akshay L

akshay L

1572939856

Hadoop vs Spark | Hadoop MapReduce vs Spark

In this video on Hadoop vs Spark you will understand about the top Big Data solutions used in the IT industry, and which one should you use for better performance. So in this Hadoop MapReduce vs Spark comparison some important parameters have been taken into consideration to tell you the difference between Hadoop and Spark also which one is preferred over the other in certain aspects in detail.

Why Hadoop is important

Big data hadoop is one of the best technological advances that is finding increased applications for big data and in a lot of industry domains. Data is being generated hugely in each and every industry domain and to process and distribute effectively hadoop is being deployed everywhere and in every industry.

#Hadoop vs Spark #Apache Spark vs Hadoop #Spark vs Hadoop #Difference Between Spark and Hadoop #Intellipaat

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Buddha Community

Hadoop vs Spark | Hadoop MapReduce vs Spark
akshay L

akshay L

1572939856

Hadoop vs Spark | Hadoop MapReduce vs Spark

In this video on Hadoop vs Spark you will understand about the top Big Data solutions used in the IT industry, and which one should you use for better performance. So in this Hadoop MapReduce vs Spark comparison some important parameters have been taken into consideration to tell you the difference between Hadoop and Spark also which one is preferred over the other in certain aspects in detail.

Why Hadoop is important

Big data hadoop is one of the best technological advances that is finding increased applications for big data and in a lot of industry domains. Data is being generated hugely in each and every industry domain and to process and distribute effectively hadoop is being deployed everywhere and in every industry.

#Hadoop vs Spark #Apache Spark vs Hadoop #Spark vs Hadoop #Difference Between Spark and Hadoop #Intellipaat

Top Spark Development Companies | Best Spark Developers - TopDevelopers.co

An extensively researched list of top Apache spark developers with ratings & reviews to help find the best spark development Companies around the world.

Our thorough research on the ace qualities of the best Big Data Spark consulting and development service providers bring this list of companies. To predict and analyze businesses and in the scenarios where prompt and fast data processing is required, Spark application will greatly be effective for various industry-specific management needs. The companies listed here have been skillfully boosting businesses through effective Spark consulting and customized Big Data solutions.

Check out this list of Best Spark Development Companies with Best Spark Developers.

#spark development service providers #top spark development companies #best big data spark development #spark consulting #spark developers #spark application

Edureka Fan

Edureka Fan

1621264208

Apache Hadoop & Spark Tutorial For Beginners | What is Hadoop & Spark

This Edureka video on “Apache Hadoop & Spark Tutorial For Beginners” will help you understand the basics of Hadoop and Spark with examples.

#hadoop #big-data #apache-hadoop #spark

Kasey  Turcotte

Kasey Turcotte

1623927960

Pandas DataFrame vs. Spark DataFrame: When Parallel Computing Matters

With Performance Comparison Analysis and Guided Example of Animated 3D Wireframe Plot

Python is famous for its vast selection of libraries and resources from the open-source community. As a Data Analyst/Engineer/Scientist, one might be familiar with popular packages such as NumpyPandasScikit-learnKeras, and TensorFlow. Together these modules help us extract value out of data and propels the field of analytics. As data continue to become larger and more complex, one other element to consider is a framework dedicated to processing Big Data, such as Apache Spark. In this article, I will demonstrate the capabilities of distributed/cluster computing and present a comparison between the Pandas DataFrame and Spark DataFrame. My hope is to provide more conviction on choosing the right implementation.

Pandas DataFrame

Pandas has become very popular for its ease of use. It utilizes DataFrames to present data in tabular format like a spreadsheet with rows and columns. Importantly, it has very intuitive methods to perform common analytical tasks and a relatively flat learning curve. It loads all of the data into memory on a single machine (one node) for rapid execution. While the Pandas DataFrame has proven to be tremendously powerful in manipulating data, it does have its limits. With data growing at an exponentially rate, complex data processing becomes expensive to handle and causes performance degradation. These operations require parallelization and distributed computing, which the Pandas DataFrame does not support.

Introducing Cluster/Distribution Computing and Spark DataFrame

Apache Spark is an open-source cluster computing framework. With cluster computing, data processing is distributed and performed in parallel by multiple nodes. This is recognized as the MapReduce framework because the division of labor can usually be characterized by sets of the mapshuffle, and reduce operations found in functional programming. Spark’s implementation of cluster computing is unique because processes 1) are executed in-memory and 2) build up a query plan which does not execute until necessary (known as lazy execution). Although Spark’s cluster computing framework has a broad range of utility, we only look at the Spark DataFrame for the purpose of this article. Similar to those found in Pandas, the Spark DataFrame has intuitive APIs, making it easy to implement.

#pandas dataframe vs. spark dataframe: when parallel computing matters #pandas #pandas dataframe #pandas dataframe vs. spark dataframe #spark #when parallel computing matters

Autumn  Blick

Autumn Blick

1598839687

How native is React Native? | React Native vs Native App Development

If you are undertaking a mobile app development for your start-up or enterprise, you are likely wondering whether to use React Native. As a popular development framework, React Native helps you to develop near-native mobile apps. However, you are probably also wondering how close you can get to a native app by using React Native. How native is React Native?

In the article, we discuss the similarities between native mobile development and development using React Native. We also touch upon where they differ and how to bridge the gaps. Read on.

A brief introduction to React Native

Let’s briefly set the context first. We will briefly touch upon what React Native is and how it differs from earlier hybrid frameworks.

React Native is a popular JavaScript framework that Facebook has created. You can use this open-source framework to code natively rendering Android and iOS mobile apps. You can use it to develop web apps too.

Facebook has developed React Native based on React, its JavaScript library. The first release of React Native came in March 2015. At the time of writing this article, the latest stable release of React Native is 0.62.0, and it was released in March 2020.

Although relatively new, React Native has acquired a high degree of popularity. The “Stack Overflow Developer Survey 2019” report identifies it as the 8th most loved framework. Facebook, Walmart, and Bloomberg are some of the top companies that use React Native.

The popularity of React Native comes from its advantages. Some of its advantages are as follows:

  • Performance: It delivers optimal performance.
  • Cross-platform development: You can develop both Android and iOS apps with it. The reuse of code expedites development and reduces costs.
  • UI design: React Native enables you to design simple and responsive UI for your mobile app.
  • 3rd party plugins: This framework supports 3rd party plugins.
  • Developer community: A vibrant community of developers support React Native.

Why React Native is fundamentally different from earlier hybrid frameworks

Are you wondering whether React Native is just another of those hybrid frameworks like Ionic or Cordova? It’s not! React Native is fundamentally different from these earlier hybrid frameworks.

React Native is very close to native. Consider the following aspects as described on the React Native website:

  • Access to many native platforms features: The primitives of React Native render to native platform UI. This means that your React Native app will use many native platform APIs as native apps would do.
  • Near-native user experience: React Native provides several native components, and these are platform agnostic.
  • The ease of accessing native APIs: React Native uses a declarative UI paradigm. This enables React Native to interact easily with native platform APIs since React Native wraps existing native code.

Due to these factors, React Native offers many more advantages compared to those earlier hybrid frameworks. We now review them.

#android app #frontend #ios app #mobile app development #benefits of react native #is react native good for mobile app development #native vs #pros and cons of react native #react mobile development #react native development #react native experience #react native framework #react native ios vs android #react native pros and cons #react native vs android #react native vs native #react native vs native performance #react vs native #why react native #why use react native