They should have the same performance, as they are compiled down to the same execution plan.
Note that starting in Spark 1.3, SchemaRDD is renamed DataFrame: https://databricks.com/blog/2015/02/17/introducing-dataframes-in-spark-for-large-scale-data-science.html On Tue, Mar 10, 2015 at 2:13 PM, Cesar Flores <ces...@gmail.com> wrote: > > I am new to the SchemaRDD class, and I am trying to decide in using SQL > queries or Language Integrated Queries ( > https://spark.apache.org/docs/1.2.0/api/scala/index.html#org.apache.spark.sql.SchemaRDD > ). > > Can someone tell me what is the main difference between the two > approaches, besides using different syntax? Are they interchangeable? Which > one has better performance? > > > Thanks a lot > -- > Cesar Flores >