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Scala Vs Python Vs R Vs Java - Which language is better for Spark & Why?

One of the most important decisions for the Big data learners or beginners is choosing the best programming language for big data manipulation and analysis. Just understanding business problems and choosing the right model is not enough but implementing them perfectly is equally important and choosing the right language (or languages) for solving the problem goes a long way. If you search top and highly effective programming languages for Big Data on Google, you will find the following top 4 programming languages: JavaScalaPythonRJavaJava is one of the oldest languages of all 4 programming languages listed here. Traditional Frameworks of Big data like Apache Hadoop and all the tools within its ecosystem are Java-based and hence using java opens up the possibility of utilizing large ecosystem of tools in the big data world.  ScalaA beautiful crossover between object-oriented and functional programming language is Scala. Scala is a highly Scalable Language. Scala was invented by the German Computer Scientist, Martin Odersky and the first version was launched in the year 2003.PythonPython was originally conceptualized by Guido van Rossum in the late 1980s. Initially, it was designed as a response to the ABC programming language and later gained its popularity as a functional language in a big data world. Python has been declared as one of the fastest-growing programming languages in 2018 as per the recently held Stack Overflow Developer Survey. Many data analysis, manipulation, machine learning, deep learning libraries are written in Python and hence it has gained its popularity in the big data ecosystem. It’s a very user-friendly language and it is its biggest advantage.  Fun factPython is not named after the snake. It’s named after the British TV show Monty Python.RR is the language of statistics. R is a language and environment for statistical computing and graphics. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is named partly after the first names of the first two R authors and partly as a play on the name of S*. The project was conceived in 1992, with an initial version released in 1995 and a stable beta version in 2000.*SS is a statistical programming language developed primarily by John Chambers and R is an implementation of the S programming language combined with lexical scoping semantics, inspired by Scheme.Every framework is implemented in the underlying programming language for its implementation. Ex Zend uses PHP, Panda Framework uses python similarly Hadoop framework uses Java and Spark uses Scala.However, Spark officially supports Java, Scala, Python and R, all 4 languages. If one browses through Apache Spark’s official website documentation, he/she would find many other languages utilized by the open-source community for Spark implementation.    When any developer wants to start learning Spark, the first question he stumbles upon is, out of these pools of languages, which one to use and which one to master? Solution Architects would have a tough time choosing the right language for spark framework and Organizations will always be wondering, which skill sets are relevant for my problem if one doesn’t have the right knowledge about these languages in the context of Spark.    This article will try to answer all these queries.so let’s start-JavaOldest of all and popular, widely adopted programming language of all. There is a number offeatures/advantages due to which Java is favorite for Big data developers and tool creators:Java is platform-agnostic language and hence it can run on almost any system. Java is portable due to something called Java Virtual Machine – JVM. JVM is a foundation of Hadoop ecosystem tools like Map Reduce, Storm, Spark, etc. These tools are written in Java and run on JVM.Java provides various communities support like GitHub and stack overflow etc.Java is scalable, backward compatible, stable and production-ready language. Also, supports a large variety of tried and tested libraries.It is statically typed language (We would see details of this functionality in later sections, in comparison with others)Java is mostly the choice for most of the big data projects but for the Spark framework, one has to ponder upon, whether Java would be the best fit.One major drawback of Java is its verbosity. One has to write long code (number of lines of code) to achieve simple functionality in Java.Java does not support Read-Evaluate-Print-Loop (REPL) which is a major deal-breaker when choosing a programming language for big data processing.ScalaScala is comparatively new to the programming scene but has become popular very quickly. Above are a few quotes from bigger names in the industry for Scala. From the Spark context, many experts prefer Scala over other programming languages as Spark is written in Scala. Scala is the native language of Spark. It means any new API always first be available in Scala.Scala is a hybrid functional programming language because It has both the features of object-oriented programming and functional programming. As an OO Programming Language, it considers every value as an object and all OOPS concepts apply. As a functional programming language, it defines and supports functions. All operations are done as functions. No variable stands by itself. Scala is a machine-compiled language.Scala and Java are popular programming languages that run over JVM. JVM makes these languages framework friendly. One can say, Scala is an advanced level of Java.Features/Advantages of Scala:It’s general-purpose object-oriented language with functional language properties too. It’s less verbose than Java.It can work with JVM and hence is portable.It can support Java APIs comfortably.It's fast and robust in Spark context as its Spark native.It is a statically typed language.Scala supports Read-Evaluate-Print-Loop (REPL)Drawbacks / Downsides of Scala:Scala is complex to learn due to the functional nature of language.Steep learning curve.Lack of matured machine learning languages.PythonPython is one of the de-facto languages of Data Science. It is a simple, open-source, general-purpose language and is very easy to learn. It has a rich set of libraries, utilities, ready-to-use features and support to a number of mature machine learning, big data processing, visualization libraries.Advantages of Python:It is interpreted language (i.e. support to REPL, Read, Evaluate, Print, Loop.) If you type a command into a command-line interpreter and it responds immediately. Java lacks this feature.Easy to learn, easy debugging, fewer lines of code.It is dynamically typed. i.e. can dynamically defined variable types. i.e. Python as a language is type-safe.Python is platform agnostic and scalable.Drawbacks/Disadvantages:Python is slow. Big data professionals find projects built in Java / Scala are faster and robust than the once with python.Whilst using user-defined functions or third party libraries in Python with Spark, processing would be slower as increased processing is involved as Python does not have equivalent Java/Scala native language API for these functionalities.Python does not support heavy weight processing fork() using uWSGI but it does not support true multithreading.R LanguageR is the favourite language of statisticians. R is fondly called a language of statisticians.  It’s popular for research, plotting, and data analysis. Together with RStudio, it makes a killer statistic, plotting, and data analytics application.R is majorly used for building data models to be used for data analysis.Advantages/Features of R:Strong statistical modeling and visualization capabilities.Support for ‘data science’ related work.It can be integrated with Apache Hadoop and Spark easily.Drawbacks/Disadvantages of R:R is not a general-purpose language.The code written in R cannot be directly deployed into production. It needs conversion into Java or Python.Not as fast as Java / Scala.Comparison of four languages for Apache SparkWith the introduction of these 4 languages, let’s now compare these languages for the Spark framework:These languages can be categorized into 2 buckets basis high-level spark architecture support, broadly:JVM Languages: Java and ScalaNon-JVM Languages: Python and RDue to these categorizations, performance may vary. Let’s understand architecture in little depth to understand the performance implications of using these languages. This would also help us to understand the question of when to use which language.Spark Framework High-level architecture An application written in any one of the languages is submitted on the driver node and further driver node distributes the workload by dividing the execution on multiple worker nodes.JVM compatible Application Execution Flow Consider the applications written are JVM compatible (Java/Scala). Now, Spark is also written in native JVM compatible Scala language, hence there is no explicit conversion required at any point of time to execute JVM compatible applications on Spark. Also, this makes the native language applications faster to perform on the Spark framework.There are multiple scenarios for Python/R written applications:Python/R driver talk to JVM driver by socket-based API. On the driver node, both the driver processes are invoked when the application language is non-JVM language.Scenario 1: Applications for which Equivalent Java/Scala Driver API exists - This scenario executes the same way as JVM compatible applications by invoking Java API on the driver node itself. The cost for inter-process communication through sockets is negligible and hence performance is comparable. This is with the assumption that processed data over worker nodes are not to be sent back to the Driver again.Scenario 1(b): If the assumption taken is void in scenario 1 i.e. processed data on worker nodes is to be sent back to driver then there is significant overhead and serialization required. This adds to processing time and hence performance in this scenario deteriorates.Scenario 2: Applications for which Equivalent Java/Scala Driver API do not exist – Ex. UDF (User-defined functions) / Third party python libraries. In such cases equivalent Java API doesn’t exist and hence, additional executor sessions are initiated on worker node and python API is serialized on worker node and executed. This python worker processes in addition to JVM and coordination between them is overhead. Processes also compete for resources which adds to memory contention.In addition, if the data is to send back to the driver node then processing takes a lot of time and problem scales up as volume increases and hence performance is bigger problem.As we have seen a performance, Let’s see the tabular comparison between these languages.Comparison PointsJavaScalaPythonRPerformanceFasterFaster (about 10x faster than Python)SlowerSlowerLearning CurveEasier than JavaTougher than PythonSteep learning curve than Java & PythonEasiestModerateUser GroupsWeb/Hadoop programmersBig Data ProgrammersBeginners & Data EngineersData Scientists/ StatisticiansUsageWeb development and Hadoop NativeSpark NativeData Engineering/ Machine Learning/ Data VisualizationVisualization/ Data Analysis/ Statistics use casesType of LanguageObject-Oriented, General PurposeObject-Oriented & Functional General PurposeGeneral PurposeSpecifically for Data Scientists.Needs conversion into Scala/Python before productizingConcurrencySupport ConcurrencySupport ConcurrencyDoes not Support ConcurrencyNAEase of UseVerboseLesser Verbose than ScalaLeast VerboseNAType SafetyStatically typedStatically typed (except for Spark 2.0 Data frames)Dynamically TypedDynamically TypedInterpreted Language (REPL)NoNoYesYesMaturated machine learning libraries availability/ SupportLimitedLimitedExcellentExcellentVisualization LibrariesLimitedLimitedExcellentExcellentWeb Notebooks SupportIjava Kernel in Jupyter NotebookApache Zeppelin Notebook SupportJupyter Notebook SupportR NotebookWhich language is better for Spark and Why?With the info we gathered for the languages, let's move to the main question i.e. which language to choose for Spark? My answer is not a straightforward single language for this question. I will state my point of view for choosing the proper language: If you are a beginner and want to choose a language from learning Spark perspective. If you are organization/ self employed or looking to answer a question for solutioning a project perspective. I. If you are beginner:If you are a beginner and have no prior education of programming language then Python is the language for you, as it’s easy to pick up. Simple to understand and very user-friendly. It would prove a good starting point for building Spark knowledge further. Also, If you are looking for getting into roles like ‘data engineering’, knowledge of Python along with supported libraries will go a long way. If you are a beginner but have education in programming languages, then you may find Java very familiar and easy to build upon prior knowledge. After all, it grapevine of all the languages.  If you are a hardcore bigdata programmer and love exploring complexities, Scala is the choice for you. It’s complex but experts say if once you love Scala, you will prefer it over other languages anytime.If you are a data scientist, statistician and looking to work with Spark, R is the language for you. R is more science oriented than Python. II. If you are organization/looking for choice of language for implementations:You need to answer the following important questions before choosing the language:Skills and Proficiency: Which skill-sets and proficiency over language, you already have with you/in your team?Design goals and availability of features/ Capability of language: Which libraries give you better support for the type of problem(s) you are trying to solve.Performance implications Details of these explained below: 1. Skillset: This is very straightforward. Whichever is available skill set within a team, go with that to solve your problem, after evaluating answers of other two questions. If you are self-employed, the one you have proficiency is the most likely suitable choice of language.  2. Library Support:  Following gives high-level capabilities of languages:R: Good for research, plotting, and data analysis.Python: Good for small- or medium-scale projects to build models and analyse data, especially for fast start-ups or small teams.Scala/Java: Good for robust programming with many developers and teams; it has fewer machine learning utilities than Python and R, but it makes up for it with increased code maintenance.In my opinion, Scala/Java can be used for larger robust projects to ease maintenance. Also, If one wants the app to scale quickly and needs it to be robust, Scala is the choice.Python and R: Python is more universal language than R, but R is more science oriented. Broadly, one can say Python can be implemented for Data engineering use cases and R for Data science-oriented use cases. On the other hand, if you discover these two languages have about the same library support you need, then pick the one whose syntax you prefer. You may find that you need both depending on the situation. 3. Performance: As seen earlier in the article, Scala/ Java is about 10x faster than Python/R as they are JVM supported languages. However, if you are writing Python/R applications wisely (like without using UDFs/ Not sending data back to the Driver etc) they can perform equally well.ConclusionFor learning, depending upon your prior knowledge, Python is the easiest of all to pick up. For implementations, Choice is in your hands which language to choose for implementations but let me tell you one secret or a tip, you don’t have to stick to one language until you finish your project. You can divide your problem in small buckets and utilize the best language to solve the problem. This way, you can achieve balance between optimum performance, availability, proficiency in a skill, and sub-problem at hand.  Do let us know how your experience was in learning the language comparisons and the language you think is better for Spark. Moreover, which one you think is “the one for you”, through comments below.

