UDAF stands for User Defined Aggregate functions. Aggregate functions are used to perform a calculation on a set of values and return a single value. It is difficult to write an aggregate function compared to writing a User Defined Functions(UDF) as we need to aggregate on multiple rows and columns. Apache Spark UDAF operates on more than one row or Column while returning a single value results
When working with Apache spark ,there are times when you need to trigger a Spark job on demand from withing and outside the cluster.There are two ways in which we can submit Apache spark job in a cluster which includes bash script and REST API.
Apache Spark Streaming execution model is advantageous over traditional streaming systems for its fast recovery from failures, dynamic load balancing, streaming and interactive analytics, and native integration.
Resilient Distributed Dataset (RDD) is the fault-tolerant and immutable primary data structure/abstraction in Apache Spark. It is a distributed collection of objects. The term ‘resilient’ in ‘Resilient Distributed Dataset’ refers…
Shared variables are an abstraction in Apache Spark which is used in parallel operations in different nodes. When Spark runs a function in parallel as a set of tasks on…
What exactly is Apache Hadoop? Apache Hadoop is an open-source distributed processing framework that is used to store and process large datasets whose size ranges from gigabytes to petabytes of…
Apache Spark is a distributed, in-memory and disk based optimized system which does real-time analytics using Resilient Distributed Data(RDD) Sets.Spark includes a streaming library, and a rich set of programming interfaces to make data processing and transformation easier.