Apache Spark Pros and Cons

Apache Spark Pros

reviewer879201
Technical Consultant at a tech services company with 1-10 employees
I feel the streaming is its best feature.
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Kürşat Kurt
Software Architect at Akbank
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.
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Rajendran Veerappan
Director at Nihil Solutions
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.
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Learn what your peers think about Apache Spark. Get advice and tips from experienced pros sharing their opinions. Updated: January 2021.
455,962 professionals have used our research since 2012.
Karthikeyan R
Principal Architect at a financial services firm with 1,001-5,000 employees
I found the solution stable. We haven't had any problems with it.
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reviewer1046250
Senior Consultant & Training at a tech services company with 51-200 employees
The most valuable feature of this solution is its capacity for processing large amounts of data.
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reviewer1221765
Co-Founder at a tech vendor with 11-50 employees
The features we find most valuable are the machine learning, data learning, and Spark Analytics.
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reviewer1223676
Lead Consultant at a tech services company with 51-200 employees
The main feature that we find valuable is that it is very fast.
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Snrsecengin567
Snr Security Engineer at a tech vendor with 201-500 employees
The scalability has been the most valuable aspect of the solution.
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Mohamed Ghorbel
Director of BigData Offer at IVIDATA
The solution is very stable.
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KamleshKhollam
Consultant at Exusia
The processing time is very much improved over the data warehouse solution that we were using.
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Apache Spark Cons

reviewer879201
Technical Consultant at a tech services company with 1-10 employees
When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources.
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Kürşat Kurt
Software Architect at Akbank
Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing.
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Rajendran Veerappan
Director at Nihil Solutions
The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate.
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Learn what your peers think about Apache Spark. Get advice and tips from experienced pros sharing their opinions. Updated: January 2021.
455,962 professionals have used our research since 2012.
Karthikeyan R
Principal Architect at a financial services firm with 1,001-5,000 employees
It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster.
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reviewer1046250
Senior Consultant & Training at a tech services company with 51-200 employees
When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data.
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reviewer1221765
Co-Founder at a tech vendor with 11-50 employees
We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data.
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reviewer1223676
Lead Consultant at a tech services company with 51-200 employees
We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time.
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Snrsecengin567
Snr Security Engineer at a tech vendor with 201-500 employees
The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive.
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Mohamed Ghorbel
Director of BigData Offer at IVIDATA
The solution needs to optimize shuffling between workers.
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KamleshKhollam
Consultant at Exusia
I would like to see integration with data science platforms to optimize the processing capability for these tasks.
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Learn what your peers think about Apache Spark. Get advice and tips from experienced pros sharing their opinions. Updated: January 2021.
455,962 professionals have used our research since 2012.