Scala Vs Python Vs R Vs Java - Which language is better for Spark & Why?

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Scala Vs Python Vs R Vs Java - Which language is better for Spark & Why?

One of the most important decisions for the Big data learners or beginners is choosing the best programming language for big data manipulation and analysis. Just understanding business problems and choosing the right model is not enough but implementing them perfectly is equally important and choosing the right language (or languages) for solving the problem goes a long way. 

If you search top and highly effective programming languages for Big Data on Google, you will find the following top 4 programming languages: 

  1. Java
  2. Scala
  3. Python
  4. R

Java

Java is one of the oldest languages of all 4 programming languages listed here. Traditional Frameworks of Big data like Apache Hadoop and all the tools within its ecosystem are Java-based and hence using java opens up the possibility of utilizing large ecosystem of tools in the big data world.  

Scala

A beautiful crossover between object-oriented and functional programming language is Scala. Scala is a highly Scalable Language. Scala was invented by the German Computer Scientist, Martin Odersky and the first version was launched in the year 2003.

Python

Python was originally conceptualized by Guido van Rossum in the late 1980s. Initially, it was designed as a response to the ABC programming language and later gained its popularity as a functional language in a big data world. Python has been declared as one of the fastest-growing programming languages in 2018 as per the recently held Stack Overflow Developer Survey. Many data analysis, manipulation, machine learning, deep learning libraries are written in Python and hence it has gained its popularity in the big data ecosystem. It’s a very user-friendly language and it is its biggest advantage.  

Fun fact

Python is not named after the snake. It’s named after the British TV show Monty Python.

R

R is the language of statistics. R is a language and environment for statistical computing and graphics. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is named partly after the first names of the first two R authors and partly as a play on the name of S*. The project was conceived in 1992, with an initial version released in 1995 and a stable beta version in 2000.

*S

S is a statistical programming language developed primarily by John Chambers and R is an implementation of the S programming language combined with lexical scoping semantics, inspired by Scheme.

Every framework is implemented in the underlying programming language for its implementation. Ex Zend uses PHP, Panda Framework uses python similarly Hadoop framework uses Java and Spark uses Scala.

However, Spark officially supports Java, Scala, Python and R, all 4 languages. If one browses through Apache Spark’s official website documentation, he/she would find many other languages utilized by the open-source community for Spark implementation.    

When any developer wants to start learning Spark, the first question he stumbles upon is, out of these pools of languages, which one to use and which one to master? Solution Architects would have a tough time choosing the right language for spark framework and Organizations will always be wondering, which skill sets are relevant for my problem if one doesn’t have the right knowledge about these languages in the context of Spark.    

This article will try to answer all these queries.so let’s start-

Java

Oldest of all and popular, widely adopted programming language of all. There is a number of

features/advantages due to which Java is favorite for Big data developers and tool creators:

  1. Java is platform-agnostic language and hence it can run on almost any system. Java is portable due to something called Java Virtual Machine – JVM. JVM is a foundation of Hadoop ecosystem tools like Map Reduce, Storm, Spark, etc. These tools are written in Java and run on JVM.
  2. Java provides various communities support like GitHub and stack overflow etc.
  3. Java is scalable, backward compatible, stable and production-ready language. Also, supports a large variety of tried and tested libraries.
  4. It is statically typed language (We would see details of this functionality in later sections, in comparison with others)

Java is mostly the choice for most of the big data projects but for the Spark framework, one has to ponder upon, whether Java would be the best fit.

One major drawback of Java is its verbosity. One has to write long code (number of lines of code) to achieve simple functionality in Java.

Java does not support Read-Evaluate-Print-Loop (REPL) which is a major deal-breaker when choosing a programming language for big data processing.

ScalaScala

Scala is comparatively new to the programming scene but has become popular very quickly. Above are a few quotes from bigger names in the industry for Scala. From the Spark context, many experts prefer Scala over other programming languages as Spark is written in Scala. Scala is the native language of Spark. It means any new API always first be available in Scala.

Scala is a hybrid functional programming language because It has both the features of object-oriented programming and functional programming. As an OO Programming Language, it considers every value as an object and all OOPS concepts apply. As a functional programming language, it defines and supports functions. All operations are done as functions. No variable stands by itself. Scala is a machine-compiled language.

Scala and Java are popular programming languages that run over JVM. JVM makes these languages framework friendly. One can say, Scala is an advanced level of Java.

