Dear Community,
Recently, I had to solve the following problem "for every entry of a
Dataset[String], concat a constant value" , and to solve it, I used built-in
functions :
val data = Seq("A","b","c").toDS
scala> data.withColumn("valueconcat",concat(col(data.columns.head),lit("
"),lit("concat"))).select("valueconcat").explain()
== Physical Plan ==
LocalTableScan [valueconcat#161]
As an alternative , a much simpler version of the program is to use map, but
it adds a serialization step that does not seem to be present for the
version above :
scala> data.map(e=> s"$e concat").explain
== Physical Plan ==
*(1) SerializeFromObject [staticinvoke(class
org.apache.spark.unsafe.types.UTF8String, StringType, fromString, input[0,
java.lang.String, true], true, false) AS value#92]
+- *(1) MapElements <function1>, obj#91: java.lang.String
+- *(1) DeserializeToObject value#12.toString, obj#90: java.lang.String
+- LocalTableScan [value#12]
Is this over-optimization or is this the right way to go?
As a follow up , is there any better API to get the one and only column
available in a DataSet[String] when using built-in functions?
"col(data.columns.head)" works but it is not ideal.
Thanks!
