NEW
Font size
WorksheetsUtility Transform
Total questions: 14
Worksheet time: 7mins
What is ParDo used for in Apache Beam?
To group elements by a key
To apply a function to each element of a PCollection
To combine multiple PCollections into one
To divide a PCollection into several output PCollections
What is the purpose of the GroupByKey transform?
To apply a function to each element of a PCollection
To put all elements with the same key together in the same worker
To combine multiple PCollections into one
To flatten multiple PCollections
What issue can arise with GroupByKey when dealing with very large groups or skewed data?
Hotkey problem
Data loss
Increased latency
Data duplication
`GroupByKey` can inherently cause data loss (True or False)
True
False
`GroupByKey` can cause data duplication. (True or False)
True
False
How does the Combine transform improve performance for large groups?
By grouping all elements with the same key together
By applying a function to each element individually
By making the transformation in a hierarchy of several steps
By dividing the PCollection into several output PCollections
What type of operation can GroupByKey be used to perform?
Inner join
Outer join
Flatten
Both a and b
What does the Flatten transform do?
Groups elements by key
Combines multiple PCollections into one
Divides a PCollection into several output PCollections
Applies a function to each element of a PCollection
What is a key difference between Flatten and joins using GroupByKey?
Flatten only works with PCollections of different types
Joins using GroupByKey require PCollections to have different value types sharing a common key
Flatten can only be used for PCollections with different value types
Joins using GroupByKey require PCollections to have the same type
What does the Partition transform do?
Groups elements by key
Combines multiple PCollections into one
Divides a PCollection into several output PCollections by applying a function that assigns a group ID to each element
Applies a function to each element of a PCollection
In which scenario would you prefer using Combine instead of GroupByKey?
When dealing with very small groups
When the data is highly skewed and you want to avoid the hotkey problem
When you want to join two PCollections
When you want to apply a function to each element
What is a potential performance issue when using GroupByKey with highly skewed data?
Data loss
Hotkey problem leading to imbalance in processing
Increased network latency
Data duplication
When would you use Flatten over GroupByKey?
When you want to combine two PCollections with different types
When you have two PCollections with the same type and want to merge them
When you want to apply a function to each element of a PCollection
When you want to join two PCollections by a common key
Which transform would you use to divide a PCollection into multiple PCollections based on a function?
GroupByKey
Flatten
Combine
Partition
