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From Devesh Raj Singh <raj.deves...@gmail.com>
Subject Re: different behavior while using createDataFrame and read.df in SparkR
Date Sat, 06 Feb 2016 12:30:50 GMT
Thank you ! Rui Sun for the observation! It helped.

I have a new problem arising. When I create a small function for dummy
variable creation for categorical column

BDADummies<-function(dataframe,column){
  cat.column<-vector(mode="character",length=nrow(dataframe))
  cat.column<-collect(column)
  lev<-length(levels(as.factor(unlist(cat.column))))
  for (j in 1:lev){



dummy.df<-withColumn(dataframe,paste0(colnames(cat.column),j),ifelse(column[[1]]==levels(as.factor(unlist(cat.column)))[j],1,0)
)


    dataframe<-dummy.df
    }
  return(dataframe)
}

*and when I call the function using*

newdummy.df<-BDADummies(df1,column=select(df1,df1$Species))


I get the below error

Error in withColumn(dataframe, paste0(colnames(cat.column), j),
ifelse(column[[1]] ==  :
  error in evaluating the argument 'col' in selecting a method for function
'withColumn': Error in if (le > 0) paste0("[1:", paste(le), "]") else "(0)"
:
  argument is not interpretable as logical


*but when i use it without calling or creating a function , the statement *

dummy.df<-withColumn(dataframe,paste0(colnames(cat.column),j),ifelse(column[[1]]==levels(as.factor(unlist(cat.column)))[j],1,0)
)

gives me the new columns generating column names as desired.

Warm regards,
Devesh.

On Sat, Feb 6, 2016 at 7:09 AM, Sun, Rui <rui.sun@intel.com> wrote:

> I guess this is related to
> https://issues.apache.org/jira/browse/SPARK-11976
>
>
>
> When calling createDataFrame on iris, the “.” Character in column names
> will be replaced with “_”.
>
> It seems that when you create a DataFrame from the CSV file, the “.”
> Character in column names are still there.
>
>
>
> *From:* Devesh Raj Singh [mailto:raj.devesh99@gmail.com]
> *Sent:* Friday, February 5, 2016 2:44 PM
> *To:* user@spark.apache.org
> *Cc:* Sun, Rui
> *Subject:* different behavior while using createDataFrame and read.df in
> SparkR
>
>
>
>
> Hi,
>
>
>
> I am using Spark 1.5.1
>
>
>
> When I do this
>
>
>
> df <- createDataFrame(sqlContext, iris)
>
>
>
> #creating a new column for category "Setosa"
>
>
>
> df$Species1<-ifelse((df)[[5]]=="setosa",1,0)
>
>
>
> head(df)
>
>
>
> output: new column created
>
>
>
>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
>
> 1          5.1         3.5          1.4         0.2  setosa
>
> 2          4.9         3.0          1.4         0.2  setosa
>
> 3          4.7         3.2          1.3         0.2  setosa
>
> 4          4.6         3.1          1.5         0.2  setosa
>
> 5          5.0         3.6          1.4         0.2  setosa
>
> 6          5.4         3.9          1.7         0.4  setosa
>
>
>
> *but when I saved the iris dataset as a CSV file and try to read it and
> convert it to sparkR dataframe*
>
>
>
> df <-
> read.df(sqlContext,"/Users/devesh/Github/deveshgit2/bdaml/data/iris/",
>
>               source = "com.databricks.spark.csv",header =
> "true",inferSchema = "true")
>
>
>
> now when I try to create new column
>
>
>
> df$Species1<-ifelse((df)[[5]]=="setosa",1,0)
>
> I get the below error:
>
>
>
> 16/02/05 12:11:01 ERROR RBackendHandler: col on 922 failed
>
> Error in select(x, x$"*", alias(col, colName)) :
>
>   error in evaluating the argument 'col' in selecting a method for
> function 'select': Error in invokeJava(isStatic = FALSE, objId$id,
> methodName, ...) :
>
>   org.apache.spark.sql.AnalysisException: Cannot resolve column name
> "Sepal.Length" among (Sepal.Length, Sepal.Width, Petal.Length, Petal.Width,
> Species);
>
>             at org.apache.spark.s
>
> --
>
> Warm regards,
>
> Devesh.
>



-- 
Warm regards,
Devesh.

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