Scala

Features/Advantages of Scala:

  1. It’s general-purpose object-oriented language with functional language properties too. It’s less verbose than Java.
  2. It can work with JVM and hence is portable.
  3. It can support Java APIs comfortably.
  4. It's fast and robust in Spark context as its Spark native.
  5. It is a statically typed language.
  6. Scala supports Read-Evaluate-Print-Loop (REPL)

Drawbacks / Downsides of Scala:

  1. Scala is complex to learn due to the functional nature of language.
  2. Steep learning curve.
  3. Lack of matured machine learning languages.

Python

Python is one of the de-facto languages of Data Science. It is a simple, open-source, general-purpose language and is very easy to learn. It has a rich set of libraries, utilities, ready-to-use features and support to a number of mature machine learning, big data processing, visualization libraries.

Advantages of Python:

  1. It is interpreted language (i.e. support to REPL, Read, Evaluate, Print, Loop.) If you type a command into a command-line interpreter and it responds immediately. Java lacks this feature.
  2. Easy to learn, easy debugging, fewer lines of code.
  3. It is dynamically typed. i.e. can dynamically defined variable types. i.e. Python as a language is type-safe.
  4. Python is platform agnostic and scalable.

Drawbacks/Disadvantages:

  1. Python is slow. Big data professionals find projects built in Java / Scala are faster and robust than the once with python.

Whilst using user-defined functions or third party libraries in Python with Spark, processing would be slower as increased processing is involved as Python does not have equivalent Java/Scala native language API for these functionalities.

  1. Python does not support heavy weight processing fork() using uWSGI but it does not support true multithreading.

R Language

R is the favourite language of statisticians. R is fondly called a language of statisticians.  It’s popular for research, plotting, and data analysis. Together with RStudio, it makes a killer statistic, plotting, and data analytics application.

R is majorly used for building data models to be used for data analysis.

Advantages/Features of R:

  1. Strong statistical modeling and visualization capabilities.
  2. Support for ‘data science’ related work.
  3. It can be integrated with Apache Hadoop and Spark easily.

Drawbacks/Disadvantages of R:

  1. R is not a general-purpose language.
  2. The code written in R cannot be directly deployed into production. It needs conversion into Java or Python.
  3. Not as fast as Java / Scala.

Comparison of four languages for Apache Spark

With the introduction of these 4 languages, let’s now compare these languages for the Spark framework:

These languages can be categorized into 2 buckets basis high-level spark architecture support, broadly:

  1. JVM Languages: Java and Scala
  2. Non-JVM Languages: Python and R

Due to these categorizations, performance may vary. Let’s understand architecture in little depth to understand the performance implications of using these languages. This would also help us to understand the question of when to use which language.

Spark Framework High-level architectureSpark Framework High-level architecture 

An application written in any one of the languages is submitted on the driver node and further driver node distributes the workload by dividing the execution on multiple worker nodes.

JVM compatible Application Execution FlowJVM compatible Application Execution Flow 

Consider the applications written are JVM compatible (Java/Scala). Now, Spark is also written in native JVM compatible Scala language, hence there is no explicit conversion required at any point of time to execute JVM compatible applications on Spark. Also, this makes the native language applications faster to perform on the Spark framework.

There are multiple scenarios for Python/R written applications:

Python/R driver talk to JVM driver by socket-based API. On the driver node, both the driver processes are invoked when the application language is non-JVM language.

Scenario 1: Applications for which Equivalent Java/Scala Driver API exists - This scenario executes the same way as JVM compatible applications by invoking Java API on the driver node itself. The cost for inter-process communication through sockets is negligible and hence performance is comparable. This is with the assumption that processed data over worker nodes are not to be sent back to the Driver again.

Scenario 1(b): If the assumption taken is void in scenario 1 i.e. processed data on worker nodes is to be sent back to driver then there is significant overhead and serialization required. This adds to processing time and hence performance in this scenario deteriorates.

JVM compatible Application Execution Flow

Scenario 2: Applications for which Equivalent Java/Scala Driver API do not exist – Ex. UDF (User-defined functions) / Third party python libraries. In such cases equivalent Java API doesn’t exist and hence, additional executor sessions are initiated on worker node and python API is serialized on worker node and executed. This python worker processes in addition to JVM and coordination between them is overhead. Processes also compete for resources which adds to memory contention.

In addition, if the data is to send back to the driver node then processing takes a lot of time and problem scales up as volume increases and hence performance is bigger problem.

JVM compatible Application Execution Flow

As we have seen a performance, Let’s see the tabular comparison between these languages.

Comparison PointsJavaScalaPythonR
PerformanceFasterFaster (about 10x faster than Python)SlowerSlower
Learning CurveEasier than Java
Tougher than Python

Steep learning curve than Java & PythonEasiestModerate
User GroupsWeb/Hadoop programmersBig Data ProgrammersBeginners & Data EngineersData Scientists/ Statisticians
UsageWeb development and Hadoop NativeSpark NativeData Engineering/ Machine Learning/ Data VisualizationVisualization/ Data Analysis/ Statistics use cases
Type of LanguageObject-Oriented, General PurposeObject-Oriented & Functional General PurposeGeneral PurposeSpecifically for Data Scientists.
Needs conversion into Scala/Python before productizing

ConcurrencySupport ConcurrencySupport ConcurrencyDoes not Support ConcurrencyNA
Ease of UseVerboseLesser Verbose than ScalaLeast VerboseNA
Type SafetyStatically typedStatically typed (except for Spark 2.0 Data frames)Dynamically TypedDynamically Typed
Interpreted Language (REPL)NoNoYesYes
Maturated machine learning libraries availability/ SupportLimitedLimitedExcellentExcellent
Visualization LibrariesLimitedLimitedExcellentExcellent
Web Notebooks SupportIjava Kernel in Jupyter NotebookApache Zeppelin Notebook SupportJupyter Notebook Support

R Notebook

Which language is better for Spark and Why?

With the info we gathered for the languages, let's move to the main question i.e. which language to choose for Spark? 

My answer is not a straightforward single language for this question. I will state my point of view for choosing the proper language: 

  1. If you are a beginner and want to choose a language from learning Spark perspective. 
  2. If you are organization/ self employed or looking to answer a question for solutioning a project perspective. 

I. If you are beginner:

  • If you are a beginner and have no prior education of programming language then Python is the language for you, as it’s easy to pick up. Simple to understand and very user-friendly. It would prove a good starting point for building Spark knowledge further. Also, If you are looking for getting into roles like ‘data engineering’, knowledge of Python along with supported libraries will go a long way. 
  • If you are a beginner but have education in programming languages, then you may find Java very familiar and easy to build upon prior knowledge. After all, it grapevine of all the languages.  
  • If you are a hardcore bigdata programmer and love exploring complexities, Scala is the choice for you. It’s complex but experts say if once you love Scala, you will prefer it over other languages anytime.
  • If you are a data scientist, statistician and looking to work with Spark, R is the language for you. R is more science oriented than Python. 

II. If you are organization/looking for choice of language for implementations:

You need to answer the following important questions before choosing the language:

  1. Skills and Proficiency: Which skill-sets and proficiency over language, you already have with you/in your team?
  2. Design goals and availability of features/ Capability of language: Which libraries give you better support for the type of problem(s) you are trying to solve.
  3. Performance implications 

Details of these explained below: 

1. Skillset: This is very straightforward. Whichever is available skill set within a team, go with that to solve your problem, after evaluating answers of other two questions. 
If you are self-employed, the one you have proficiency is the most likely suitable choice of language.  

2. Library Support:  
Following gives high-level capabilities of languages:

  • R: Good for research, plotting, and data analysis.
  • Python: Good for small- or medium-scale projects to build models and analyse data, especially for fast start-ups or small teams.
  • Scala/Java: Good for robust programming with many developers and teams; it has fewer machine learning utilities than Python and R, but it makes up for it with increased code maintenance.
    In my opinion, Scala/Java can be used for larger robust projects to ease maintenance. Also, If one wants the app to scale quickly and needs it to be robust, Scala is the choice.
    Python and R: Python is more universal language than R, but R is more science oriented. Broadly, one can say Python can be implemented for Data engineering use cases and R for Data science-oriented use cases. On the other hand, if you discover these two languages have about the same library support you need, then pick the one whose syntax you prefer. You may find that you need both depending on the situation. 

3. Performance: As seen earlier in the article, Scala/ Java is about 10x faster than Python/R as they are JVM supported languages. However, if you are writing Python/R applications wisely (like without using UDFs/ Not sending data back to the Driver etc) they can perform equally well.

