2018-06-27T19:19:00Z

What do you like most about Apache Spark?

Miriam Tover - PeerSpot reviewer
  • 1
  • 6
PeerSpot user
29

29 Answers

Suriya Senthilkumar - PeerSpot reviewer
Real User
2024-02-26T16:01:50Z
Feb 26, 2024

The product’s most valuable features are lazy evaluation and workload distribution.

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Hamid M. Hamid - PeerSpot reviewer
Real User
Top 5Leaderboard
2024-02-05T09:17:45Z
Feb 5, 2024

The deployment of the product is easy.

SS
Real User
Top 5Leaderboard
2023-12-06T10:45:56Z
Dec 6, 2023

We use it for ETL purposes as well as for implementing the full transformation pipelines.

NB
MSP
Top 5
2023-11-10T13:04:33Z
Nov 10, 2023

The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations.

Jagannadha Rao - PeerSpot reviewer
Real User
Top 10
2023-10-20T07:41:27Z
Oct 20, 2023

The most valuable feature of Apache Spark is its flexibility.

FK
Real User
Top 5Leaderboard
2023-07-26T09:09:50Z
Jul 26, 2023

The data processing framework is good.

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JK
Real User
Top 20
2023-07-06T10:55:23Z
Jul 6, 2023

The distribution of tasks, like the seamless map-reduce functionality, is quite impressive.

Armando Becerril - PeerSpot reviewer
Real User
Top 5
2023-02-13T20:14:00Z
Feb 13, 2023

Provides a lot of good documentation compared to other solutions.

Ilya Afanasyev - PeerSpot reviewer
Real User
Top 5Leaderboard
2022-08-03T04:09:48Z
Aug 3, 2022

There's a lot of functionality.

SK
Real User
Top 20
2022-07-04T15:18:53Z
Jul 4, 2022

The most valuable feature of Apache Spark is its ease of use.

AmitMataghare - PeerSpot reviewer
Real User
Top 5
2022-04-27T08:19:23Z
Apr 27, 2022

One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast.

Salvatore Campana - PeerSpot reviewer
Real User
Top 5
2022-04-27T08:19:19Z
Apr 27, 2022

Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term.

Onur Tokat - PeerSpot reviewer
Consultant
2022-02-15T16:44:00Z
Feb 15, 2022

Spark can handle small to huge data and is suitable for any size of company.

Suresh_Srinivasan - PeerSpot reviewer
Real User
2021-12-28T09:52:00Z
Dec 28, 2021

Apache Spark can do large volume interactive data analysis.

Oscar Estorach - PeerSpot reviewer
Real User
Top 10
2021-08-18T14:51:07Z
Aug 18, 2021

The solution has been very stable.

GA
Real User
2021-03-27T15:39:24Z
Mar 27, 2021

I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library.

NK
Real User
Top 20
2021-02-01T12:04:16Z
Feb 1, 2021

Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica.

Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark.

KK
Real User
2020-10-28T02:27:29Z
Oct 28, 2020

AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI.

RV
Real User
2020-07-23T07:58:35Z
Jul 23, 2020

The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly.

GK
Real User
2020-06-10T05:27:31Z
Jun 10, 2020

I love every core functionality of Apache Spark Initially they have only provided RDD basic interface to process the data across distributed cluster. Then it evolved to dataframe and dataset interface with optimised execution engine and more flexibility for developers to perform querying on the data.

KK
Real User
Top 20
2020-02-02T10:42:14Z
Feb 2, 2020

The processing time is very much improved over the data warehouse solution that we were using.

Suresh_Srinivasan - PeerSpot reviewer
Real User
2020-01-29T11:22:00Z
Jan 29, 2020

The features we find most valuable are the machine learning, data learning, and Spark Analytics.

it_user1223676 - PeerSpot reviewer
Consultant
2020-01-29T11:22:00Z
Jan 29, 2020

The main feature that we find valuable is that it is very fast.

SA
Consultant
2019-12-23T07:05:00Z
Dec 23, 2019

I feel the streaming is its best feature.

MG
Real User
2019-12-09T10:58:00Z
Dec 9, 2019

The solution is very stable.

AD
Consultant
2019-10-13T05:48:00Z
Oct 13, 2019

The most valuable feature of this solution is its capacity for processing large amounts of data.

LC
Real User
2019-07-14T10:21:00Z
Jul 14, 2019

The scalability has been the most valuable aspect of the solution.

it_user946074 - PeerSpot reviewer
Real User
2019-07-10T12:01:00Z
Jul 10, 2019

I found the solution stable. We haven't had any problems with it.

reviewer894894 - PeerSpot reviewer
User
2018-06-27T19:19:00Z
Jun 27, 2018

Features include machine learning, real time streaming, and data processing.

Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function...
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