Overview
This is a repackaged open source software product wherein additional charges apply for support and maintenance by AskforCloud LLC.
Apache Spark™ is an open source multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, pandas API on Spark for pandas workloads, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for incremental computation and stream processing.
Disclaimer: This Virtual machine offer contains free and open source software. All the software, trademarks used in the Virtual machine offer are the exclusive property of their respective owners. Askforcloud LLC does not offer commercial license of the product mentioned above. Apache Spark, Spark, Apache, the Apache feather logo, and the Apache Spark project logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries. Apache Spark Licensed under the Apache License, Version 2.0.
Highlights
- Execute fast, distributed ANSI SQL queries for dashboarding and ad-hoc reporting. Runs faster than most data warehouses.
- Unify the processing of your data in batches and real-time streaming, using your preferred language: Python, SQL, Scala, Java or R.
- Train machine learning algorithms on a laptop and use the same code to scale to fault-tolerant clusters of thousands of machines.
Details
Typical total price
$0.193/hour
Features and programs
Financing for AWS Marketplace purchases
Pricing
- ...
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t2.nano | $0.006 | $0.006 | $0.012 |
t2.micro AWS Free Tier | $0.006 | $0.012 | $0.018 |
t2.small | $0.01 | $0.023 | $0.033 |
t2.medium | $0.06 | $0.046 | $0.106 |
t2.large Recommended | $0.10 | $0.093 | $0.193 |
t2.xlarge | $0.10 | $0.186 | $0.286 |
t2.2xlarge | $0.10 | $0.371 | $0.471 |
t3.nano | $0.006 | $0.005 | $0.011 |
t3.micro AWS Free Tier | $0.006 | $0.01 | $0.016 |
t3.small | $0.01 | $0.021 | $0.031 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp2) volumes | $0.10/per GB/month of provisioned storage |
Vendor refund policy
For this offer, Askforcloud LLC does not offer refund, you can cancel at anytime.
Legal
Vendor terms and conditions
Content disclaimer
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
Latest version - https://spark.apache.org/docs/latest/
Additional details
Usage instructions
Connect to EC2 Linux instance - https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstances.html ( Port - 22 and Username - admin)
Spark - https://spark.apache.org/docs/latest/ Use the following steps:
- Ports - 8080,7077
- Start a standalone master server using command - start-master.sh
- Open your web browser and access the Spark web interface using the URL http://your-server-ip:8080
- Start Spark Worker Process - start-slave.sh spark://your-server-ip:7077
- Use the spark-shell command to access Spark Shell - /opt/spark/bin/spark-shell
- Connect the Spark with command for Python, use pyspark - /opt/spark/bin/pyspark
- Stop Master and Slave server with the following command:
- stop-slave.sh
- stop-master.sh
Resources
Vendor resources
Support
Vendor support
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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