Apache Spark VS Smile

Compare Apache Spark vs Smile and see what are their differences.

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Apache Spark Smile
101 9
38,320 5,921
1.1% -
10.0 9.8
3 days ago 3 days ago
Scala Java
Apache License 2.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Apache Spark

Posts with mentions or reviews of Apache Spark. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-11.

Smile

Posts with mentions or reviews of Smile. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-07.
  • The Current State of Clojure's Machine Learning Ecosystem
    4 projects | news.ycombinator.com | 7 Apr 2024
    > I don't think it's right to recommend that new users move away from the package because of licensing issues

    I was going to chime in to agree but then I saw how this was done - a completely innocuous looking commit:

    https://github.com/haifengl/smile/commit/6f22097b233a3436519...

    And literally no mention in the release notes:

    https://github.com/haifengl/smile/releases/tag/v3.0.0

    I think if you are going to change license especially in a way that makes it less permissive you need to be super open and clear about both the fact you are doing it and your reasons for that. This is done so silently as to look like it is intentionally trying to mislead and trick people.

    So maybe I wouldn't say to move away because of the specific license, but it's legitimate to avoid something when it's so clearly driven by a single entity and that entity acts in a way that isn't trustworthy.

  • Need statistic test library for Spark Scala
    1 project | /r/scala | 5 May 2023
    Check out Smile too.
  • Just want to vent a bit
    3 projects | /r/ProgrammingLanguages | 3 Dec 2022
    Although it may be a bit more work, you can do both machine learning and AI in Java. If you are doing deep learning, you can use DeepJavaLibrary (I do work on this one at Amazon). If you are looking for other ML algorithms, I have seen Smile, Tribuo, or some around Spark.
  • Anybody here using Java for machine learning?
    11 projects | /r/java | 13 Sep 2022
    For deploying a trained model there are a bunch of options that use Java on top of some native runtime like TF-Java (which I co-lead), ONNX Runtime, pytorch has inference for TorchScript models. Training deep learning models is harder, though you can do it for some of them in DJL. Training more standard ML models is much simpler, either via Tribuo, or using things like LibSVM & XGBoost directly, or other libraries like SMILE or WEKA.
  • What libraries do you use for machine learning and data visualizing in scala?
    5 projects | /r/scala | 27 Nov 2021
    I use smile https://github.com/haifengl/smile with ammonite and it feels pretty easy/good to work with. Of course for pure looking at data, and exploration, you're not going to beat python.
  • Python VS Scala
    2 projects | /r/scala | 2 Jul 2021
    Actually, it does. Scala has Spark for data science and some ML libs like Smile.
  • [R] NLP Machine Learning with low RAM
    1 project | /r/MachineLearning | 2 Jun 2021
    I guess I must have a mistake somewhere. It's not much code. it's written in Kotlin with smile. My dataset is only about 32MB. I load the dataset into memory. I then use 80% of the data for training, and the other for later testing. I get just the columns I need and store them in the variable dataset.
  • Kotlin with Randon Forest Classifier
    1 project | /r/Kotlin | 19 Apr 2021
    I've heard good things about Smile, probably beats libs like Weka by far. I'm not sure if you can load a scikit-learn model though, so you might need to retrain the model in Kotlin.
  • Machine learning on JVM
    6 projects | /r/scala | 5 Apr 2021
    I was using Smile for some period - https://haifengl.github.io/ - it's quite small and lightweight Java lib with some very basic algorithms - I was using in particularly cauterization. Along with this it provides Scala API.

What are some alternatives?

When comparing Apache Spark and Smile you can also consider the following projects:

Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

Weka

Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Breeze - Breeze is a numerical processing library for Scala.

Scalding - A Scala API for Cascading

Apache Flink - Apache Flink

mrjob - Run MapReduce jobs on Hadoop or Amazon Web Services

ND4S - ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J.

luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

Apache Mahout - Mirror of Apache Mahout