the multiple Row values into a Single row value like above.



Please note that 'AND' is a Literal between the condition to be built, which would appear until the second last record.



Once the Last Record is reached, Only the condition would appear(xx=yy)



I wish the result to be in SCALA SPARK.

Many thanks in advance!







scala apache-spark-2.0






share|improve this question









New contributor




Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|improve this question









New contributor




Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this question




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edited Nov 9 at 14:28





















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asked Nov 9 at 13:54









Farhan Soomro

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12




New contributor




Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Farhan Soomro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











  • Could you please share what have you tried so far?
    – ulubeyn
    Nov 9 at 14:40











  • Many thanks for the response. Im a learner so couldnt go much further. Heres what Ive been able to achieve val dfconf= spark.read.option("header", "true").csv("file:///conf.csv").alias("conf"); dfconf.show(10, false) val newDF1 = dfconf.withColumn("Y",lit("1")) val newDF2 = newDF1.withColumn("Z",lit(",")) val newDF3 = newDF2.withColumn("comb",concat($"hivetablename",lit("."),$"hivetablecolumn",lit("="),$"dbtablename",lit("."),$"dbtablecolumn")) newDF3.show() val newDF4 = newDF3.groupBy("Y").agg(collect_set("z").as("combined"))
    – Farhan Soomro
    Nov 9 at 14:51

















  • Could you please share what have you tried so far?
    – ulubeyn
    Nov 9 at 14:40











  • Many thanks for the response. Im a learner so couldnt go much further. Heres what Ive been able to achieve val dfconf= spark.read.option("header", "true").csv("file:///conf.csv").alias("conf"); dfconf.show(10, false) val newDF1 = dfconf.withColumn("Y",lit("1")) val newDF2 = newDF1.withColumn("Z",lit(",")) val newDF3 = newDF2.withColumn("comb",concat($"hivetablename",lit("."),$"hivetablecolumn",lit("="),$"dbtablename",lit("."),$"dbtablecolumn")) newDF3.show() val newDF4 = newDF3.groupBy("Y").agg(collect_set("z").as("combined"))
    – Farhan Soomro
    Nov 9 at 14:51
















Could you please share what have you tried so far?
– ulubeyn
Nov 9 at 14:40





Could you please share what have you tried so far?
– ulubeyn
Nov 9 at 14:40













Many thanks for the response. Im a learner so couldnt go much further. Heres what Ive been able to achieve val dfconf= spark.read.option("header", "true").csv("file:///conf.csv").alias("conf"); dfconf.show(10, false) val newDF1 = dfconf.withColumn("Y",lit("1")) val newDF2 = newDF1.withColumn("Z",lit(",")) val newDF3 = newDF2.withColumn("comb",concat($"hivetablename",lit("."),$"hivetablecolumn",lit("="),$"dbtablename",lit("."),$"dbtablecolumn")) newDF3.show() val newDF4 = newDF3.groupBy("Y").agg(collect_set("z").as("combined"))
– Farhan Soomro
Nov 9 at 14:51





Many thanks for the response. Im a learner so couldnt go much further. Heres what Ive been able to achieve val dfconf= spark.read.option("header", "true").csv("file:///conf.csv").alias("conf"); dfconf.show(10, false) val newDF1 = dfconf.withColumn("Y",lit("1")) val newDF2 = newDF1.withColumn("Z",lit(",")) val newDF3 = newDF2.withColumn("comb",concat($"hivetablename",lit("."),$"hivetablecolumn",lit("="),$"dbtablename",lit("."),$"dbtablecolumn")) newDF3.show() val newDF4 = newDF3.groupBy("Y").agg(collect_set("z").as("combined"))
– Farhan Soomro
Nov 9 at 14:51


















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