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R Programming Language

Shiwani Sharma — Tue, 07 May 2024 07:43:19 +0000

What is R Programming Language?

An open-source programming language, formulated by two professors, Robert Gentleman and Ross Ihaka, in 1993 and developed by the R Development team, was released in 1995. This programming language is used on various platforms such as Linux, Windows, macOS, etc., for statistical computing and graphical presentation. One of the most important functions of the R language is data visualization and analysis. The R language is an open-source and free language that is released under the General Public License (GPL) project. The open source nature means anyone can utilize, modify, and distribute the software as per their requirements.

The name “R” is derived from the initials of its two developers, Robert and Ross. The R language is instrumental in classifications, non-linear modeling, linear modeling, classical statistics, and more. Due to its unique and robust features, it has gained popularity in academic circles. Additionally, its availability for free download from the Free Software Foundation contributes to its widespread use. Users adopt the R language to read data, load it, implement operations, and even create their own functions. Another useful and famous feature of R is looping, which allows users to perform actions repeatedly, such as extracting samples from large datasets.

This is the premier language for data analysis and statistical computing. Its rising popularity can be attributed to several factors. Data scientists, researchers, and statisticians are drawn to it due to its extensive package ecosystem, robust data manipulation capabilities, strong community support, and powerful visualization tools.”

Why Choose the R Language?

One might wonder why they should use the R language. Well, here are some benefits:

Free of cost and open-source: R programing language is an open source that means it is free of cost, you can easily installed as well update it on your system. The other main reason is you don’t ha0ve to buy any license mandatory as well you can shared out and buy it again.
It boasts an extensive community: R language has a very huge number of active community such as numbers of Data Scientists, Developers & Coders. Whenever you need any help you can take it from R, because as you now they have numbers of community that work together. So, you can take any idea with other professionals.
It is platform-independent: In a number of operating system, R has the capacity to run in numbers of these operating system with the identification of software and hardware. You can observe or had observed somewhere that some language like R or Window, Linux, Mac can run properly on the operating systems. and also capable to import the data from MySQL, Microsoft Excel & SQLite.
Incorporates cutting-edge technology.
Segregated from other languages: R language is segregated from other language
A trending language: As you have seen the image in the above article that how R language is utilizing in several industries such as healthcare, insurance, academic etc. the other reason of becoming popular of R language is, it has many community as Data scientists, Developers and Coders. So, everyone wants to learn R because in any industry you are struck in any problem you can take help from them.
A vast resource for data science, machine learning, data visualization, and data analysis.

Features of R Programming:

Data Analysis: R offers a vast collection of tools for data analysis. R programming language is best for data analysis. As we know many data scientists are involved in R language so this is the best programming language in terms of data analysis.
Data Visualization: It provides robust visualization capabilities through packages like base graphics and lattice, enabling users to create graphs and charts.
Open Source: R is freely available for installation as an open-source platform.
Community: With a vast community of data analysts, statisticians, and researchers, it fosters a rich ecosystem of packages.
Data Manipulation: R is a reliable source for various data manipulation tools, including transformation, filtering, summarization, and data cleaning practices.

Industries Using R Language

R language finds applications in numerous industries, including eRtail, Education (Edtech), Fintech, manufacturing, healthcare, data journalism, social media, and more.

Image credit: https://www.guru99.com/r-programming-introduction-basics.html

With a glance at the image above, you will gain an understanding of how R language is being used in various industries. Every sector, including academia, healthcare, government, and insurance, utilizes the R language. Although this data or report is from the year 2017, you can still observe the impact R language has had on multiple industries.

Comparison Between R and Python

Let’s look at the comparison between two popular language that is R and Python.

S.No.	R	Python
01	R language is used for data visualization.	It is used for deep learning.
02	The important package and library of R is tidyverse,ggplot2,etc.	The important package & library are pandas,numpy, Tensor-flow etc.
03	The objective of R is analysis of data as well statistical modeling.	Python objective is web development & in data science.
04	It is formulated for statistical and mathematical computing.	It is created for basis purpose of programming language with the function of code readability.
05	It is open source and free.	It is also free and open source language.

Conclusion

As we know, there are numerous programming languages available in the market. If you want to become a programmer or developer and are confused about which is the best language to learn to brighten your career, R language is one of the best and trending languages, alongside Python, Java, C++, and others. You can choose R language fearlessly; it will undoubtedly help you in your career.

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Presto DB

Shiwani Sharma — Tue, 30 Apr 2024 09:42:54 +0000

What is Presto or Presto DB?

It(Presto) written in the language Java and formulated on 10 November in the year 2013 by Facebook. It is also known as PrestoDB and it helps non-relational data sources and relational data sources. Non-relational data sources are like MongoDB, Base, Amazon S3, HDFS (Hadoop Distributed File System) and relational data sources are Microsoft SQL Server, MySQL, PostgreSQL and Teradata. It’s(Presto) an open-source SQL query engine that is created for a large scale industry that circulated for several servers and for running fast.

Many companies are using this like Facebook, Netflix and some trending network companies are Dropbox, Airbnb, Groupon. It(Presto) is formulated to solve the query immediately and a data infrastructure group of Facebook created this. Several organizations and Facebook allotted for this , while it’s(Presto) become trending for doing interactive queries on Hadoop.

By utilizing Presto per day Facebook solves at least 30, 000 queries. Many data driven companies use this and for them it(Presto) has become a choice. On your data you can easily operate this SQL queries.

It facilitates data where it dwells, which means data that has the query consists of Hadoop, relational databases, Cassandra, NoSQL databases, AWS S3. It also permits the users to access the data from several sources that permit the whole organization for analytics.

Presto as per Wikipedia:

It(including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWSS3, Alluxio, MySQL, MongoDB and Teradata, and allows use of multiple data sources within a query. this is community-driven open-source software released under the Apache License.

Features of Presto

There are some important features of Presto which we are discuss in broadly in points as mentioned below:

All the data sources have been authorized: This feature is very unique and makes presto distinct from other data sources platforms. Presto attaches the data from other sources because it does not have its own storage but it reads the data from them. By Presto, you can utilize numerous data sources at one time and from these multiple data, only one query can cross the source data.

It has the highest speed: Having big data forms a big list of queries such as a user-facing data-driven application. Presto permits to build this without having an intermediary system needing the performance.
By using Presto, your business empower with real-time analytics as well it explore and visualize your data in time, regardless of its size or complexity.

Obtainability is high: If you want to change you can change the worker according to your wish or want or even you can add them also. It (Presto)also provide the high performance as Presto is known for its exceptional query performance. It(Presto) achieves this through techniques like in-memory processing, vectorized execution and pipelining. These optimization minimize data movement and processing overhead, resulting in faster query response times.

Pipelined In-Memory Execution: In presto, there are no other results kept in the disk and it accomplishes the whole processing in memory.

Open Sources: Presto is an open-source project that is maintained by the Presto Software Foundation. The open nature of Presto encourages in fosters innovation, community contribution, and ensure transparency in its development.

Advantage of Presto

One of the important advantage of Presto are as follow:
Anyone can understand this, because it is simple to use and easy to understand.
It operates many queries, it solves over 30,000 queries per day on Facebook, as well on many other network sites.
It is unique and what make it different is because it support ANSI SQL.
It support a large amount of data in very high speed.

Conclusion: Presto DB is formulated to solve the query immediately and a data infrastructure group of Facebook created this. In the conclusion we only conclude that this is a simple language that any one can understand this Presto and can support the large amount of data in very high speed.

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