RDDs from External Datasets

PySpark can easily create RDDs from files that are stored in external storage devices, such as HDFS (Hadoop Distributed File System), Amazon S3 buckets, etc. However, the most common method of creating RDD's is from files stored in your local file system. This method takes a file path and reads it as a collection of lines. In this exercise, you'll create an RDD from the file path (file_path) with the file name README.md which is already available in your workspace.

Remember, you already have a SparkContext sc available in your workspace.

Deze oefening maakt deel uit van de cursus

Big Data Fundamentals with PySpark

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Oefeninstructies

Print the file_path in the PySpark shell.
Create a RDD named fileRDD from a file_path.
Print the type of the fileRDD created.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Print the file_path
print("The file_path is", ____)

# Create a fileRDD from file_path
fileRDD = sc.____(file_path)

# Check the type of fileRDD
print("The file type of fileRDD is", type(____))

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