Login using Social Account
Login using your credentials
Operations that can not benefit from Partitioning?
groupWith()
groupByKey()
reduceByKey(),
filter()
join()
lookup()
Taking you to the next exercise in seconds...
Stay here Next Exercise
Want to create exercises like this yourself? Click here.
No hints are availble for this assesment
Go Back to the Course
1 Adv Spark Programming - Understanding Persistence
2 Spark Programming - RDD caching is used for avoiding re-computation of an RDD:...
3 Spark Programming - With persistence we can replicate the RDD so that spark...
4 Spark Programming - RDD cachng is basically persisting an RDD into the RAM?...
5 Adv Spark Programming - Persistence StorageLevel
6 Spark Programming - The persist() method accepts an argument which is an object...
7 Spark Programming - Say, you are creating an RDD rdd1 after a lot...
8 Spark Programming - Which of the following is not true for MEMORY_AND_DISK_2 storage...
9 Spark Programming - StorageLevel does not specify the following configuration?...
10 Adv Spark Programming - Data Partitioning
11 Adv Spark Programming - Partitioning HandsOn
12 Adv Spark Programming - Data Partitioning Example
13 Spark Programming - Apache Spark's Data partitioning in RDD is useful if...
14 Spark Programming - Which of the following is not true about Data partitioning?...
15 Spark Programming - Which of the following is not an example of default...
16 Spark Programming - We had a key-value RDD having 1 to 10 as...
17 Spark Programming - We had a key-value RDD having 1 to 10 as...
18 Spark Programming - Operations that can not benefit from Partitioning?...
19 Adv Spark Programming - Custom Partitioner
20 Spark Programming - You can create own partitioner?...
21 Adv Spark Programming - Shared Variables
22 Spark Programming - When we pass a function say f to map or...
23 Spark Programming - If we have some data, which of the following is...
24 Spark Programming - If we have some data of few kilobyte size, which...
25 Adv Spark Programming - Accumulators
26 Spark Programming - Accumulators are used for...
27 Spark Programming - Accumulators will give incorrect results in the cases where:...
28 Spark Programming - Which of the use-case is not right for accumulator:...
29 Adv Spark Programming - Custom Accumulators
30 Adv Spark Programming - Broadcast Variables
31 Spark Programming - Broadcast variables are used because...
32 Spark Programming - To share few bytes data with workers we use:...
33 Adv Spark Programming - Broadcast Variables Example
34 Adv Spark Programming - Key Performance Considerations - Parallelism
35 Spark Programming - If you have an RDD with 1000 records. The function...
36 Adv Spark Programming - Key Performance Considerations - Partitions
37 Spark Programming - If we have a text file of 8GB in HDFS...
38 Spark Programming - If we have 1GB data as an array and we...
39 Spark Programming - Which of the following is not right way of controlling...
40 Adv Spark Programming - Serialization Format
41 Spark Programming - Serialization happens when...
42 Spark Programming - Performance of serializer is important because in Spark the serialization...
43 Spark Programming - Which serializer is slowest?...
44 Adv Spark Programming - Memory Management
45 Spark Programming - How much memory is consumed for loading an RDD?...
46 Spark Programming - Spark reserves 20% of memory to shuffle and agregation buffers....
47 Spark Programming - Spark reserves last 20% of memory to code. What does...
48 Adv Spark Programming - Hardware Provisioning
49 Spark Programming - Which of the following hardware parameters do not matter for...
50 Spark Programming - Spark is able to achieve linear scaling. What does it...
51 Spark Programming - Why the memory beyond 64GB is discouraged?...
52 Adv Spark Programming - Slides
Loading comments...