Conclusion

For learning, depending upon your prior knowledge, Python is the easiest of all to pick up. 

For implementations, Choice is in your hands which language to choose for implementations but let me tell you one secret or a tip, you don’t have to stick to one language until you finish your project. You can divide your problem in small buckets and utilize the best language to solve the problem. This way, you can achieve balance between optimum performance, availability, proficiency in a skill, and sub-problem at hand.  

Do let us know how your experience was in learning the language comparisons and the language you think is better for Spark. Moreover, which one you think is “the one for you”, through comments below.

Shruti

Shruti Deshpande

Blog Author

10+ years of data-rich experience in the IT industry. It started with data warehousing technologies into data modelling to BI application Architect and solution architect.


Big Data enthusiast and data analytics is my personal interest. I do believe it has endless opportunities and potential to make the world a sustainable place. Happy to ride on this tide.


*Disclaimer* - Expressed views are the personal views of the author and are not to be mistaken for the employer or any other organization’s views.

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1 comments

Rahul 01 Jul 2020

Outstanding explanation... Thanks a lot Sir.....

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Having a programming certification will give you an edge over other peers and will highlight your coding skills.Most Popular Programming CertificationsC & C++ CertificationsOracle Certified Associate Java Programmer OCAJPCertified Associate in Python Programming (PCAP)MongoDB Certified Developer Associate ExamR Programming CertificationOracle MySQL Database Administration Training and Certification (CMDBA)CCA Spark and Hadoop Developer1. C & C++ CertificationsRegardless of your specialization in your UG or PG courses, clearing a developer-rated certification will not only make your resume stand out from others but also enhance your skills and boost your confidence. We have curated the top-most and popularly available certifications with descriptions that can help you decide which one is appropriate for your career path.C & C++ Certifications: C and C++ are often called the mother of Procedure-oriented and Object-oriented programming languages, which is absolutely true. These two programming languages have been around for many decades. Colleges and universities all over the world teach these as the base language. To get global recognition for the C and C++ certification, C++ Institute and Pearson VUE decided to carve a niche in this part of the certification landscape by offering the world's first international C/C++ certifications.Aspirants and professionals can choose either C or C++ as a career option/path and climb the certification ladder from associate to professional to senior. The C Programming Language Certified Associate (CLA) and C++ Certified Associate Programmer (CPA) are the core and first-level C and C++ certifications.CLA comprises of topics likeIntroduction to compiling and software development;Basic scalar data types and their operators;Flow control;Complex data types: arrays, structures and pointers;Memory management;Files and streams;Structuring the code: functions and modules;Preprocessor directives and complex declarations.CPA comprises of topics likeIntroduction to compiling and software development;Basic scalar data types, operators, flow control, streamed input/output, conversions;Declaring, defining and invoking functions, function overloading;Data aggregates;String processing, exceptions handling, dealing with namespaces;Object-oriented approach and its vocabulary;Dealing with classes and objects, class hierarchy and inheritance;Defining overloaded operators, user-defined operators, exceptions;Demand and Benefits: Having a CLA certification verifies that the programmer or the aspirant has an understanding of all the necessary and essential universal concepts of computer programming and developer tools. The course also covers all the syntax and semantics of different C constructs plus the data types offered by the language. This course brings crisp knowledge on writing programs using standard language infrastructure regardless of the hardware or software platform.A C++ Certified Associate Programmer (CPA) certification will give you an upper hand because it comprises syntax and semantics of the C++ language plus basic C++ data types. Apart from that, it contains principles of the object-oriented model and C++ implementation. Also, you will get to know about the various C++ standard libraries through this certification process. The average entry-level salary of a C/C++ developer with this certification will be $ 7,415 per annum. With two to three years of experience, the average salary hikes to $ 10,593 annually.Top companies and industries hiring CLA and CPA are Philips, Calsoft Pvt. Ltd., Cognizant, Synopsys Inc., private universities, Mphasis, etc.Where to take Training for Certification: CPP Institute has all the study resources you need to prepare for this examination. Apart from that, you can study from YouTube free resources.Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to expand their knowledge of C/C++ or start their career as a C/C++ programmer or developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification:CLA Certification: $ 147.50 (50% discount voucher)CPA Certification: $ 147.50 (50% discount voucher)Exam fee for certification:CLA Certification: $ 295CPA Certification: $ 295Retake fee for certification: Aspirants who have paid the complete exam price (USD 295) or have completed a course aligned with certification in the self-study mode (50% discount voucher) can have a free retake of the CPA or CLA exam. There is no limit to the number of times a candidate may retake the exam. You must wait 15 days before being allowed to re-sit that exam.2. Oracle Certified Associate Java Programmer OCAJPThis is a Java programming certification provided by Oracle. Java is among the most popular programming languages. James Gosling is the creator of Java which was earlier named Oak. It is a robust, high-level, general-purpose, pure object-oriented programming language developed by Sun Microsystems (now part of Oracle). Java consistently tops the 'most used programming languages’ list and is one of the most extensively used software development platforms. If you have the plan to get a proper training course online before appearing for the certification exam, KnowledgeHut (https://www.knowledgehut.com/programming/java-training) has that for you.It is the preliminary and most basic certification provided by Oracle for Java. It helps gain fundamental understanding of Java programming and builds a foundation in Java and other general programming concepts. The certification encompasses two subcategories –OCAJP Java Standard Edition 8 (OCAJP 8) and  OCAJP Java Standard Edition 11 (OCAJP 11)It comprises of topics likeJava BasicsWorking with Java Data TypesUsing Operators and Decision ConstructsCreating and Using ArraysUsing Loop ConstructsWorking with Methods and EncapsulationWorking with InheritanceHandling ExceptionsClass Methods and EncapsulationDescribing and Using Objects and ClassesHandling ExceptionsJava Technology and the Java Development EnvironmentInheritance and InterfacesUnderstanding ModulesUsing Operators and Decision ConstructsWorking with Java ArraysWorking with Selected classes, Java Primitive Data Types and String APIsDemand and Benefits: Having an OCAJP certification verifies that the aspirant has all the necessary and essential skills to become an expert Java developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The entry-level salary of a junior Java developer with this certification is $ 3670 per annum; when the candidate gathers two to three years of experience, the average salary hikes to $ 5430 annually.Top companies and industries hiring Oracle Certified Associate Java Programmers are Smart Monitor Pvt. Ltd., Fiserv, Micron Semiconductor Asia Pvt. Ltd., private universities and many others.Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for beginners in Java programming. It has workshops with hands-on learning and 40 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course.Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to settle as a Java developer or start his/her career as a Java programmer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fee for Certification: $ 245Application fee for certification:OCAJP8: $ 245OCAJP11: $ 249Exam fee for certification:OCAJP8: $ 245OCAJP11: $ 255Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.3. Certified Associate in Python Programming (PCAP)Python is an interpreted, general-purpose, and high-level programming language developed by Guido Van Rossum. Python released in 1991 and within 5 to 6 years, this programming language become the most popular and widely used programming language in various disciplines. Today, companies use Python for GUI and CLI-based software development, web development (server-side), data science, machine learning, AI, robotics, drone systems, developing cyber-security tools, mathematics, system scripting, etc. PCAP is a professional Python certification credential that measures your competency in using the Python language to create code and your fundamental understanding of object-oriented programming.It comprises of topics likeBasic concepts of PythonOperators & data typesControl and EvaluationsModules and PackagesData AggregatesException HandlingStringsFunctions and ModulesObject-Oriented ProgrammingList Comprehensions, Lambdas, Closures, and I/O OperationsClasses, Objects, and ExceptionsDemand and Benefits: Having a Python certification verifies that the programmer or the aspirant has all the necessary and essential skills needed to become an expert Python developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The average entry-level salary of a Python developer starts at around $100k per annum. With a few years of experience, the average salary hikes to $ 105k annually.Top companies and organizations hiring certified Python programmers are Bank of America, Atlassian, Google, Adobe, Apple, Cisco Systems, Intel, Lyft, IBM, etc.Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for beginners in Python programming. It has hands-on learning with 24 hours of instructor-led online lectures. Apart from that, the course has 100 hours of MCQs and three live projects.Who should take the Training (roles) for Certification: Any programmer, graduate, post graduate student, or computer science aspirant - who wants to pursue a career as a Python developer or  Python programmer can opt for this certification training. There is no other prerequisite to appear for this exam.Course fees for Certification:  $ 295Exam fee for certification: $ 295Retake fee for certification: If a candidate fails the exam, he/she has to wait for 15 days before being allowed to retake the exam for free. There is no limit to the number of times a candidate may retake an exam.4. MongoDB Certified Developer Associate ExamMongoDB is a NoSQL, document-based high-volume heterogeneous database system. Instead of having tables with rows and columns, MongoDB uses a collection of documents. It is a database development system that provides scalability and flexibility as per query requirements. Its document models are easy to implement for developers and can meet complex demands at scale.MongoDB created this MongoDB Certified Developer Associate Exam for individuals who require to verify their knowledge on fundamentals of designing and building applications using MongoDB. They recommend this certification for those who want to become software engineers and have a solid understanding of core MongoDB along with professional experience.It comprises of topics likeMongoDB BasicsCRUDIndexing and PerformanceThe MongoDB Aggregation FrameworkBasic Cluster AdministrationAggregation & ReplicationShardingMongoDB Performance  MongoDB for Python DevelopersMongoDB for Java Developers or MongoDB for JavaScript DevelopersData ModelingDemand and Benefits: Having a MongoDB Certified Developer Associate Exam certification verifies that the programmer or the aspirant has all the necessary and essential skills to become a NoSQL database expert. The MongoDB certification is inexpensive and in demand. The average salary for a software developer with MongoDB skills starts from $ 8200 per annum.Top companies and organizations hiring certified MongoDB developers are Accenture, Collabera, Leoforce LLC., Adobe, Trigent Software, Lyft, etc.Where to take Training for Certification: KnowledgeHut has a comprehensive course structure for those who want to learn MongoDB & Mongodb Administrator. It has 24+ hours of instructor-led online lectures and 80+ hours of hands-on with cloud labs. This self-paced course also includes capstone projects to give participants a feel of real world working.  Who should take the Training (roles) for Certification: Any programmer, graduate, post graduate student, experienced developer or computer science aspirant - who wants to embark on a career as a MongoDB developer or start his/her career as a NoSQL database expert or do better in their current role as a MongoDB developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification:  $ 150Exam fee for certification: $ 150Retake fee for certification: MongoDB University is no longer allowing a free retake with the exam fee. The candidate has to pay an additional $10 to reschedule or retake the exam.5. R Programming CertificationIt is a part of the data science specialization from Johns Hopkins University under Coursera. This course teaches R programming for efficient data analysis. It covers different R programming concepts like building blocks of R, datatypes, reading data into R from external files, accessing packages, writing functions, debugging techniques, profiling R code, and performing analysis.It comprises of topics like:Basic building blocks in RData types in RControl StructuresScoping Rules - OptimizationCoding StandardsDates and TimesFunctionsLoopingDebugging toolsSimulating data in RR ProfilerDemand and Benefits: Having an R Programming certification verifies that the programmer or the aspirant has all the necessary and essential skills require to get a job role as data analyst. This certification also helps in getting an internship or entry-level jobs in different organizations and firms. The average salary of a certified R programmer with this certification is ₹ 508,224 per annum.Top companies and industries hiring certified R programmers are Technovatrix, CGI Group Inc., Amazon, Sparx IT Solutions, Accenture, Uber, etc.Where to take Training for Certification: KnowledgeHut has a fascinating training course for those who wants to become a R programmer. It has 22+ hours of instructor-led live training and three self-paced live projects.Who should take the Training (roles) for Certification: Any data analyst, graduate, post graduate student, experienced data analyst or computer science aspirant - who wants to settle as a R programmer or data analyst can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: FreeFee for certification: $ 60 (Coursera Plus Monthly)Retake fee for certification: Free6. Oracle MySQL Database Administration Training and Certification (CMDBA)It is another course offered by Oracle for SQL developers. Oracle University designed this course for database administrators who want to validate their skills with developing performance, blending business processes, and accomplishing data processing work. Structured Query Language (SQL) is one of the top database management query languages that allows us to access and manipulate databases. If you want to verify your database skills during a job interview or impress your peers at your workplace then this certification is worth getting. This certification path includes Professional, Specialist, and Developer levels. The candidate should pass the MySQL Database Administrator Certified Professional Exam Part 1 & Part 2 to earn the certification.It comprises of topics likeInstalling MySQLMySQL ArchitectureConfiguring MySQLUser ManagementMySQL SecurityMaintaining a Stable SystemOptimizing Query PerformanceBackup StrategiesConfiguring a Replication TopologyDemand and Benefits: Having an CMDBA certification verifies that the programmer or the aspirant has all the necessary and essential skills required to get a job role as SQL developer. This certification also helps in getting an internship or entry-level jobs in different organizations and firms. The average salary of a certified MySQL DBA or backend developer with this certification is $ 66,470 per annum.Top companies and industries hiring Certified MySQL database administrators are Fiserv, IBM, HCL, Adobe, Microsoft, Apple, Accenture, Collabera, and more.Where to take Training for Certification: KnowledgeHut has a cutting-edge curriculum for those who want to become  MySQL database administrators. It has 16+ hours of instructor-led online lectures and 80+ hours of hands-on lab. Apart from that, this self-paced course has Capstone projects.Who should take the Training (roles) for Certification: Any developer, graduate, post graduate student, experienced developer or computer science aspirant - who wants to pursue a career as a DBA or backend developer or start his/her career in database management or backend software development can opt for this certification course. There is no other prerequisite to appear for this exam or course.Course fees for Certification: $ 255Exam fee for certification: $ 255Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days after the initial attempt.7. CCA Spark and Hadoop DeveloperWith the exponential growth in data, IT firms and organizations have to manage this tremendous amount of data generated. So, many companies are actively looking for Big data and Spark developers who can optimize performance. Big Data is the term used to describe enormous volumes of data. Apache Spark supports data management as it is an open-source centralized analytics engine that handles large-scale data processing.It requires prerequisite knowledge of Scala and Python. This certification also verifies and showcases your skills through Spark and Hadoop projects. Passing this certification course gives you a logo and a license to authenticate your CCA status.It comprises of topics likeLoad data from HDFS for use in Spark applicationsWrite the results back into HDFS using SparkRead and write files in a variety of file formatsPerform standard extract, transform, load (ETL) processes on data using the Spark APIUse metastore tables as an input source or an output sink for Spark applicationsUnderstand the fundamentals of querying datasets in SparkFilter data using SparkWrite queries that calculate aggregate statisticsJoin disparate datasets using SparkProduce ranked or sorted dataSupply command-line options to change your application configuration, such as increasing available memoryDemand and Benefits: Passing the CCA Spark and Hadoop Developer Exam (CCA175) by Cloudera verifies that you have all the essential skills required to get a job as a Hadoop developer and handle Big data projects. The average salary of a certified CCA Spark and Hadoop Developer with this certification is $ 74,200 per annum.Top companies and industries hiring Certified Spark and Hadoop Developers are Primus Global, IBM, Collabera, CorroHealth, Genpact, Xerox, Accenture, and more.Where to take Training for Certification: KnowledgeHut has extensive courses for those who want to become Big Data experts and want to work as Hadoop developers. It has different courses on Big Data Analytics, Apache Storm, Hadoop Administration, Apache Spark & Scala, Big Data with Hadoop, and more.Who should take the Training (roles) for Certification: Any Big Data developer, graduate & post graduate students, Hadoop developer or computer science aspirant - who wants to make a career in Big data development or start his/her career as a Big Data or Hadoop project developer can opt for this certification course. There is no other prerequisite to appear for this exam.Course fees for Certification: $ 295Application fee for certification: $ 295Exam fee for certification: $ 295Retake fee for certification: Within 30 to 60 minutes of exam completion, Cloudera will send a scorecard mail with a pass or fail status. If the candidate fails the exam, then they have to wait for 30 days for another try.  Cloudera gives additional discounts on retakes.ConclusionWhether you are starting your career as a coder or are an experienced programmer looking to grow in the industry, having a certification and proper knowledge of any popular programming language is one of the most proven ways to elevate your programming career.  We trust that this article will help you to understand your area of interest. Choose the programming language you wish to make a career in, wisely. This would also depend on your pre-existing knowledge. If you aren't sure which resource will be more informative for doing your certification as per your area of interest, KnowledgeHut (https://www.knowledgehut.com/) has all the support and expert trainers who can guide you, from start to finish—that is in clearing the exam and helping you gain sound knowledge of your preferred subject.Receiving a programming certification is an added bonus which will make you stand out from the rest. Proper training from an institute such as KnowledgeHut will help you gain skills that are relevant and in demand in the industry.
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Top-Paying Programming Certifications for 2021

