The problems solved in the big data era are mainly large data sets, so the chosen programming language is the same, which can handle large data sets and solve problems well. Here are some recommended mainstream languages.
#First of all, Java is most commonly used at this stage. Why? This is because there are too many people playing Java and switching to big data, so many people like to use Java. Some companies choose to use Java language development for maintenance and talent use, and some are because the platform has Hadoop. The old MapReduce program is mixed with Spark tasks. Java is chosen to unify the development language of the platform. Some companies also choose the more versatile Java language for development in order to connect with external projects.
Scala can also be said to be the main language for big data Spark development, because after you learn Spark, you will definitely have further research and study on Scala, because in order to learn Spark technology well, you need to study the source code, Need to develop projects more concisely and quickly. Therefore, Scala, the Spark big data development language, is the most popular.
Python, with the rise of machine learning and AI, is also a language favored by many people; there is also a wave of people who like it, that is, big data analysts, who use Python for script scheduling in SQL and spark SQL.
R is a language and operating environment for statistical analysis and graphics. R is a free, free, open source software belonging to the GNU system. It is an excellent tool for statistical calculations and statistical graphics.
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