Another way to explore data in Spark is by using Spark SQL. This allows analysts who may not be well-versed in language-specific APIs, such as SparkR, PySpark (for Python), and Scala, to explore Spark data.
I will describe two different ways of accessing Spark data via SQL:
- Issuing SQL commands through the R interface:
This has the advantage of returning the results as an R dataframe, where it can be further manipulated
- Issuing SQL queries via databricks SQL magic: directive
This method allows analysts to issue direct SQL commands, without regard to any specific language environment
Before processing an object as SQL, the object needs to be registered as a SQL table or view. Once it is registered, it can be accessed through ...