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The total ranking of a product, represented by the bar length, is based on a weighted aggregate score. The score is calculated as follows: The product with the highest count in each area gets the highest available score. (20 points for Reviews; 16 points for Views, Comparisons, and Followers.) Every other product gets assigned points based on its total in proportion to the #1 product in that area. For example, if a product has 80% of the number of reviews compared to the product with the most reviews then the product's score for reviews would be 20% (weighting factor) * 80% = 16. For Average Rating, the maximum score is 32 points awarded linearly based on our rating scale of 1-10. If a product has fewer than ten reviews, the point contribution for Average Rating is reduced (one-third reduction in points for products with 5-9 reviews; two-thirds reduction for products with fewer than five reviews). Reviews that are more than 24 months old, as well as those written by resellers, are completely excluded from the ranking algorithm.
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Java Frameworks Reviews

Read reviews of Java Frameworks that are trending in the IT Central Station community:
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Pivotal
Real User
Principal Architect at a tech services company with 11-50 employees
Nov 15 2017

What do you think of Spring MVC?

Primary Use Case Mostly REST service and web application development on RDBMS products • Valuable Features I have found the new version with annotations and differentiation between SpringMVC and REST Controllers to be most valuable. • Improvements to My Organization Spring MVC has reduced the time spent on building MVC code in Java projects. • Room for Improvement The link with UI components could be improved. For example, there could be auto-transformation from Java objects to simple UI components (such as jQuery tables, drop down lists, autocomplete lists), so that the transformation from Java on the server side to UI components is built-in. • Use of Solution I have used this solution since 2008. • Stability Issues I have not encountered any issues with...
Consultant
Big Data Consultant at a tech services company with 501-1,000 employees
Aug 25 2017

What do you think of Apache Spark?

Valuable Features The good performance. The nice graphical management console. The long list of ML algorithms. • Improvements to My Organization We are able to solve problems, e.g., reporting on big data, that we were not able to tackle in the past. • Room for Improvement Apache Spark provides very good performance The tuning phase is still tricky. • Use of Solution I've used it for 2 years. • Deployment Issues We didn't have an issue with the deployment. • Stability Issues In the past we deployed Spark 1.3 to use Spark SQL but unfortunately one of our queries failed because of a bug fixed in following releases. Then we moved to Spark 1.6 but still some queries were failing when run against huge datasets. Now we are using version 2.1: it is more stable, it...

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Real User
Sr. Software Engineer at a tech vendor with 1-10 employees
Oct 01 2017

What is most valuable?

The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics. The community is growing and hence executing ML in a distributed fashion is quite good.

How has it helped my organization?

Previously we were using Hadoop MapReduce to reduce the Google Ngrams (3TB), which took us approximately five days on our cluster. After using Spark, we were able to accomplish this task within hours.

What needs improvement?

This product is already improving as the community is developing it rapidly. More ML based algorithms should be added to it, to make it algorithmic-rich for developers.
Real User
Architect at a healthcare company with 51-200 employees
Sep 27 2017

What do you think of Apache Spark?

Valuable Features ETL and streaming capabilities. • Improvements to My Organization Made Big Data processing more convenient and a uniform framework adds to efficiency of usage since the same framework can be used for batch and stream processing. • Room for Improvement Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet). • Use of Solution I have used Spark since its inception in March 2015, from Spark 1.1 onwards. Currently, I use 2.2 extensively. • Stability Issues Yes, occasionally with different APIs. • Scalability Issues No. • Customer Service and Technical Support Since we were using the Open Source version of Apache Spark, without the Databricks support, we never used technical support form...
Consultant
Manager | Data Science Enthusiast | Management Consultant at a consultancy with 5,001-10,000 employees
Dec 10 2017

What do you think of Apache Spark?

Improvements to My Organization Organisations can now harness richer data sets and benefit from use cases, which add value to their business functions. • Valuable Features Distributed in memory processing. Some of the algorithms are resource heavy and executing this requires a lot of RAM and CPU. With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware. • Room for Improvement Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing. • Use of Solution Three to five years. • Stability Issues At times when users do not know how to use Spark and request a lot of resources, then the underlying JVMs can crash, which is a big sense of worry.  • Scalability Issues No...
Pivotal
Real User
Department Manager at a tech services company with 51-200 employees
Jan 18 2018

What do you think of Spring MVC?

Primary Use Case Spring is used as a J2EE framework for our Java applications server side. We are using MVC, Hibernate, and Security. • Improvements to My Organization Spring has a speedy development process with a lightweight framework. We have found Spring is easy to use and learn.  • Valuable Features Dependency Injection is one of the major features which makes our life easier using Spring. It is well documented and has active communities, which provide us enormous help. • Room for Improvement Spring IDE needs some work and improvement. We have faced many issues when adding third-party Eclipse plugins. • Use of Solution One to three years.
Consultant
Big Data and Cloud Solution Consultant at a financial services firm with 10,001+ employees
Oct 02 2017

What do you think of Apache Spark?

Valuable Features DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort. • Improvements to My Organization We developed a tool for data ingestion from HDFS->Raw->L1 layer with data quality checks, putting data to elastic search, performing CDC. • Room for Improvement Dynamic DataFrame options are not yet available. • Use of Solution One and a half years. • Stability Issues No. • Scalability Issues No. • Other Advice Spark gives the flexibility for developing custom applications.

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