Apache Spark is Best, But why Not Perfect here the answer

Why Apache Spark is not perfect: here’s the answer

2

Âť

Âť

Nowadays, the big data has been turned out to be one of the most significant assets of any kind organization, be it a small-scale organization or be it a large-scale enterprise.

These organizations anticipate that big data analytics provides valuable insights which assist in making faster and better business-related decisions, reducing operating costs, identifying customer requirements, and delivering delightful customer experience.

3

APACHE SPARK’S JOURNEY INTO BIG DATA »

Amid significant technological transformations, Apache Spark recently completed 10 years with tremendous success and has turned out to be one of the most essential components of several renowned projects across the globe.

»

As per the latest report, the total value of Databricks’s analytics platform that originally developed Apache Spark is approx. $2.75 billion.

»

Though the fact that the Apache Spark is considered to be the future of large data analytics, there are many drawbacks, which restrict access to specific situations. And they are:

4

1. Performance indicators with complex nature 2. As noted by Bala Venkatrao 3. Good at everything - Best at nothing 4. According to Ashish Thusoo, CEO 5. The occurrence of random bugs

5

PERFORMANCE INDICATORS WITH COMPLEX NATURE: » Although originally developed as a substitute for MapReduce, the most advanced Apache Spark offered excellent performance over the years through processing a massive amount of data with the help of Apache Hadoop.

6

AS NOTED BY BALA VENKATRAO Âť Vice President (Product) of a California-based firm - Unravel Data, the writing of the right codes assumes an important role in Apache Spark, and for that, one must require in-depth knowledge of its working methodology. Moreover, the enriched library of Spark facilitates the hassle-free coding of work tasks.

7

•

Today, Apache Spark Service has gained wide recognition in the field of big data as it offers some of the advanced features such as integration with Hadoop, graph processing, and faster processing.

•

Even though most of the industry experts acknowledged Apache Spark relevance across the sectors, however, some are still in, the dilemma regarding its invisible future.

•

Under these circumstances, the potential users of Apache Spark must be attentive and should investigate its pros and cons while deploying it into prominent projects.

8

GOOD AT EVERYTHING - BEST AT NOTHING » Owing to its variety of advanced applications and ease of use, Apache Spark regarded as “Swiss Army Knife of Big Data Analytics”. It offers high efficient applications with honor to analytics, which includes - ETL, real-time processing, SQL machine learning, graph engine libraries, APIs for multiple programming languages, and a huge set of well-defined data connectors.

9

ACCORDING TO ASHISH THUSOO, CEO Âť Qubole, Apache Spark well-suits the requirements of in-memory computing workloads and witness high demand for machine learning, streaming ETL, and batch ETL workloads among its prominent users. Further, he claims that the upsurge in the user base indicates that Apache Spark will certainly survive for a long time in the market.

10

THE OCCURRENCE OF RANDOM BUGS: » As soon as the initial concerns associated with Apache Spark’s scalability got resolved, the application is believed to be appropriate for deployment and was extensively adopted by various industries across the world. » For instance, the tech-giant IBM is considered to be the earliest believer of Apache Spark that has incorporated the application into plenty of its products. However, it does not mean that Apache Spark is a perfect application.

11

IN RECENT YEARS

Apache Spark witnessed huge popularity and considered as one of the best big data solutions for enterprises over the next few years.

However, similar to all other technological applications built by humans, Apache Spark is far from being a perfect model.

The breakthrough innovations in the near future might assist to overcome the Apache Spark’s drawbacks and ensure successful implementation at the large-scale.

12

AEGIS SOFTWARE

CANADA Offshore software development company 2 Robert Speck Parkway, Suite 750 Mississauga, Ontario, Canada - L4Z1H8 info@aegissoftwares.com https://www.aegissoftwares.com

13

THANK YOU