SPARK-DEV practice questions 151–160

1. Question 151 · 219 in bank

   The code block shown below contains an error. The code block is intended to return a new DataFrame where column managerName from DataFrame storesDF is split at the space character into column managerFirstName and column managerLastName. Identify the error. A sample of DataFrame storesDF is displayed below:

   

   Code block: storesDF.withColumn("managerFirstName", col("managerName").split(" ").getItem(0)) .withColumn("managerLastName", col("managerName").split(" ").getItem(1))

   • AThe index values of 0 and 1 are not correct – they should be 1 and 2, respectively.
   • BThe index values of 0 and 1 should be provided as second arguments to the split() operation rather than indexing the result.
   • CThe split() operation comes from the imported functions object. It accepts a string column name and split character as arguments. It is not a method of a Column object.
   • DThe split() operation comes from the imported functions object. It accepts a Column object and split character as arguments. It is not a method of a Column object.
   • EThe withColumn operation cannot be called twice in a row.

   Show answer

   Answer: C

   Explanation

   I think it is C data = [ ("John Smith",), ("Jane Doe",), ("Mike Johnson",) ] df = spark.createDataFrame(data, ["managerName"]) df.show() df = df.withColumn("managerFirstName", split(col("managerName"), " ").getItem(0)) \ .withColumn("managerLastName", split(col("managerName"), " ").getItem(1)) df.show()

   Source: Adapted from community discussion — newusername

   Next question

2. Question 152 · 219 in bank

   The code block shown below should return a new DataFrame where single quotes in column storeSlogan have been replaced with double quotes. Choose the response that correctly fills in the numbered blanks within the code block to complete this task. A sample of DataFrame storesDF is below:

   

   Code block: storesDF.__1__(__2__, __3__(__4__, __5__, __6__))

   • A1. withColumn 2. "storeSlogan" 3. regexp_extract 4. col("storeSlogan") 5. "\"" 6. "'"
   • B1. newColumn 2. storeSlogan 3. regexp_extract 4. col(storeSlogan) 5. "\"" 6. "'"
   • C1. withColumn 2. "storeSlogan" 3. regexp_replace 4. col("storeSlogan") 5. "\"" 6. "'"
   • D1. withColumn 2. "storeSlogan" 3. regexp_replace 4. col("storeSlogan") 5. "'" 6. "\""
   • E1. withColumn 2. "storeSlogan" 3. regexp_extract 4. col("storeSlogan") 5. "'" 6. "\""

   Show answer

   Answer: D

   Next question

3. Question 153 · 219 in bank

   Which of the following code blocks returns a new DataFrame where column sqft from DataFrame storesDF has had its missing values replaced with the value 30,000? A sample of DataFrame storesDF is below:

   

   • AstoresDF.na.fill(30000, Seq("sqft"))
   • BstoresDF.nafill(30000, col("sqft"))
   • CstoresDF.na.fill(30000, col("sqft"))
   • DstoresDF.fillna(30000, col("sqft"))
   • EstoresDF.na.fill(30000, "sqft")

   Show answer

   Answer: E

   Explanation

   E is answer. It's tested. A)AttributeError: module 'pyspark.sql.functions' has no attribute 'Seq' B)AttributeError: 'DataFrame' object has no attribute 'nafill' C)PySparkTypeError: [NOT_LIST_OR_TUPLE] Argument `subset` should be a list or tuple, got Column. D)PySparkTypeError: [NOT_LIST_OR_TUPLE] Argument `subset` should be a list or tuple, got Column.

   Source: Adapted from community discussion — Samir_91

   Next question

4. Question 154 · 219 in bank

   Which of the following operations can be used to return a DataFrame with no duplicate rows? Please select the most complete answer.

