What is MAP and flatMap in spark?
Both map() and flatMap() are used for transformations. The map() transformation takes in a function and applies it to each element in the RDD and the result of the function is a new value of each element in the resulting RDD. The flatMap() is used to produce multiple output elements for each input element.
How do you use the flatMap in spark?
Usage of Spark flatMap() Transformation Spark flatMap() transformation flattens the RDD/DataFrame column after applying the function on every element and returns a new RDD/DataFrame respectively. The returned RDD/DataFrame can have the same count or more number of elements.
What is map in Apache spark?
A map is a transformation operation in Apache Spark. It applies to each element of RDD and it returns the result as new RDD. In the Map, operation developer can define his own custom business logic. The same logic will be applied to all the elements of RDD.
What is the difference between MAP () and flatMap () transformation?
As per the definition, difference between map and flatMap is: map : It returns a new RDD by applying given function to each element of the RDD. Function in map returns only one item. flatMap : Similar to map , it returns a new RDD by applying a function to each element of the RDD, but output is flattened.
Why is RDD reduceByKey better in performance than RDD groupByKey?
When a groupByKey is called on a RDD pair the data in the partitions are shuffled over the network to form a key and list of values. The reduceByKey works much better on a large dataset as compared to. That’s because Spark knows it can combine output with a common key on each partition before shuffling the data.
What is the difference map and flatMap?
map() function produces one output for one input value, whereas flatMap() function produces an arbitrary no of values as output (ie zero or more than zero) for each input value….Difference Between map() And flatMap() In Java Stream.
| map() | flatMap() |
|---|---|
| Produce a stream of value. | Produce a stream of stream value. |
What is the role of spark SQL?
Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data.
What is map and reduce in spark?
MapReduce is a programming engine for processing and generating large data sets with a parallel, distributed algorithm on a cluster of the computer. MapReduce is composed of several components, including : JobTracker — The master node that manages all jobs and resources in a cluster.
What is difference between MAP and flatMap in Java 8?
Why is reduceByKey faster than groupByKey?
Hi, The groupByKey can cause out of disk problems as data is sent over the network and collected on the reduced workers. Whereas in reducebykey, Data are combined at each partition, only one output for one key at each partition to send over the network.
Why is reduceByKey better than groupByKey?
Both reduceByKey and groupByKey result in wide transformations which means both triggers a shuffle operation. The key difference between reduceByKey and groupByKey is that reduceByKey does a map side combine and groupByKey does not do a map side combine.
What is flat map called?
planar projection Noun. map projection where the Earth’s surface is projected onto a flat surface (plane).