What is Spark SQL and how to use SQL queries to retrieve data?
Spark SQL is a component in Apache Spark that supports processing structured data by providing an interface for executing SQL queries, allowing users to query data using SQL statements.
To query data using SQL statements, you need to first create a SparkSession object, load the data you want to query into a DataFrame. Then, you can use the sql() method of SparkSession to execute the SQL query.
For instance, suppose we have a DataFrame containing student information such as names, ages, and grades. We can use the following SQL statement to query all students over the age of 18.
val spark = SparkSession.builder()
.appName("Spark SQL Example")
.getOrCreate()
val studentDF = spark.read.json("path/to/student.json")
studentDF.createOrReplaceTempView("students")
val result = spark.sql("SELECT * FROM students WHERE age > 18")
result.show()
In the code above, we start by creating a SparkSession object and loading a DataFrame containing student information. Next, we register the DataFrame as a temporary view “students” so that it can be referenced in SQL queries. Finally, we use the sql() method to execute the SQL query and display the results.