Explore Free Databricks Apache Spark Associate Developer Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Practice Questions for Exam Mastery

In which order should the code blocks shown below be run in order to create a DataFrame that shows the mean of column predError of DataFrame transactionsDf per column storeId and productId,

where productId should be either 2 or 3 and the returned DataFrame should be sorted in ascending order by column storeId, leaving out any nulls in that column?

DataFrame transactionsDf:

1. +-------------+---------+-----+-------+---------+----+

2. |transactionId|predError|value|storeId|productId| f|

3. +-------------+---------+-----+-------+---------+----+

4. | 1| 3| 4| 25| 1|null|

5. | 2| 6| 7| 2| 2|null|

6. | 3| 3| null| 25| 3|null|

7. | 4| null| null| 3| 2|null|

8. | 5| null| null| null| 2|null|

9. | 6| 3| 2| 25| 2|null|

10. +-------------+---------+-----+-------+---------+----+

1. .mean("predError")

2. .groupBy("storeId")

3. .orderBy("storeId")

4. transactionsDf.filter(transactionsDf.storeId.isNotNull())

5. .pivot("productId", [2, 3])

Which of the following code blocks returns a 2-column DataFrame that shows the distinct values in column productId and the number of rows with that productId in DataFrame transactionsDf?

Which of the following code blocks immediately removes the previously cached DataFrame transactionsDf from memory and disk?

The code block shown below should return a new 2-column DataFrame that shows one attribute from column attributes per row next to the associated itemName, for all suppliers in column supplier

whose name includes Sports. Choose the answer that correctly fills the blanks in the code block to accomplish this.

Sample of DataFrame itemsDf:

1. +------+----------------------------------+-----------------------------+-------------------+

2. |itemId|itemName |attributes |supplier |

3. +------+----------------------------------+-----------------------------+-------------------+

4. |1 |Thick Coat for Walking in the Snow|[blue, winter, cozy] |Sports Company Inc.|

5. |2 |Elegant Outdoors Summer Dress |[red, summer, fresh, cooling]|YetiX |

6. |3 |Outdoors Backpack |[green, summer, travel] |Sports Company Inc.|

7. +------+----------------------------------+-----------------------------+-------------------+

Code block:

itemsDf.__1__(__2__).select(__3__, __4__)

The code block shown below should add a column itemNameBetweenSeparators to DataFrame itemsDf. The column should contain arrays of maximum 4 strings. The arrays should be composed of

the values in column itemsDf which are separated at - or whitespace characters. Choose the answer that correctly fills the blanks in the code block to accomplish this.

Sample of DataFrame itemsDf:

1. +------+----------------------------------+-------------------+

2. |itemId|itemName |supplier |

3. +------+----------------------------------+-------------------+

4. |1 |Thick Coat for Walking in the Snow|Sports Company Inc.|

5. |2 |Elegant Outdoors Summer Dress |YetiX |

6. |3 |Outdoors Backpack |Sports Company Inc.|

7. +------+----------------------------------+-------------------+

Code block:

itemsDf.__1__(__2__, __3__(__4__, "[\s\-]", __5__))