Just a thought. SQL itself is a DSL. Why DSL on top of another DSL?
On Tue, Jul 25, 2017 at 4:47 AM kant kodali <kanth...@gmail.com> wrote:
> Hi All,
>
> I am thinking to express Spark SQL using JSON in the following the way.
>
> For Example:
>
> *Query using Spark DSL*
>
> DS.filter(col("name").equalTo("john"))
> .groupBy(functions.window(df1.col("TIMESTAMP"), "24 hours", "24
> hours"), df1.col("hourlyPay"))
> .agg(sum("hourlyPay").as("total"));
>
>
> *Query using JSON*
>
>
>
>
>
> The Goal is to design a DSL in JSON such that users can and express SPARK
> SQL queries in JSON so users can send Spark SQL queries over rest and get
> the results out. Now, I am sure there are BI tools and notebooks like
> Zeppelin that can accomplish the desired behavior however I believe there
> maybe group of users who don't want to use those BI tools or notebooks
> instead they want all the communication from front end to back end using
> API's.
>
> Also another goal would be the DSL design in JSON should closely mimic the
> underlying Spark SQL DSL.
>
> Please feel free to provide some feedback or criticize to whatever extent
> you like!
>
> Thanks!
>
>
>
