Can data in RDD be changed once RDD is created?

Each time it creates new RDD when we apply any transformation. Thus, the so input RDDs, cannot be changed since RDD are immutable in nature.

How do I read multiple files in Spark?

Spark core provides textFile() & wholeTextFiles() methods in SparkContext class which is used to read single and multiple text or csv files into a single Spark RDD. Using this method we can also read all files from a directory and files with a specific pattern.

How does RDD work in Spark?

The key idea of spark is Resilient Distributed Datasets (RDD); it supports in-memory processing computation. This means, it stores the state of memory as an object across the jobs and the object is sharable between those jobs. Data sharing in memory is 10 to 100 times faster than network and Disk.

What are the limitations of Apache Spark?

What are the limitations of Apache Spark

• No File Management system. Spark has no file management system of its own.
• No Support for Real-Time Processing. Spark does not support complete Real-time Processing.
• Small File Issue.
• Cost-Effective.
• Window Criteria.
• Latency.
• Less number of Algorithms.
• Iterative Processing.

How many ways RDD can be created?

There are three ways to create an RDD in Spark. Parallelizing already existing collection in driver program. Referencing a dataset in an external storage system (e.g. HDFS, Hbase, shared file system). Creating RDD from already existing RDDs.

How does spark Read RDD?

1.1 textFile() – Read text file into RDD sparkContext. textFile() method is used to read a text file from HDFS, S3 and any Hadoop supported file system, this method takes the path as an argument and optionally takes a number of partitions as the second argument. Here, it reads every line in a “text01.

What are the features of RDD that makes RDD an important abstraction of Spark?

Prominent Features

• In-Memory. It is possible to store data in spark RDD.
• Lazy Evaluations. By its name, it says that on calling some operation, execution process doesn’t start instantly.
• Immutable and Read-only.
• Cacheable or Persistence.
• Partitioned.
• Parallel.
• Fault Tolerance.
• Location Stickiness.