ArrayType(StringType) to IntegerType conversion in spark dataframe










-1















I'm trying to groupBy column name host and aggregate average of a column of type ArrayType(StringType) after type casting it to ArrayType(IntegerType).



It throws below error



 `cannot resolve `avg(variables)` due to datatype mismatch: function average requires numeric types, not ArrayType(IntegerType,true);


Input Data - sample Dataframe before grouping



|request|time |type |host |service | variables |
|REST |1542111483170|RESTFUL|KAFKA|www.google.com|[Duration, 7,Type] |
|REST |1542111486570|RESTFUL|KAFKA|www.google.com|[Duration, 9, Type]|


How to cast or handle ArrayType(StringType) to IntegerType i.e Column variables is of ArrayType(varaible.variable:String,varaible.value:String,varaible.TypeString) I want to convert 2nd value of Array varaible.value to Integer for Aggregation (Average calculation)?



Case Class:



 case class ServiceActivity(val request: String, val time: Long, val Type: String, val host: String, val service: String, val variables: Array[Variables])

case class Variables(val variable: String, val value: String, val Type: String)


Code Below:



val report = df.select("*").where(array_contains(df("variables.variable"),"Duration"))
val intermediate = report.withColumn("variables", col(variables.value).cast(org.apache.spark.sql.types.ArrayType(org.apache.spark.sql.types.IntegerType,true)
intermediate.withColumn("duration",$"variables".getItem(2)).drop("variables").withColumnRenamed("duration","variables")


GroupBy Code(error):



 intermediate.groupBy(intermediate("host")).agg(Map("variables"->"avg"))


Any workarounds.



Thanks










share|improve this question
























  • can you share the schema of dataframe df ?

    – Shankar Koirala
    Nov 14 '18 at 8:09












  • Question Updated

    – Vicky
    Nov 14 '18 at 8:14











  • @ShankarKoirala, Any Updates.

    – Vicky
    Nov 14 '18 at 10:14











  • Could you add more detials on how you are inputing Variables dataframe and combining it with ServiceActivity dataframe? Sample code and data would be helpful to replicate the problem.

    – user238607
    Nov 14 '18 at 12:35











  • Can you please update in detail with input data and required output data

    – Shankar Koirala
    Nov 14 '18 at 13:23
















-1















I'm trying to groupBy column name host and aggregate average of a column of type ArrayType(StringType) after type casting it to ArrayType(IntegerType).



It throws below error



 `cannot resolve `avg(variables)` due to datatype mismatch: function average requires numeric types, not ArrayType(IntegerType,true);


Input Data - sample Dataframe before grouping



|request|time |type |host |service | variables |
|REST |1542111483170|RESTFUL|KAFKA|www.google.com|[Duration, 7,Type] |
|REST |1542111486570|RESTFUL|KAFKA|www.google.com|[Duration, 9, Type]|


How to cast or handle ArrayType(StringType) to IntegerType i.e Column variables is of ArrayType(varaible.variable:String,varaible.value:String,varaible.TypeString) I want to convert 2nd value of Array varaible.value to Integer for Aggregation (Average calculation)?



Case Class:



 case class ServiceActivity(val request: String, val time: Long, val Type: String, val host: String, val service: String, val variables: Array[Variables])

case class Variables(val variable: String, val value: String, val Type: String)


Code Below:



val report = df.select("*").where(array_contains(df("variables.variable"),"Duration"))
val intermediate = report.withColumn("variables", col(variables.value).cast(org.apache.spark.sql.types.ArrayType(org.apache.spark.sql.types.IntegerType,true)
intermediate.withColumn("duration",$"variables".getItem(2)).drop("variables").withColumnRenamed("duration","variables")


GroupBy Code(error):



 intermediate.groupBy(intermediate("host")).agg(Map("variables"->"avg"))


Any workarounds.



Thanks










share|improve this question
























  • can you share the schema of dataframe df ?

