Spark SQL Overview

In this video we are discussing Spark SQL overview

This Spark SQL works on the structured data. So let us go for some more discussion on it

So what is Spark SQL? The Spark SQL is used to process structured data in Spark and from the Spark SQL interface

we can find detailed information about the data. So SQL we know that it is having the full form that is a structured query language

using this Spark SQL, we can get some detailing about our data

So, to interact with the Spark SQL, we can use the different ways like our data frame

and dataset and so on. So, let us see that in how many ways we can interact with this Spark SQL

So, there are basically three different ways to handle data in Spark

And Spark provides data frames for different languages like our PIPA Scala Java to work on the structured data So the way number one is our data frame with the help of which we can interact with

our data and these particular data frames will be supported by different high-level

languages like our Python, Java, Scala and so on. The next method, that means we are having three different ways in which you can access

our spark data. So first one is our data frame. Next one. So, data can be written in different format like our JSON, HypeTable, and etc

So, data can be accessed in multiple different formats also. Next one is that the form the SQL, we can query data from Spark programs or from external

tools. Using some external tools or writing this queries in our Spark programs, we can

access and we can query our data. So, there are three different ways to handle data

in our spark. And we'll be discussing more on this particular topic in the next videos

Please watch those videos also in the continuation of this one. Thanks for watching this video