PySpark and AWS: Master Big Data with PySpark and AWS - Spark DF (Group By - Multiple Columns and Aggregations)

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Information Technology (IT), Architecture
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University
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Hard
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary difference between grouping by a single column and grouping by multiple columns?
Grouping by a single column creates one group, while multiple columns create nested groups.
Grouping by multiple columns is only possible in SQL.
Grouping by multiple columns is faster than a single column.
Grouping by a single column requires more memory.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What happens under the hood when grouping by multiple columns?
It ignores the second column.
It merges all columns into one.
It creates a single group for all columns.
It creates a group for each unique value of the first column, then subgroups for the second column.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the example provided, what is the first step when grouping data by course and gender?
Sort the data by marks.
Calculate the average marks.
Create a group based on the course.
Filter the data by gender.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which function is used to perform multiple aggregations on grouped data?
sum
aggregate
agg
groupBy
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What error might occur if you try to perform a sum without specifying a column?
Column not found error.
Syntax error.
Data frame object has no attribute sum.
Type mismatch error.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT an aggregation function mentioned in the video?
median
max
average
sum
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of using the 'static' keyword in the context of counting?
To ensure the count is accurate.
To speed up the counting process.
To indicate that any column can be used for counting.
To specify a particular column for counting.
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