    – Shankar Koirala
    Nov 14 '18 at 8:09












  • Question Updated

    – Vicky
    Nov 14 '18 at 8:14











  • @ShankarKoirala, Any Updates.

    – Vicky
    Nov 14 '18 at 10:14











  • Could you add more detials on how you are inputing Variables dataframe and combining it with ServiceActivity dataframe? Sample code and data would be helpful to replicate the problem.

    – user238607
    Nov 14 '18 at 12:35











  • Can you please update in detail with input data and required output data

    – Shankar Koirala
    Nov 14 '18 at 13:23














-1












-1








-1








I'm trying to groupBy column name host and aggregate average of a column of type ArrayType(StringType) after type casting it to ArrayType(IntegerType).



It throws below error



 `cannot resolve `avg(variables)` due to datatype mismatch: function average requires numeric types, not ArrayType(IntegerType,true);


Input Data - sample Dataframe before grouping



|request|time |type |host |service | variables |
|REST |1542111483170|RESTFUL|KAFKA|www.google.com|[Duration, 7,Type] |
|REST |1542111486570|RESTFUL|KAFKA|www.google.com|[Duration, 9, Type]|


How to cast or handle ArrayType(StringType) to IntegerType i.e Column variables is of ArrayType(varaible.variable:String,varaible.value:String,varaible.TypeString) I want to convert 2nd value of Array varaible.value to Integer for Aggregation (Average calculation)?



Case Class:



 case class ServiceActivity(val request: String, val time: Long, val Type: String, val host: String, val service: String, val variables: Array[Variables])

case class Variables(val variable: String, val value: String, val Type: String)


Code Below:



val report = df.select("*").where(array_contains(df("variables.variable"),"Duration"))
val intermediate = report.withColumn("variables", col(variables.value).cast(org.apache.spark.sql.types.ArrayType(org.apache.spark.sql.types.IntegerType,true)
intermediate.withColumn("duration",$"variables".getItem(2)).drop("variables").withColumnRenamed("duration","variables")


GroupBy Code(error):



 intermediate.groupBy(intermediate("host")).agg(Map("variables"->"avg"))


Any workarounds.



Thanks










share|improve this question
















I'm trying to groupBy column name host and aggregate average of a column of type ArrayType(StringType) after type casting it to ArrayType(IntegerType).



It throws below error



 `cannot resolve `avg(variables)` due to datatype mismatch: function average requires numeric types, not ArrayType(IntegerType,true);


Input Data - sample Dataframe before grouping



|request|time |type |host |service | variables |
|REST |1542111483170|RESTFUL|KAFKA|www.google.com|[Duration, 7,Type] |
|REST |1542111486570|RESTFUL|KAFKA|www.google.com|[Duration, 9, Type]|


How to cast or handle ArrayType(StringType) to IntegerType i.e Column variables is of ArrayType(varaible.variable:String,varaible.value:String,varaible.TypeString) I want to convert 2nd value of Array varaible.value to Integer for Aggregation (Average calculation)?



Case Class:



 case class ServiceActivity(val request: String, val time: Long, val Type: String, val host: String, val service: String, val variables: Array[Variables])

case class Variables(val variable: String, val value: String, val Type: String)


Code Below:



val report = df.select("*").where(array_contains(df("variables.variable"),"Duration"))
val intermediate = report.withColumn("variables", col(variables.value).cast(org.apache.spark.sql.types.ArrayType(org.apache.spark.sql.types.IntegerType,true)
intermediate.withColumn("duration",$"variables".getItem(2)).drop("variables").withColumnRenamed("duration","variables")


GroupBy Code(error):



 intermediate.groupBy(intermediate("host")).agg(Map("variables"->"avg"))


Any workarounds.



Thanks







apache-spark apache-spark-sql






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edited Nov 15 '18 at 5:33







Vicky

















asked Nov 14 '18 at 8:01









VickyVicky

97




97












  • can you share the schema of dataframe df ?

