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README
MIT

Data Accelerator for Apache Spark

Data Accelerator for Apache Spark democratizes streaming big data using Spark by offering several key features such as a no-code experience to set up a data pipeline as well as fast dev-test loop for creating complex logic. Our team has been using the project for two years within Microsoft for processing streamed data across many internal deployments handling data volumes at Microsoft scale. It offers an easy to use platform to learn and evaluate streaming needs and requirements. We are thrilled to share this project with the wider community as open source!

Data Accelerator offers three level of experiences:

  • The first requires no code at all, using rules to create alerts on data content.
  • The second allows to quickly write a Spark SQL query with additions like LiveQuery, time windowing, in-memory accumulator and more.
  • The third enables integrating custom code written in Scala or via Azure functions.

You can get started locally for Windows, macOs and Linux following these instructions
To deploy to Azure, you can use the ARM template; see instructions deploy to Azure.

The data-accelerator repository contains everything needed to set up an end-to-end data pipeline. There are many ways you can participate in the project:

Getting Started

To unleash the full power Data Accelerator, deploy to Azure and check cloud mode tutorials.

We have also enabled a "hello world" experience that you try out locally by running docker container. When running locally there are no dependencies on Azure, however the functionality is very limited and only there to give you a very cursory overview of Data Accelerator. To run Data Accelerator locally, deploy locally and then check out the local mode tutorials.

Data Accelerator for Spark runs on the following:

  • HDInsights with Spark 2.3
  • Service Fabric (v6.4.637.9590) with
    • .NET Core 2.1
    • ASP.NET
  • App Service with Node 10.6

See the wiki pages for further information on how to build, diagnose and maintain your data pipelines built using Data Accelerator for Spark.

Contributing

If you are interested in fixing issues and contributing to the code base, we would love to partner with you. Try things out, join in the design conversations and make pull requests.

Feedback

Please also see our Code of Conduct.

Security issues

Security issues and bugs should be reported privately, via email, to the Microsoft Security Response Center (MSRC) secure@microsoft.com. You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Further information, including the MSRC PGP key, can be found in the Security TechCenter.

License

This repository is licensed with the MIT license.

MIT License Copyright (c) Microsoft Corporation. All rights reserved. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE

简介

Data Accelerator for Apache Spark simplifies onboarding to Streaming of Big Data. It offers a rich, easy to use experience to help with creation, editing and management of Spark jobs on Azure HDInsights while enabling the full power of the Spark engine. 展开 收起
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