Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google Cloud Platform Reviews & Ratings
    61,066 Ratings
    Company Website
  • TIMi Reviews & Ratings
    68 Ratings
    Company Website
  • Runpod Reviews & Ratings
    230 Ratings
    Company Website
  • Anaconda Reviews & Ratings
    625 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Google Cloud Speech-to-Text Reviews & Ratings
    443 Ratings
    Company Website
  • Gemini Enterprise Agent Platform Reviews & Ratings
    1,161 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    2,027 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    41 Ratings
    Company Website

What is MLlib?

MLlib, the machine learning component of Apache Spark, is crafted for exceptional scalability and seamlessly integrates with Spark's diverse APIs, supporting programming languages such as Java, Scala, Python, and R. It boasts a comprehensive array of algorithms and utilities that cover various tasks including classification, regression, clustering, collaborative filtering, and the construction of machine learning pipelines. By leveraging Spark's iterative computation capabilities, MLlib can deliver performance enhancements that surpass traditional MapReduce techniques by up to 100 times. Additionally, it is designed to operate across multiple environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud settings, while also providing access to various data sources like HDFS, HBase, and local files. This adaptability not only boosts its practical application but also positions MLlib as a formidable tool for conducting scalable and efficient machine learning tasks within the Apache Spark ecosystem. The combination of its speed, versatility, and extensive feature set makes MLlib an indispensable asset for data scientists and engineers striving for excellence in their projects. With its robust capabilities, MLlib continues to evolve, reinforcing its significance in the rapidly advancing field of machine learning.

What is Apache Spark?

Apache Spark™ is a powerful analytics platform crafted for large-scale data processing endeavors. It excels in both batch and streaming tasks by employing an advanced Directed Acyclic Graph (DAG) scheduler, a highly effective query optimizer, and a streamlined physical execution engine. With more than 80 high-level operators at its disposal, Spark greatly facilitates the creation of parallel applications. Users can engage with the framework through a variety of shells, including Scala, Python, R, and SQL. Spark also boasts a rich ecosystem of libraries—such as SQL and DataFrames, MLlib for machine learning, GraphX for graph analysis, and Spark Streaming for processing real-time data—which can be effortlessly woven together in a single application. This platform's versatility allows it to operate across different environments, including Hadoop, Apache Mesos, Kubernetes, standalone systems, or cloud platforms. Additionally, it can interface with numerous data sources, granting access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and many other systems, thereby offering the flexibility to accommodate a wide range of data processing requirements. Such a comprehensive array of functionalities makes Spark a vital resource for both data engineers and analysts, who rely on it for efficient data management and analysis. The combination of its capabilities ensures that users can tackle complex data challenges with greater ease and speed.

Media

Media

Integrations Supported

Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Hadoop
Kubernetes

Integrations Supported

Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Hadoop
Kubernetes
Acxiom InfoBase
Amazon SageMaker Data Wrangler
Apache Phoenix
Botify.cloud
Ficstar
IBM Data Refinery
NVIDIA RAPIDS
Spark Streaming
Speedb
VeloDB
Yandex Data Proc
eQube®-DaaS

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1995

Company Location

United States

Company Website

spark.apache.org/mllib/

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

spark.apache.org

Categories and Features

Machine Learning

Not specified

Categories and Features

Big Data

Not specified

Data Analysis

Not specified

Data Modeling

Not specified

Query Engines

Not specified

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation

Popular Alternatives

Apache Spark Reviews & Ratings

Apache Spark

Apache Software Foundation

Popular Alternatives

Apache Mahout Reviews & Ratings

Apache Mahout

Apache Software Foundation
dbt Reviews & Ratings

dbt

dbt Labs
Amazon EMR Reviews & Ratings

Amazon EMR

Amazon
MLlib Reviews & Ratings

MLlib

Apache Software Foundation