How to use Spark DataFrame column value to update the elasticsearch

Problem description: I am trying to update documents in elastic search. I have data in a dataframe. Dataframe has esIndex, id and body attributes. I need to use the value in index attribute to update the document in the right index. The following code below does not work. What is possible fix?

Command 1

val esUrl = "test.elasticsearch.com"

Command 2

import spark.implicits._
val df = Seq(
  ("test_datbricks001","1221866122238136328", "TEST DATA 001"),
    ("test_datbricks001","1221866122238136329", "TEST DATA 002"),
      ("test_datbrick","1221866122238136329", "TEST DATA 002")

).toDF("esIndex", "id", "body")

Command 3

display(df)

Command 4

import org.apache.spark.sql.functions.col
val retval = df.toDF.write
        .format("org.elasticsearch.spark.sql")
        .option("es.nodes.wan.only","true")
        .option("es.mapping.id","id")
        .option("es.mapping.exclude", "id, esIndex")
        .option("es.port","80")
        .option("es.nodes", esUrl)
        .option("es.write.operation", "update") 
        .option("es.index.auto.create", "no")
        .mode("Append")
        .save("{esIndex}")  // <<== This index is not taking value from "index" column of df

I am getting the following error EsHadoopIllegalArgumentException: Target index [{esIndex}] does not exist and auto-creation is disabled [setting 'es.index.auto.create' is 'false']

Question: How do I get code in Command 4 to use the value in esIndex column of df