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What is Apache Spark and what is it used for?

Posted on February 12, 2023March 12, 2023 By admin

Estimated reading time: 2 minutes

You have been probably looking at large sets of data for a while, and projects to extract insights from them.

If you are given a set of data that is so large you may need something more!

This is where Apache Spark comes in!

So what does Apache Spark do?

It performs the following functions:

  1. Batch streaming of data – In large-volume organizations it allows for the data to be processed in an efficient way.
  2. Separately if you are looking to stream data live through say XML or JSON it will facilitate this as well.
  3. It allows you to write your queries in multiple languages such as Python, SQL, Scala, Java, or R.
  4. This is excellent as not everyone is proficient in all languages and helps to provide connectivity.
  5. For data analytics, if your preferred language is SQL it caters to this as well.
  6. If you work data science and need the ability to process large datasets, you are in luck.
  7. If you are working on machine learning projects it will help you build and test your model to your requirements.

What are the benefits of using Apache Spark?

  1. It will help you to reduce build times, increasing productivity.
  2. You can run individual tests or test to look at specific outcomes.
  3. It can be run on clusters over a few nodes or thousands of nodes.
  4. It is supported by a number of different packages, the links below will give you more information.

Here are numerous packages you can use such as AppVeyor , Scaleway , GitHub which will support you in your endeavors.

If you would like to download Apache Spark go to this link here: Download Apache Spark

There are thousands of companies using this at the moment, and it shows its popularity.

This list of companies using Apache Spark will give you a flavor.

What are the key questions to help you decide whether to implement Apache Spark in your organization or not?

  1. Decide on your strategy, what you want to get out of it, and where you are at in the collection and storage of data.
  2. Map how many people are working on data in your organization – Apache Spark helps to give a unified development platform to work on.
  3. What is the urgency – do you need to roll out a system quickly and with ease? Because it supports many different programming languages, the different skills will be catered for.
  4. Do you have a requirement for batch and or real-time processing? If the answer is yes then it will help you deliver those requirements.
  5. What is your computing capacity? If low computing capacity then you should be looking at alternatives.
Apache Spark, Python, SQL Tags:Apache Spark, clusters, Data Science, machine learning, Python, sql

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