There are millions of tools that are available in the market to do the same type of things but there are only a few of these that stand out. A major classification of these concepts is on the basis of speed and performance and this is where the Apache Spark stands out. When you take apache spark and Scala online training, you will come to know many of its advantages. Apache spark is built on the concepts of Hadoop’s MapReduce. Hadoop is mainly used for the analysis of datasets in big quantities. Since the data sets these days are quite huge, the major challenge was to process it in the quickest time frames. The basic concepts of this are worked upon in a way that the efficiency so that the concepts of Stream Processing and Interactive Queries can be handled in a better way. The main reason behind the introduction of Spark by Apache was to give the needed speed here.
Before learning the apache spark and Scala online training in Dallas there are a few things that you should know at the initial level. You are expected to have a basic knowledge of Scala and how programming is done. Along with this, the knowledge of basic concepts of DBMS and Linux will also be helpful.
The Hadoop is used for the storage as well as the processing of the data in the spark. Additionally, spark is loaded with its personal computations of the cluster management and due to that the major use is limited to data storage only. The main features of spark includes its multiple language compatibility, the speed that it provides to th processing of datasets and the variety of advanced analytics features for the support of Machine Learning, SQL, data streaming, etc.
The implementation of spark is done on the Scala and therefore, if you don’t know the basic concepts and their implementations related to Scala, you would face difficulty working with spark. Shell is a major component in spark and in most of the cases; it is designed using Scala only. However, you could find some options where python is used instead of Scala.
You would rarely meet a developer who is not aware of the concepts of object oriented programming and since Scala works on these concepts, using it for spark and developing the needed programs becomes easy. Since the logic sets and basic functionalities do not change, you can easily take the help of libraries to find things that are far more result oriented in comparison to the other options.
Apart from adding to the speed of the data sets, the combinations of spark and Scala are also known for their security features and high level of productivity. No matter how large amount of data has to be processed, you won’t have to worry about keeping it save and secured. Also, since the process is fast and the chances of errors are minimal, the productivity automatically increases.