Sold by: kCloudHubs LLC
Deployed on AWS
AWS Free Tier
This product has charges associated with it for seller support. Apache Spark is an open-source, distributed computing system designed for fast, large-scale data processing, supporting SQL, machine learning, streaming, and graph analytics.
Overview
Apache Spark on Ubuntu 26.04 with Free Maintenance Support by kCloudHubs
Apache Spark is an open-source unified analytics engine designed for large-scale data processing, analytics, machine learning, and real-time data workloads. It provides distributed computing capabilities that allow organizations and developers to process large datasets efficiently across clusters or individual systems.
Architecture & Platform Design
- Ready-to-use Amazon Web Services (AWS) Marketplace Amazon Machine Image (AMI)
- Optimized for Ubuntu 26.04 LTS
- Built on the Java Virtual Machine (JVM) with support for Scala, Python, Java, and R
- Provides distributed processing and cluster computing capabilities
- Includes core components for:
- Distributed data processing
- SQL analytics
- Machine learning
- Streaming data processing
Core Capabilities :
Distributed Data Processing
- Process large datasets across distributed computing environments
- Support batch processing and large-scale data transformation
- Use Spark DataFrames, Datasets, and Resilient Distributed Datasets (RDDs)
- Perform data processing workloads using Python, Java, Scala, and R
Analytics & Machine Learning
- Run SQL queries over structured and semi-structured data
- Build and execute machine learning workflows using MLlib
- Process real-time and streaming data using Spark Structured Streaming
- Integrate with distributed storage systems and external data platforms
Customization & Configuration :
Flexible Processing Models
- Suitable for development, testing, analytics, and production data workloads
- Can operate in standalone mode or integrate with cluster managers such as Kubernetes and Hadoop YARN
- Configurable executors, memory, CPU resources, parallelism, and application settings
- Supports customization according to workload and data processing requirements
Cloud & Scalability
- Designed for deployment on AWS EC2
- Can scale distributed workloads across multiple EC2 instances
- Compatible with AWS storage, networking, databases, and data services
- Supports cluster-based architectures for large-scale data processing
- Resources can be adjusted according to dataset size and workload demand
- Suitable for environments-
- development
- staging
- production
kCloudHubs Value Addition
- Pre-configured and deployment-validated AWS Marketplace AMI
- Faster deployment compared to manual Apache Spark installation
- Production-ready default configuration
- Free maintenance support from kCloudHubs
Target Use Cases
- Big data processing and analytics
- ETL and data transformation pipelines
- Real-time stream processing
- Machine learning and data science workloads
- Large-scale SQL analytics
- Distributed data engineering and processing
Licensing & Support
Apache Spark is open-source software released under the Apache License 2.0. This AWS Marketplace AMI is independently packaged, maintained, and supported by kCloudHubs. Free maintenance support is included with the offering, with additional support and maintenance services available when required.
Highlights
- Handles batch, streaming, machine learning, and graph processing in one platform.
- APIs available in Python, Scala, Java, R, and SQL.
- Executes tasks significantly faster than disk-based engines like Hadoop MapReduce.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
m4.large Recommended | $0.03 |
t2.micro | $0.01 |
t3.micro | $0.03 |
t2.large | $0.03 |
t3.large | $0.03 |
r3.large | $0.03 |
r4.large | $0.03 |
t3.nano | $0.03 |
t3.medium | $0.03 |
t2.2xlarge | $0.03 |
Vendor refund policy
No Refund
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Packaged with latest updates as of August/2026.
Additional details
Usage instructions
Connect your instance via SSH, the username is ubuntu. More info on SSH: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html - Use the following command to check Apache Spark version : #sudo su #sudo apt update #/opt/spark/bin/spark-submit --version #sudo -u spark /opt/spark/sbin/start-worker.sh spark://server-ip
Support
Vendor support
Feel free to reach out anytime. Our support team is available 24x7 for assistance. Email: meha@kcloudhubs.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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