spark override the dataframe variable without using var
I have one API which perform delete operation on dataframe like below
def deleteColmns(df:DataFrame,clmList :List[org.apache.spark.sql.Column]):DataFrame
var ddf:DataFrame = null
for(clm<-clmList)
ddf.drop(clm)
return ddf
Since it is not good practice to use the var in functional programming , how to avoid this situation
apache-spark apache-spark-sql
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
add a comment |
I have one API which perform delete operation on dataframe like below
def deleteColmns(df:DataFrame,clmList :List[org.apache.spark.sql.Column]):DataFrame
var ddf:DataFrame = null
for(clm<-clmList)
ddf.drop(clm)
return ddf
Since it is not good practice to use the var in functional programming , how to avoid this situation
apache-spark apache-spark-sql
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
add a comment |
I have one API which perform delete operation on dataframe like below
def deleteColmns(df:DataFrame,clmList :List[org.apache.spark.sql.Column]):DataFrame
var ddf:DataFrame = null
for(clm<-clmList)
ddf.drop(clm)
return ddf
Since it is not good practice to use the var in functional programming , how to avoid this situation
apache-spark apache-spark-sql
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
I have one API which perform delete operation on dataframe like below
def deleteColmns(df:DataFrame,clmList :List[org.apache.spark.sql.Column]):DataFrame
var ddf:DataFrame = null
for(clm<-clmList)
ddf.drop(clm)
return ddf
Since it is not good practice to use the var in functional programming , how to avoid this situation
apache-spark apache-spark-sql
apache-spark apache-spark-sql
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
asked Nov 15 '18 at 13:25
user3607698user3607698
353115
353115
add a comment |
add a comment |
1 Answer
1
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With Spark >2.0, you can drop multiple columns using a sequence of column name :
val clmList: Seq[Column] = _
val strList: Seq[String] = clmList.map(c => s"$c")
df.drop(strList: _*)
Otherwise, you can always use foldLeft to fold left on the DataFrame and drop your columns :
clmList.foldLeft(df)((acc, c) => acc.drop(c))
I hope this helps.
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
With Spark >2.0, you can drop multiple columns using a sequence of column name :
val clmList: Seq[Column] = _
val strList: Seq[String] = clmList.map(c => s"$c")
df.drop(strList: _*)
Otherwise, you can always use foldLeft to fold left on the DataFrame and drop your columns :
clmList.foldLeft(df)((acc, c) => acc.drop(c))
I hope this helps.
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
add a comment |
With Spark >2.0, you can drop multiple columns using a sequence of column name :
val clmList: Seq[Column] = _
val strList: Seq[String] = clmList.map(c => s"$c")
df.drop(strList: _*)
Otherwise, you can always use foldLeft to fold left on the DataFrame and drop your columns :
clmList.foldLeft(df)((acc, c) => acc.drop(c))
I hope this helps.
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
add a comment |
With Spark >2.0, you can drop multiple columns using a sequence of column name :
val clmList: Seq[Column] = _
val strList: Seq[String] = clmList.map(c => s"$c")
df.drop(strList: _*)
Otherwise, you can always use foldLeft to fold left on the DataFrame and drop your columns :
clmList.foldLeft(df)((acc, c) => acc.drop(c))
I hope this helps.
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
With Spark >2.0, you can drop multiple columns using a sequence of column name :
val clmList: Seq[Column] = _
val strList: Seq[String] = clmList.map(c => s"$c")
df.drop(strList: _*)
Otherwise, you can always use foldLeft to fold left on the DataFrame and drop your columns :
clmList.foldLeft(df)((acc, c) => acc.drop(c))
I hope this helps.
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
edited Nov 15 '18 at 21:46
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
answered Nov 15 '18 at 14:03
eliasaheliasah
27.2k770115
27.2k770115
add a comment |
add a comment |
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