Apache Spark

Apache Spark

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation
+
+

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About

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

About

​Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. ​

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Organizations that want a unified analytics engine for large-scale data processing

Audience

Data scientists and engineers wanting a machine learning solution for efficient data processing and analysis within the Apache Spark framework

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Supported

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org

Company Information

Apache Software Foundation
Founded: 1995
United States
spark.apache.org/mllib/

Alternatives

Alternatives

Apache Spark

Apache Spark

Apache Software Foundation
dbt

dbt

dbt Labs
Apache Mahout

Apache Mahout

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation
Amazon EMR

Amazon EMR

Amazon

Categories

Big Data Supported
Data Analysis Supported
Data Modeling Supported
Query Engines Supported

Categories

Machine Learning Supported

Streaming Analytics Features

Data Enrichment Supported
Data Wrangling / Data Prep Supported
Multiple Data Source Support Supported
Process Automation Supported
Real-time Analysis / Reporting Not Supported
Visualization Dashboards Not Supported

Integrations

Amazon EC2 Supported
Apache Cassandra Supported
Apache HBase Supported
Apache Hive Supported
Apache Mesos Supported
Hadoop Supported
Kubernetes Supported
Deep.BI Supported
Genesis Computing Supported
Google Cloud Lakehouse Supported
IBM watsonx.data integration Supported
JupyterLab Supported
Metabase Supported
NVMesh Supported
Onehouse Supported
PubSub+ Platform Supported
RunCode Supported
Saagie Supported
Snowflake CoCo Supported
TeamStation Supported

Integrations

Amazon EC2 Supported
Apache Cassandra Supported
Apache HBase Supported
Apache Hive Supported
Apache Mesos Supported
Hadoop Supported
Kubernetes Supported
Deep.BI Not Supported
Genesis Computing Not Supported
Google Cloud Lakehouse Not Supported
IBM watsonx.data integration Not Supported
JupyterLab Not Supported
Metabase Not Supported
NVMesh Not Supported
Onehouse Not Supported
PubSub+ Platform Not Supported
RunCode Not Supported
Saagie Not Supported
Snowflake CoCo Not Supported
TeamStation Not Supported
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