In which order should the code blocks shown below be run in order to read...

Explanation

Correct code block:

importedDf = spark.read.json(jsonPath)

importedDf.createOrReplaceTempView("importedDf")

spark.sql("SELECT * FROM importedDf WHERE productId != 3")

Option 5 is the only correct way listed of reading in a JSON in PySpark. The option("format", "json") is not the correct way to tell Spark's DataFrameReader that you want to read a JSON file. You

would do this through format("json") instead. Also, you can communicate the specific path of the JSON file to the DataFramReader using the load() method, not the path() method.

In order to use a SQL command through the SparkSession spark, you first need to create a temporary view through DataFrame.createOrReplaceTempView().

The SQL statement should start with the SELECT operator. The FILTER operator SQL provides is not the correct one to use here.

Static notebook | Dynamic notebook: See test 2, QUESTION NO: 59 (Databricks import instructions)