   • ADataFrame.distinct()
   • BDataFrame.dropDuplicates() and DataFrame.distinct()
   • CDataFrame.dropDuplicates()
   • DDataFrame.drop_duplicates()
   • EDataFrame.dropDuplicates(), DataFrame.distinct() and DataFrame.drop_duplicates()

   Show answer

   Answer: E

   Next question

5. Question 155 · 219 in bank

   QUESTION NO: 75 - Which of the following code blocks returns a DataFrame where column divisionDistinct is the approximate number of distinct values in column division from DataFrame storesDF?

   • AstoresDF.withColumn("divisionDistinct", approx_count_distinct(col("division")))
   • BstoresDF.agg(col("division").approx_count_distinct("divisionDistinct"))
   • CstoresDF.agg(approx_count_distinct(col("division")).alias("divisionDistinct"))
   • DstoresDF.withColumn("divisionDistinct", col("division").approx_count_distinct())
   • EstoresDF.agg(col("division").approx_count_distinct().alias("divisionDistinct"))

   Show answer

   Answer: C

   Next question

6. Question 156 · 219 in bank

   The code block shown below should return a new DataFrame with the mean of column sqft from DataFrame storesDF in column sqftMean. Choose the response that correctly fills in the numbered blanks within the code block to complete this task. Code block: storesDF.__1__(__2__(__3__).alias("sqftMean"))

   • A1. agg 2. mean 3. col("sqft")
   • B1. withColumn 2. mean 3. col("sqft")
   • C1. agg 2. average 3. col("sqft")
   • D1. mean 2. col 3. "sqft"
   • E1. agg 2. mean 3. "sqft"

   Show answer

   Answer: A

   Next question

7. Question 157 · 219 in bank

   Which of the following code blocks returns the number of rows in DataFrame storesDF for each unique value in column division?

   • AstoresDF.groupBy("division").agg(count())
   • BstoresDF.agg(groupBy("division").count())
   • CstoresDF.groupby.count("division")
   • DstoresDF.groupBy().count("division")
   • EstoresDF.groupBy("division").count()

   Show answer

   Answer: E

   Next question

8. Question 158 · 219 in bank

   Which of the following code blocks returns a DataFrame sorted alphabetically based on column division?

   • AstoresDF.sort("division")
   • BstoresDF.orderBy(desc("division"))
   • CstoresDF.orderBy(col("division").desc())
   • DstoresDF.orderBy("division", ascending - true)
   • EstoresDF.sort(desc("division"))

   Show answer

   Answer: A

   Next question

9. Question 159 · 219 in bank

   Which of the following code blocks returns a 10 percent sample of rows from DataFrame storesDF with replacement?

   • AstoresDF.sample(true)
   • BstoresDF.sample(true, fraction = 0.1)
   • CstoresDF.sample(true, fraction = 0.15)
   • DstoresDF.sampleBy(fraction = 0.1)
   • EstoresDF.sample(false, fraction = 0.1)

   Show answer

   Answer: B

   Next question

10. Question 160 · 219 in bank

    Which of the following is the most complete description of lazy evaluation?

    • ANone of these options describe lazy evaluation
    • BA process is lazily evaluated if its execution does not start until it is put into action by some type of trigger
    • CA process is lazily evaluated if its execution does not start until it is forced to display a result to the user
    • DA process is lazily evaluated if its execution does not start until it reaches a specified date and time
    • EA process is lazily evaluated if its execution does not start until it is finished compiling

    Show answer

    Answer: B

    Explanation

    The most complete description of lazy evaluation is: B. A process is lazily evaluated if its execution does not start until it is put into action by some type of trigger. Explanation: Lazy evaluation is a programming language feature that delays the evaluation of expressions or computations until the result is actually needed or requested. In a lazily evaluated system, expressions are not immediately executed or evaluated when they are defined or assigned. Instead, the evaluation is deferred until the value is needed by another part of the program or when an action is triggered.

    Source: Adapted from community discussion — TmData

    Next question

Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

SPARK-DEV practice, question 151. 219 questions available.