There has been a change for registration of a DataFrame as a table. Refer to this:

• For versions prior to Spark 2.0.0: registerTempTable()
• For Spark version 2.0.0 and previous: createOrReplaceTempView()

Pre-Spark 2.0.0 to register a DataFrame as a SQL table like artifact:

Before we can use the DataFrame for queries via SQL, we have to register the DataFrame as a temp table so the SQL statements can refer to it without any Scala/Spark syntax. This step may cause confusion for many beginners as we are not creating any table (temp or permanent), but the call registerTempTable() creates a name in SQL land that the SQL statements can refer to without additional UDF or without any domain-specific query language.

• Register the CustDf DataFrame as a name which SQL statements recognize as customers:

custDF.registerTempTable("customers")

• Register the prodDf DataFrame as a name which SQL statements recognize as product:

custDF.registerTempTable("customers")

• Register the saleDf DataFrame as a name which SQL statements recognize as sales:

custDF.registerTempTable("customers")

To ensure completeness, we include the import statements that we used prior to Spark 2.0.0 to run the code (namely, Spark 1.5.2):

import org.apache.spark._
 
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.SQLContext
 import org.apache.spark.mllib.linalg._
 import org.apache.spark.util._
 import Array._
 import org.apache.spark.sql._
 import org.apache.spark.sql.types._
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.types.{ StructType, StructField, StringType};