You can take a look at the code that Spark generates:
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.execution.debug.codegenString
val spark: SparkSession
import org.apache.spark.sql.functions._
import spark.implicits._
val data = Seq("A","b","c").toDF("col")
data.write.parquet("/tmp/data")
val df = spark.read.parquet("/tmp/data")
val df1 = df.withColumn("valueconcat", concat(col(data.columns.head),
lit(" "), lit("concat"))).select("valueconcat")
println(codegenString(df1.queryExecution.executedPlan))
val df2 = df.map(e=> s"$e concat")
println(codegenString(df2.queryExecution.executedPlan))
It shows that for the df1 it internally uses
org.apache.spark.unsafe.types.UTF8String#concat vs
deserialization/serialization of the map function in the df2
Using spark native functions in most cases is the most effective way
in terms of performance
On Sat, Apr 4, 2020 at 2:07 PM <em...@yeikel.com> wrote:
>
> Dear Community,
>
>
>
> Recently, I had to solve the following problem “for every entry of a
> Dataset[String], concat a constant value” , and to solve it, I used built-in
> functions :
>
>
>
> val data = Seq("A","b","c").toDS
>
>
>
> scala> data.withColumn("valueconcat",concat(col(data.columns.head),lit("
> "),lit("concat"))).select("valueconcat").explain()
>
> == Physical Plan ==
>
> LocalTableScan [valueconcat#161]
>
>
>
> As an alternative , a much simpler version of the program is to use map, but
> it adds a serialization step that does not seem to be present for the version
> above :
>
>
>
> scala> data.map(e=> s"$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!
--
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