Databricks Data Engineer Associate exam dumps

Databricks Data Engineer Associate practice question 87 of 532

Databricks Certified Data Engineer Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Data Engineer Associate Question 87

Select 2

You are a data engineer working on a Databricks notebook. You are tasked with reading sales data stored in multiple CSV files located in a directory called 'sales_data/', as well as a single file named 'summary.csv' in the same directory. Which of the following commands will correctly load the data into two distinct DataFrames?

  1. A

    sales_df = spark.read.csv('sales_data/', header=True); summary_df = spark.read.csv('sales_data/summary.csv', header=True)

  2. B

    sales_df = spark.read.format('csv').load('sales_data/', header=True); summary_df = spark.read.format('csv').load('sales_data/summary.csv', header=True)

  3. C

    sales_df = spark.read.csv('sales_data/', header=True); summary_df = spark.read.csv('sales_data/summary.csv')

  4. D

    sales_df = spark.read.format('csv').load('sales_data/'); summary_df = spark.read.format('csv').load('sales_data/summary.csv', header=True)

  5. E

    sales_df = spark.read.csv('sales_data/', header=True); summary_df = spark.read.text('sales_data/summary.csv')

Show answer and explanation

Correct answers: A, C

Explanation

To extract data from a directory of files and a single file in Databricks, you can use spark.read.csv or spark.read.format('csv').load() methods. It is important to ensure that the 'header=True' option is used when the CSV files include a header row. The correct options demonstrate the proper syntax for reading both a directory of files and a single file into distinct DataFrames.

  • A. Correct.

    Correct. This command uses spark.read.csv for both operations with the 'header=True' option specified for reading the header row. It correctly reads the directory of files and the single file into separate DataFrames.

  • B. Incorrect.

    Incorrect. This command improperly uses spark.read.format('csv') and does not correctly specify the 'header=True' option for the directory of files.

  • C. Correct.

    Correct. This command uses spark.read.csv to read both the directory of files and the single file. The first read includes 'header=True' to process the headers, while the second read defaults to the correct behavior for a single file.

  • D. Incorrect.

    Incorrect. This command misses the 'header=True' option while reading the directory of files, which would result in incorrect behavior for CSVs that include a header row.

  • E. Incorrect.

    Incorrect. This command uses spark.read.text for the single file, which is not appropriate for reading a CSV file.

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