title: how can i add a timestamp as an extra column to my dataframe
body: <p>*Hi all,</p>
  
  <p>I have an easy question for you all.
   I have an RDD, created from kafka streaming using createStream method.
  Now i want to add a timestamp as a value to this rdd before converting in to dataframe.
  I have tried doing  to add a value to the dataframe using with withColumn() but returning this error*</p>
  
  <pre><code>val topicMaps = Map("topic" -&gt; 1)
      val now = java.util.Calendar.getInstance().getTime()
  
      val messages = KafkaUtils.createStream[String, String, StringDecoder, StringDecoder](ssc, kafkaConf, topicMaps, StorageLevel.MEMORY_ONLY_SER)
  
        messages.foreachRDD(rdd =&gt;
            {
  
              val sqlContext = new org.apache.spark.sql.SQLContext(sc)
              import sqlContext.implicits._
  
              val dataframe = sqlContext.read.json(rdd.map(_._2))
  
  
  
          val d =dataframe.withColumn("timeStamp_column",dataframe.col("now"))
  </code></pre>
  
  <blockquote>
    <p>val d =dataframe.withColumn("timeStamp_column",dataframe.col("now"))
            org.apache.spark.sql.AnalysisException: Cannot resolve column name "now" among (action, device_os_ver, device_type, event_name,
    item_name, lat, lon, memberid, productUpccd, tenantid);
                    at org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:15</p>
  </blockquote>
  
  <p>As i came to know that DataFrames cannot be altered as they are immutable, but RDDs are immutable as well.
  Then what is the best way to do it.
  How to a value to the RDD(adding timestamp to an RDD dynamically).</p>