Apache Spark
kCloudHub LLC · Software Development
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 8 captures on record
What the publisher says
As described on Microsoft Marketplace.
Apache Spark 4.0.1 is a high-performance, open-source distributed data processing and analytics framework designed for large-scale data engineering, machine learning, streaming, and real-time analytics workloads.
The solution supports common big data and analytics workflows including distributed data processing, SQL analytics, machine learning, ETL pipelines, graph processing, and streaming analytics. Apache Spark integrates with Hadoop, Hive, Kafka, Parquet, and cloud platforms, making it ideal for developers, data engineers, data scientists, and enterprise analytics teams working with large-scale data processing environments on Azure.
Show the rest of the publisher’s description (23 more lines)
Version: Apache Spark 4.0.1
Features of Apache Spark:
- Fast distributed in-memory data processing engine.
- Support for batch processing and real-time stream analytics.
- Built-in Spark SQL for structured data processing.
- Machine learning support through MLlib.
- Graph processing support using GraphX.
- Integration with Hadoop, Hive, Kafka, Parquet, and cloud storage.
- Supports Python, Scala, Java, and R programming languages.
- Web-based monitoring dashboard for Spark applications and clusters.
Usage instructions for Apache Spark
$ sudo su
$ cd /opt
$ spark-submit --version
Testing Apache Spark installation
Access information:
Apache Spark provides a web-based monitoring dashboard.
Default Spark Web UI:
http://SERVER-IP:4040
Required Azure inbound ports:
SSH Port: 22
Spark Web UI Port: 4040
Disclaimer: Apache Spark is provided “as is” under applicable open-source licenses. Users are responsible for proper installation, cluster configuration, workload optimization, data validation, and secure management of distributed analytics environments. This solution is best suited for big data processing, ETL workflows, machine learning, streaming analytics, and enterprise-scale distributed computing workloads in development and production environments.
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
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Vendor
External enrichment · as of 2026-08-29
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