Hello Everyone..
As you can see my topic is based on same like comparison in both tool Apache Spark and Apache Hadoop on Big Data and individual features are to be provided.
In this part of project, apache spark components and Hadoop components are compared and then there is comparison between Apache spark and hadoop.
In this i compares the Hadoop and Apache spark where Hadoop is a structure for the appropriated preparing of huge information crosswise over packets of PCs utilizing MapReduce programming information display. Hadoop is accepted to be dependable, adaptable, and blame tolerant. It is outstanding that MapReduce is a solid match for utilizations of handling huge information, however it is a poor fit for emphasis calculations and low-inactivity calculations on the grounds that MapReduce depends on tireless capacity to give adaptation to internal failure, and requires the whole informational collection to be stacked into framework before running scientific inquiries. So that is the reason Spark was conceived.
Comparison between Hadoop and Apache Spark
| Features | Hadoop | Apache Spark |
| Engine for processing of Data | MapReduce of Hadoop is batch processing engine at the core. | Similarly, Apache Spark is also batch processing Engine at the core. |
| Language Support | Streaming of Hadoop are supported by C, C++, Python, Java, Perl, Groovy | Languages supported by AS are Scala, Java, R and Python |
| Language Developed | Java is used for developing Hadoop | Scala is used for developing Spark |
More details are provided in my report on same.
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Vikas Mahla
VikasPRJ702 