Podcast
Questions and Answers
What is a recommended approach to improve performance when the same dataframe is being referred to in multiple places in a Spark program?
What is a recommended approach to improve performance when the same dataframe is being referred to in multiple places in a Spark program?
- Increasing the size of the dataframe
- Avoiding the use of dataframe caching
- Running unnecessary Actions in the program
- Using cache() or persist() functions (correct)
In a Spark program, what can be done to reduce shuffling when joining a big table with a small table?
In a Spark program, what can be done to reduce shuffling when joining a big table with a small table?
- Using additional Actions before the join
- Partitioning the small table
- Increasing the number of executors
- Utilizing broadcast join (correct)
What will happen if unnecessary Actions are used in a Spark program?
What will happen if unnecessary Actions are used in a Spark program?
- Improves memory efficiency
- Triggers unnecessary DAG execution (correct)
- Optimizes the program automatically
- Reduces CPU utilization
Which function in Spark is specifically used to store a dataframe at a user-defined storage level?
Which function in Spark is specifically used to store a dataframe at a user-defined storage level?
Why is it not recommended to run unnecessary Actions in Spark programs?
Why is it not recommended to run unnecessary Actions in Spark programs?
When does broadcast join tend to have less advantage over shuffle-based joins?
When does broadcast join tend to have less advantage over shuffle-based joins?
What is the major difference between the 'coalesce()' and 'repartition()' functions in Spark?
What is the major difference between the 'coalesce()' and 'repartition()' functions in Spark?
What technique can be used to eliminate data skewness issues in Spark?
What technique can be used to eliminate data skewness issues in Spark?
How does Spark optimize the logical plan internally for better performance?
How does Spark optimize the logical plan internally for better performance?
When should you use the 'repartition()' function in Spark?
When should you use the 'repartition()' function in Spark?
What is a common issue that can cause tasks to take longer in Spark?
What is a common issue that can cause tasks to take longer in Spark?
How does filtering data in earlier steps affect the performance of Spark applications?
How does filtering data in earlier steps affect the performance of Spark applications?
Flashcards are hidden until you start studying