Programming is at the core of software development... Read More

Top IT Certifications for Java Developers in 2021

Programming languages are at the heart of computer science and software development. They help developers write efficient code for developing digital solutions through applications and websites. Programming helps in automating, maintaining, assembling, and measuring the processed data.  Java is one such popular programming language. It is a robust, high-level, general-purpose, pure object-oriented programming language developed by Sun Microsystems (now part of Oracle). James Gosling is the creator of Java which was earlier named Oak. Java ranks high in the top programming languages list and is one of the most extensively used software development platforms. It is well suited to developing software solutions and other innovative projects and simulations.  Since Oracle acquired Sun Microsystems in January 2010, they have been responsible for the further development of the Java platform. All the mentioned top Java certifications verify a specific expertise level and knowledge of the Java platform highlighting particular domains. Without further due, let us now dig into the top 5 Java certifications and their details. About Oracle’s Java CertificationsOrganizations and industries consider certifications as proof of knowledge, especially when the certifications are from a recognized body or firm. Aspirants and professionals looking for possibilities in the Java development domain can avail of a plethora of benefits through the certifications mentioned in this article. There are six levels of Oracle Java Certification based on job roles, skills, and responsibilities: Oracle Certified Junior Associate (OCJA) Oracle Certified Associate (OCA) Oracle Certified Professional (OCP) Oracle Certified Specialist (OCS) Oracle Certified Expert (OCE) Oracle Certified Master (OCM) Among them, the top five Java certifications that are in demand for the year 2021 are – 1. Oracle Certified Associate Java Programmer OCAJPIt is the preliminary and most basic certification provided by Oracle for Java. It helps you gain fundamental understanding of Java programming and build a foundation in Java and other general programming concepts. There are two subcategories in this certification – OCAJP Java Standard Edition 8 (OCAJP 8) and  OCAJP Java Standard Edition 11 (OCAJP 11) OCAJP8 comprises of topics like  Creating and Using Arrays Handling Exceptions Java Basics Using Loop Constructs Using Operators and Decision Constructs Working with Inheritance Working with Java Data Types Working with Methods and Encapsulation Working with Selected classes from the Java API OCAJP11 comprises of topics like Applying Encapsulation Creating and Using Methods Creating Simple Java Programs Describing and Using Objects and Classes Handling Exceptions Java Technology and the Java Development Environment Programming Abstractly Through Interfaces Reusing Implementations Through Inheritance Understanding Modules Using Operators and Decision Constructs Working with Java Arrays Working with Java Primitive Data Types and String APIs Demand and Benefits: Having an OCAJP certification verifies that the programmer or the aspirant has all the necessary and essential skills to become an expert Java developer. This certification also helps in getting an internship or entry-level jobs in different organizations. The entry-level salary of a junior Java developer with this certification is $ 3670 per annum; when the candidate gathers two to three years of experience, the average salary hikes to $ 5430 annually.   (Source: Glassdoor) Top companies and industries hiring Oracle Certified Associate Java Programmers are Smart Monitor Pvt. Ltd., Fiserv, Micron Semiconductor Asia Pvt. Ltd., and more. Where to take Training for Certification: KnowledgeHut has a fascinating course, designed for beginners in Java programming. It offers hands-on learning with 40 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant - who wants to be a Java developer or start his/her career as a Java programmer can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. 2) Oracle Certified Professional Java Programmer OCPJPIt is a professional-level certification program provided by Oracle for Java developers. It verifies the candidates' knowledge and professional expertise. Using this certification, aspirants and other hard-core Java programmers can distinguish themselves from those Java professionals who are not certified. It comes in the second level of Oracle's Java Certification list. There are two subcategories of this certification – OCPJP Java Standard Edition 8 (OCPJP 8) and  OCPJP Java Standard Edition 11 (OCPJP 11) This certification is preferable if someone has professional experience with Java or has already worked for some years in Java technology.  OCPJP8 comprises of topics like: Advanced Class Design Building Database Applications with JDBC Concurrency Exceptions and Assertions Generics and Collections Java Class Design Java File I/O (NIO.2) Java I/O Fundamentals Java Stream API Lambda Built-in Functional Interfaces Localization Use Java SE 8 Date/Time API OCPJP11 comprises of topics like: Annotations Built-in Functional Interfaces Concurrency Database Applications with JDBC Exception Handling and Assertions Functional Interface and Lambda Expressions Generics and Collections I/O (Fundamentals and NIO.2) Java Fundamentals Java Interfaces Java Stream API Lambda Operations on Streams Localization Migration to a Modular Application Parallel Systems Secure Coding in Java SE Application Services in a Modular ApplicationDemand and Benefits: Once you are a certified Professional Java Programmer (OCPJP), you can switch to better salary slabs and organizations that hire senior Java developers. This certification also helps in getting internal promotions as Java developers in different organizations and firms. The average salary of a certified professional Java developer is $ 5300 - $ 8610 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are Oracle, Capgemini, Morgan Stanley, Chetu, Mphasis, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for Java developers and professionals for learning intermediate Java topics. It has hands-on learning with 32 hours of instructor-led online lectures. Apart from that, Oracle also provides exam vouchers for this certification course. Who should take the Training (roles) for Certification: Any Java programmer who wants to apply for a senior Java developer's role or start his/her career as a Java programmer can opt for this professional certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.3. Oracle Certified Expert - Web Component Developer OCEWCDIt is an intermediate-level course offered by Oracle for Java web developers. The Oracle Certified Expert Web Component Developer is for web developers who want to write web applications using Java. Through this course, they can prove their expertise in developing web apps using JSP and Servlet technologies. It verifies your expertise in Servlet 3.0 and helps in creating dynamic Web content and Web services.  It comprises of topics like Understanding Java EE Architecture Managing Persistence using JPA entities and Bean Validation Implementing business logic using EJBs Using Java Message Service API Implement SOAP Services using JAX-WS and JAXB APIs Creating Java Web Applications using Servlets and JSPs Implementing REST Services using JAX-RS API Creating Java Applications using WebSockets Developing Web Applications using JSFs Securing Java EE 7 Applications Using CDI Beans Demand and Benefits: You can opt for this course once you are a certified Professional Java Programmer (OCPJP) or certified associated Java programmer. This certification course will help you get a job in organizations having rigorous work in Servlet, Java Server Page, JSF, and web microservices. The average salary of a certified professional Java developer is $ 8,850 - $ 11,930 per annum. Top companies and industries hiring Oracle Certified Web Component Developers are Amdocs, IBM, Oracle, Capgemini, SAP, Shine, Byjus, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity for Java web developers (. It has hands-on learning with instructor-led online lectures and live projects. Apart from this, you can get online training from Oracle University as wellWho should take the Training (roles) for Certification: Any programmer or computer science aspirant who wants to settle as a Java web developer or start his/her career as a Java web content and web service developer can opt for this certification course. As a prerequisite, you have to pass the OCPJP to opt for this certification.  Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. 4. Oracle Certified Professional Java Application Developer (OCPJAD)It is an advanced-level course offered by Oracle for Java application developers. The Oracle Certified Professional Java Application Developer (OCPJAD) is for software developers who want to write different applications and automation tools using Java. Through this course, developers can prove their expertise and abilities to develop and deploy applications through Java Enterprise Edition 7. OCPJAD is ideal for desktop application developers, frontend + backend app developers, software engineers, and application architects. It comprises of topics like Creating Batch API Developing CDI Beans Concepts of Concurrency Creating Java Applications with Web-Sockets Creating Java Web Applications with JSPs Developing Java Web Applications with Servlets Developing Web Applications with JSFs Implementing Business Logic with EJBs Performing REST Services with JAX-RS API Implementing SOAP Services with JAX-WS and JAXB APIs Java EE 7 system architecture Java EE 7 Security Techniques Java Message Service API Managing Persistence with JPA Entities and Bean-ValidationDemand and Benefits: Once you pass the Certified Professional Java Application Developer (OCPJAD), you can seek employment in organizations that work on critical application development and command higher salaries. This professional certification will give you exposure to develop APIs, implementing business logic using EJBs, create message services, and apply security systems. The average salary of a certified professional application developer is $ 9,800 - $ 13,910 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are Oracle, Capgemini, NetSuite Inc., SAP, Cognizant, etc. Where to take Training for Certification: KnowledgeHut has a fascinating course opportunity with hands-on learning exposure and live projects. Apart from this, you can get online training from Oracle University as well. Who should take the Training (roles) for Certification: Any Java developer or full-stack application developer who wants to become a certified Java application developer or move to the specialized sector of API development using REST, security architect or software engineer can opt for this certification course. As a prerequisite, you should have passed the OCAJP certification.  Course fees for Certification:  $ 245 Application fee for certification: $ 245 Exam fee for certification: $ 245 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days.5. Oracle Certified Master Java Enterprise Architect (OCMJEA)Large-scale development and service firms have different critical applications and systems to develop, manage, and maintain. Such systems require full-stack developers and specialized professionals with proven skills. Such organizations and MNCs hire only highly experienced professionals and specialists who can supervise the extensive operation, architect the defects, and define & develop systems as per requirements. The Oracle Certified Master Java Enterprise Architect (OCMJEA) is one of the most prestigious Java certifications a Java developer can achieve.  It comprises of topics like Architect Enterprise Applications through Java EE Developing Applications for the Java EE 6 Developing Applications for the Java EE 7 Developing Applications with Java EE 6 on WebLogic Server 12c Java Design Patterns Java EE 6: Develop Business Components with JMS & EJBs Java EE 6: Develop Database Applications with JPA Java EE 6: Develop Web Services with JAX-WS & JAX-RS Java EE 7: New Features Java SE 7: Develop Rich Client Applications Java SE 8: Programming Java SE 8 Fundamentals Object-Oriented Analysis and Design Using UML, etc. Demand and Benefits: Once you pass the Certified Master Java Enterprise Architect course, you get the essential skills and understanding of how to execute application development on an enterprise level. Such an experienced professional gains full-stack Java development skills. They get hired with the responsibility of undertaking Java projects from the very start to their final delivery. Many Certified Master Java Enterprise Architects work as managers or senior managerial roles in industries and firms. The average salary of a certified professional application developer is $ 14,000 - $ 19,210 per annum. Top companies and industries hiring Oracle Certified Professional Java Programmers are IBM, Oracle, Microsoft, HCL, Capgemini, NetSuite Inc., SAP, Cognizant, Atlassian, etc. Where to take Training for Certification: KnowledgeHut has a fascinating Java course  with hands-on learning exposure and a live project. Apart from that, a professional can train himself through ILT (Instructor-Led-in-Class), Learning Subscription, TOD (Training on Demand), LVC (Live Virtual Class), or classes delivered by Oracle Authorized Education Center . Other Oracle Authorized Partner Oracle Academy, Oracle University Training Center, or Oracle Workforce Development Program can also benefit and train you in this course.  Who should take the Training (roles) for Certification: Any Java developer or full-stack application developer who wants to move to a senior role in the enterprise-level or want to become a manager or team lead can opt for this certification course. As a prerequisite, you need to have passed the OCPJP certification.  Course fees for Certification:  $248 Application fee for certification: $ 248 Exam fee for certification: $ 248 Retake fee for certification: Aspirants can retake the exam if the exam voucher has a free retake option. If the exam retake option is available, one can opt for the exam after 14 days. Java is an evergreen programming language and is here to stay, at least for the next couple of decades. A vast community of professionals and entry-level aspirants enjoy the benefit of this pure object-oriented, class-based, multi-paradigm, high-level programming language. Java Certification requires proper training.KnowledgeHut has the required infrastructure and quality education faculty, both online and offline, to train aspirants for these Oracle Certifications. It caters to well-structured, industry-oriented Java certification training, explicitly designed to serve the candidates according to the latest industry needs. Getting proper training from KnowledgeHut will help aspirants master core knowledge of Java plus equip themselves with the industry standards to manage large projects. 
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Top IT Certifications for Java Developers in 2021