    – Shankar Koirala
    Nov 14 '18 at 8:09












  • Question Updated

    – Vicky
    Nov 14 '18 at 8:14











  • @ShankarKoirala, Any Updates.

    – Vicky
    Nov 14 '18 at 10:14











  • Could you add more detials on how you are inputing Variables dataframe and combining it with ServiceActivity dataframe? Sample code and data would be helpful to replicate the problem.

    – user238607
    Nov 14 '18 at 12:35











  • Can you please update in detail with input data and required output data

    – Shankar Koirala
    Nov 14 '18 at 13:23


















  • can you share the schema of dataframe df ?

    – Shankar Koirala
    Nov 14 '18 at 8:09












  • Question Updated

    – Vicky
    Nov 14 '18 at 8:14











  • @ShankarKoirala, Any Updates.

    – Vicky
    Nov 14 '18 at 10:14











  • Could you add more detials on how you are inputing Variables dataframe and combining it with ServiceActivity dataframe? Sample code and data would be helpful to replicate the problem.

    – user238607
    Nov 14 '18 at 12:35











  • Can you please update in detail with input data and required output data

    – Shankar Koirala
    Nov 14 '18 at 13:23

















can you share the schema of dataframe df ?

– Shankar Koirala
Nov 14 '18 at 8:09






can you share the schema of dataframe df ?

– Shankar Koirala
Nov 14 '18 at 8:09














Question Updated

– Vicky
Nov 14 '18 at 8:14





Question Updated

– Vicky
Nov 14 '18 at 8:14













@ShankarKoirala, Any Updates.

– Vicky
Nov 14 '18 at 10:14





@ShankarKoirala, Any Updates.

– Vicky
Nov 14 '18 at 10:14













Could you add more detials on how you are inputing Variables dataframe and combining it with ServiceActivity dataframe? Sample code and data would be helpful to replicate the problem.

– user238607
Nov 14 '18 at 12:35





Could you add more detials on how you are inputing Variables dataframe and combining it with ServiceActivity dataframe? Sample code and data would be helpful to replicate the problem.

– user238607
Nov 14 '18 at 12:35













Can you please update in detail with input data and required output data

– Shankar Koirala
Nov 14 '18 at 13:23






Can you please update in detail with input data and required output data

– Shankar Koirala
Nov 14 '18 at 13:23













1 Answer
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oldest

votes


















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Sorted out by splitting the Array and using concat_ws method



 val splitArray = ab.withColumn("Avg_Duration", concat_ws("", ab("variables.value")))

splitArray.groupBy(splitArray("host")).agg(Map("Avg_Duration" -> "avg")).show(false)


Thank you






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    1 Answer
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    1 Answer
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    Sorted out by splitting the Array and using concat_ws method



     val splitArray = ab.withColumn("Avg_Duration", concat_ws("", ab("variables.value")))

    splitArray.groupBy(splitArray("host")).agg(Map("Avg_Duration" -> "avg")).show(false)


    Thank you






    share|improve this answer



























      0














      Sorted out by splitting the Array and using concat_ws method



       val splitArray = ab.withColumn("Avg_Duration", concat_ws("", ab("variables.value")))

      splitArray.groupBy(splitArray("host")).agg(Map("Avg_Duration" -> "avg")).show(false)


      Thank you






      share|improve this answer

























        0












        0








        0







        Sorted out by splitting the Array and using concat_ws method



         val splitArray = ab.withColumn("Avg_Duration", concat_ws("", ab("variables.value")))

        splitArray.groupBy(splitArray("host")).agg(Map("Avg_Duration" -> "avg")).show(false)


        Thank you






        share|improve this answer













        Sorted out by splitting the Array and using concat_ws method



         val splitArray = ab.withColumn("Avg_Duration", concat_ws("", ab("variables.value")))

        splitArray.groupBy(splitArray("host")).agg(Map("Avg_Duration" -> "avg")).show(false)


        Thank you







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 15 '18 at 5:34









        VickyVicky

        97




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