I have a CSV file where the last column is inside parenthesis and the values are separated by commas. The number of values is variable in the last column. When I read them to as Dataframe with some column names as follows, I get Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: The number of columns doesn't match
. My CSV file looks like this
a1,b1,true,2017-05-16T07:00:41.0000000,2.5,(c1,d1,e1)
a2,b2,true,2017-05-26T07:00:42.0000000,0.5,(c2,d2,e2,f2,g2)
a2,b2,true,2017-05-26T07:00:42.0000000,0.5,(c2)
a2,b2,true,2017-05-26T07:00:42.0000000,0.5,(c2,d2)
a2,b2,true,2017-05-26T07:00:42.0000000,0.5,(c2,d2,e2)
a2,b2,true,2017-05-26T07:00:42.0000000,0.5,(c2,d2,e2,k2,f2)
what I finally want is something like this:
root
|-- MId: string (nullable = true)
|-- PId: string (nullable = true)
|-- IsTeacher: boolean(nullable = true)
|-- STime: datetype(nullable = true)
|-- TotalMinutes: double(nullable = true)
|-- SomeArrayHeader: array<string>(nullable = true)
I have written the following code till now:
val infoDF =
sqlContext.read.format("csv")
.option("header", "false")
.load(inputPath)
.toDF(
"MId",
"PId",
"IsTeacher",
"STime",
"TotalMinutes",
"SomeArrayHeader")
I thought of reading them without giving column names and then cast the columns which are after the 5th columns to array type. But then I am having problems with the parentheses. Is there a way I can do this while reading and telling that fields inside parenthesis are actually one field of type array.
Ok. The solution is only tactical for your case. The below one worked for me
val df = spark.read.option("quote", "(").csv("in/staff.csv").toDF(
"MId",
"PId",
"IsTeacher",
"STime",
"TotalMinutes",
"arr")
df.show()
val df2 = df.withColumn("arr",split(regexp_replace('arr,"[)]",""),","))
df2.printSchema()
df2.show()
Output:
+---+---+---------+--------------------+------------+---------------+
|MId|PId|IsTeacher| STime|TotalMinutes| arr|
+---+---+---------+--------------------+------------+---------------+
| a1| b1| true|2017-05-16T07:00:...| 2.5| c1,d1,e1)|
| a2| b2| true|2017-05-26T07:00:...| 0.5|c2,d2,e2,f2,g2)|
| a2| b2| true|2017-05-26T07:00:...| 0.5| c2)|
| a2| b2| true|2017-05-26T07:00:...| 0.5| c2,d2)|
| a2| b2| true|2017-05-26T07:00:...| 0.5| c2,d2,e2)|
| a2| b2| true|2017-05-26T07:00:...| 0.5|c2,d2,e2,k2,f2)|
+---+---+---------+--------------------+------------+---------------+
root
|-- MId: string (nullable = true)
|-- PId: string (nullable = true)
|-- IsTeacher: string (nullable = true)
|-- STime: string (nullable = true)
|-- TotalMinutes: string (nullable = true)
|-- arr: array (nullable = true)
| |-- element: string (containsNull = true)
+---+---+---------+--------------------+------------+--------------------+
|MId|PId|IsTeacher| STime|TotalMinutes| arr|
+---+---+---------+--------------------+------------+--------------------+
| a1| b1| true|2017-05-16T07:00:...| 2.5| [c1, d1, e1]|
| a2| b2| true|2017-05-26T07:00:...| 0.5|[c2, d2, e2, f2, g2]|
| a2| b2| true|2017-05-26T07:00:...| 0.5| [c2]|
| a2| b2| true|2017-05-26T07:00:...| 0.5| [c2, d2]|
| a2| b2| true|2017-05-26T07:00:...| 0.5| [c2, d2, e2]|
| a2| b2| true|2017-05-26T07:00:...| 0.5|[c2, d2, e2, k2, f2]|
+---+---+---------+--------------------+------------+--------------------+