Programming languages are at the heart of comput... Read More

Best Python Certifications of 2021

Programming is always at the core of computer science and Information Technology. Every year millions of programmers graduate with a degree and look for opportunities in the job market. The demand for programmers is growing exponentially, and this demand is not going anytime soon. Python was released by Python Software Foundation in 1991, and in just a few years, has become the most popular and widely used programming language in various disciplines.Python is an interpreted, general-purpose, and high-level programming language developed by Guido Van Rossum. Today, companies use Python for GUI and CLI-based software development, web development (server-side), data science, machine learning, AI, robotics, drone systems, developing cyber-security tools, mathematics, system scripting, etc.According to TIOBE index, Python ranks second among all other programming languages. KnowledgeHut has some fascinating advanced-level courses on Python, such as Machine Learning using Python and Artificial Intelligence using Python.Once you gain expertise in writing Python programs, candidates can start learning advanced-level Python libraries and modules such as Pandas, SciPy, NumPy, Matplotlib, etc. There are different options one can explore after learning Python. These are data analysis, machine learning, cybersecurity, automation, web scraping, etc.Top Python Certifications of 2021Certified Entry-Level Python Programmer (PCEP) Certified Associate in Python Programmer (PCAP) Introduction to Programming Using Python by Microsoft Certified Professional in Python Programming 1 & 2 (PCPP 1 & 2) Certified Expert in Python Programming (PEPP) During the course of your Python certification training and exam preparation, you will develop different real-world projects and get familiar with case studies. Also, there will be hands-on lab experiences in Python programming. In this article, you will get to know the top five Python certifications of 2021 that can give you the launchpad you need to embark on a successful career.   1. Certified Entry-Level Python Programmer (PCEP): The PCEP is an entry-level Python certification. To enroll in this course, you need to have a basic understanding of how procedural programming works. Also, some knowledge of flowcharts and algorithm creation will benefit you. Through this certification, an aspirant can gain the core and fundamental understanding of Python. This certification from the Python Institute will make you proficient in Python programming and help you become a Python certified professional. Aspirants and professionals can choose Python as a career option/path and climb the Python Institute’s certification ladder from associate to professional.PCEP comprises of topics like Basic formatting and outputting methods Handling Boolean values Compilation vs. interpretation Constants, Variables and Variable naming conventions Defining user-defined functions Fundamentals of computer programming Inputting and converting Data Logical vs. bitwise operations in Python Looping and control statements Lists New data aggregates: Tuples and Dictionaries The assignment operator Primary kinds of data and numerical operators Rules governing the building of expressions Working with multi-dimensional arrays Different slicing operations Demand and Benefits: Having a PCEP certification verifies that the programmer or the aspirant has knowledge of all the necessary and fundamental Python concepts. The course also covers all the syntax and semantics of different Python constructs & data types offered by the language. This course brings crisp knowledge on general coding techniques using standard language infrastructure and basic programming skills using Python. The average entry-level salary of a Python programmer with this certification will be $ 5660 per annum. Top companies and industries hiring PCEP are Philips, Cataleya Pvt. Ltd., Deloitte, Zynga, Mphasis, VMware, etc.Where to take Training for Certification: Python Institute has all the study resources you need to prepare for this examination. Apart from that, you can join the Python course offered by KnowledgeHut  that has 24 hours of instructor-led training covering the core programming concepts like operators, control flow, functions, syntax & indentations. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant, who wants to learn Python or start an internship or entry-level job as Python programmer can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 295 Application fee for certification: $ 295 Exam fee for certification: $ 295 Retake fee for certification: If a candidate fails the exam, he/she can wait 15 days before being allowed to retake the exam for free. There is no limit on the number of times a candidate may retake the exam.2. Certified Associate in Python Programmer (PCAP):PCAP is another important second-level or associate-level certification exam for Python. This course and certification will give you the confidence to measure your skill and complete the Python-based coding tasks. It also facilitates competing for competitive coding sessions. This course also comprises the essential notions and concepts related to object-oriented programming. With this associated-level certification, you can stand unique in the competitive job market. PCAP comprises of topics like Basic formatting and outputting methods Python basics Using Boolean values Compilation vs. interpretation Variables and variable naming conventions Defining and using functions Fundamentals of computer programming Fundamentals of OOP  How to use OOPs in the Python programming language Generators and closures Inputting and converting of data Logical vs. bitwise operations Looping and control statements File processing for Python developers Name scope issues New data aggregates: tuples and dictionaries Primary kinds of data and numerical operators Python modules Inheritance in Python Rules for creating expressions Working with multi-dimensional arrays Strings, lists, and other Python data structures The assignment operator The concept of exceptions and implementation Demand and Benefits: Having a PCAP certification verifies that the programmer or the aspirant has all the necessary and essential concepts of intermediate-level Python programming. The course also covers all the fundamental concepts of different Python constructs & fundamentals of OOP. This course brings crisp knowledge on general coding techniques using standard language infrastructure and basic programming skills using Python. The approximate salary of a Python programmer with this certification will be $7000 to $11,262 per annum. Top companies and industries hiring PCAP are CareCentrix, Accenture, Deutsche Bank, Collabera, NetApp, Capgemini, Tech Mahindra, Myntra, etc. Where to take Training for Certification: Python Institute (https://pythoninstitute.org/free-python-courses/) has all the study resources you need to prepare for this examination. You can also get a comprehensive training by enrolling for the Python course offered by KnowledgeHut (https://www.knowledgehut.com/programming/python-programming-certification-training) that has 24 hours of instructor-led training covering the core programming concepts like operators, control flow, functions, syntax & indentations. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant, who wants to build a career in Python or pursue an associate-level job as a Python programmer or developer, can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 295 Application fee for certification: $ 295 Exam fee for certification: $ 295 Retake fee for certification: If a candidate fails the exam, he/she can wait 15 days before being allowed to retake the exam for free. There is no limit to the number of times a candidate may retake an exam. 3. Introduction to Programming Using Python by MicrosoftIt is another popular entry-level Python certification by Microsoft (https://docs.microsoft.com/en-us/learn/certifications/exams/98-381). This certification covers all the syntax, data types, and basic understanding of Python. It also teaches how to logically solve any problem using Python constructs. Candidates wanting to enroll for this course are expected to have had some instruction or hands-on experience of approximately 100 hours with the Python programming language, including debugging skills, logic development, understanding conditional & decision-making statements, and maintaining well-formed well documented Python code. Microsoft’s Introduction to Programming Using Python comprises of topics like Basics of Python Using Boolean values Fundamentals of computer programming Interpretations Variables and variable naming conventions Defining and using functions Indexing and slicing operations Type conversions Basic formatting and outputting Data Types and Operators Control Flow with Decisions and Loops Construct Data structures Jump Statements Perform Input and Output Operations Document and Structure Code Comments and white-spaces Perform Operations Using Modules and Tools Demand and Benefits: Having a Microsoft certification verifies that the Python programmer or the aspirant has all the necessary and fundamental Python concepts. The course also covers all the syntax and semantics of different Python constructs & data types offered by the language. Anyone with this certification will have a better understanding of core Python, and the candidate can stand out in the competitive exams from the rest. The average entry-level salary of a Python programmer with this certification will be $ 5660 per annum. Top companies and industries hiring Python professionals with this credential are Cataleya Pvt. Ltd., Zynga, VMware, Mphasis, Deloitte, Capgemini, etc. Where to take Training for Certification: Microsoft has a paid five-day instructor-led course to prepare for this examination. Apart from that, you can join the Python course offered by KnowledgeHut that has 24 hours of instructor-led training covering the core programming concepts like operators, control flow, functions, syntax & indentations. Who should take the Training (roles) for Certification: Any programmer or computer science aspirant, who wants to learn Python or start an internship or entry-level job as Python programmer, can opt for this certification course. There is no other prerequisite to appear for this exam. Course fees for Certification: $ 127 Application fee for certification: $ 127 Exam fee for certification: $ 127 Retake fee for certification: Exam retake is free. If the candidate fails to achieve a passing score on the first attempt, he/she must wait 24 hours before retaking the exam. 4. Certified Professional in Python Programming 1 & 2 (PCPP 1 & 2):Once you sound knowledge of the core concepts of Python or have 3 to 5 years of experience in Python programming, you may prepare for professional Python certification. Certified Professional in Python Programming 1 certifications will reflect your experience and programming skills in the following areas: Text File Handling GUI-based Programming Encapsulation Inheritance Advanced Object-Oriented Programming PEP conventions Metaprogramming Communicating with a program's environment Using Libraries and Modules Importing math, science, and engineering modules Having this globally recognized credential will make you stand out in a competitive job market. Many recruiting agencies and firms are looking for professional Python programmers who can develop and deploy applications. Certified Professional in Python Programming 2 (PCPP2) is another advanced-level professional certification course offering proficiency in Python-MySQL database handling. Certified Professional in Python Programming 2 certification will reflect your experience and programming skills in the following areas: Basic directory structure CRUD operations Design patterns Observer and Proxy Singleton and State Design Template Method Model-View-Controller using Python Multiprocessing, threading, subprocess, and multiprocessor synchronization Relational database management using Python MySQL and SQL commands Sharing, storing and installing packages Network programming in Python Application testing techniques and principles Demand and Benefits: Having a PCPP certification verifies that the Python developer has all the necessary and essential skills of a professional Python programmer. The course covers all the advanced object-oriented programming concepts, GUI programming, etc. This course brings crisp knowledge for experienced professionals to make them stand out in the software development industry. The approximate salary of a Python programmer with this certification will be $ 12,053 to $ 14,700 per annum. Top companies and industries hiring PCPP certified professionals are Dell, Accenture, SG Analytics, HCL, Oracle, Capgemini, Tech Mahindra, Flipkart, etc. Where to take Training for Certification: Python Institute has all the study resources you need to prepare for this examination. Apart from that, you can join the Python course offered by KnowledgeHut that has 32 hours of instructor-led training covering the advanced programming concepts like database handling, OOPs, logical layout, data visualization, etc. Who should take the Training (roles) for Certification: Any professional, programmer, or experienced Python developer - who wants to settle as a senior Python developer or pursue an experienced-level job as a Python programmer or developer can opt for this certification course. The candidate should have the Certified Associate in Python Programmer (PCAP) certification or few years of work experience in Python. Course fees for Certification: $ 195 Application fee for certification: $ 195 Exam fee for certification: $ 195  Retake fee for certification: If a candidate fails the exam, he/she can wait 15 days before being allowed to retake the exam for free. There is no limit to the number of times a candidate may retake an exam. 5. Certified Expert in Python Programming (CEPP):This Python certification tag is for experts who complete all the OpenEDG Python Institute's Programming certification program (PCAP-31-xx, PCPP-32-1-xx, and PCPP-32-2-xx exams). It is the most advanced credential a Python developer can achieve from the Python Institute. Having this globally recognized credential will verify your expertise in Python programming. It highlights expertise in the universal concepts of Python programming. Also, this certification showcases the skills in resolving typical implementation challenges on different verticals of Python. Demand and Benefits: Having a CEPP certification verifies that the Python developer has industry level expertise in Python. This certification designates that the candidate has covered all the topics from basics to advance object-oriented programming concepts, GUI programming, etc. Using this certification, one can apply for a senior software development role, Python developer’s role, team lead, agile project management lead, and other senior job roles. Many professionals switch their careers to Big Data, Data Analytics, Machine learning, and deep learning after completing this certification. The approximate salary of a Python programmer with this certification will be $ 17,350 to $ 39,945 per annum. Top companies and industries hiring CEPPs are Amazon, Tesla, HSBC, Google, HCL, Oracle, Capgemini, Qualcomm, 6sense, Vitrana, and other top service-based companies. Where to take Training for Certification: Python Institute has all the study resources you need to prepare for PCAP-31-xx, PCPP-32-1-xx, and PCPP-32-2-xx examination. Once a candidate has passed all the certifications, he/she becomes recognized as an Open EDG Python Institute Certified Expert in Python Programming (CEPP). Who should take the Training (roles) for Certification: Any professional, Python expert, or senior Python developer, who wants to settle as a team lead or pursue an experienced-level job profile can opt for these certifications to reach at this level.  Course fees for Certification: $ 295 + $ 295 + $ 195 Application fee for certification: $ 295 + $ 295 + $ 195 Exam fee for certification: $ 295 + $ 295 + $ 195  Retake fee for certification: There is no retake fee Conclusion We trust this article gave you a better insight into different Python certifications! Whether you are starting out as a coder, or are an experienced Python programmer looking at making a splash in the industry, having a Python certification and proper knowledge of Python will elevate your programming career. Python is one of the top programming languages that can help you land different jobs in web development, app development, data science, cybersecurity, networking, web scraping, robotics, IoT, etc. If you aren't sure which online resource will be more informative for your Python certification, KnowledgeHut (https://www.knowledgehut.com/) has all the study materials and expert trainers who will help you reach the pinnacle of Python expertise. Receiving a Python certification, apart from academics and degrees, will make you stand out from the rest. So, start preparing for one today! 
9574
Best Python Certifications of 2021

Programming is always at the core of computer scie... Read More