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Kunpeng BoostKit for Big Data

Kunpeng BoostKit for Big Data optimizes data processing for big data components, improves concurrent computing, and leverages the multi-core feature of the Kunpeng processors to provide you with excellent big data service performance.

Starting from Here

  • What's New

    Describes the latest updates in documents of Kunpeng BoostKit for Big Data.

  • Feature List

    Provides an overview of basic and application acceleration features.

  • Technical White Paper

    Describes the solution architecture, networking, typical configuration, and key features of Kunpeng BoostKit for Big Data.

  • List of Fixed Vulnerabilities

    Provides details about all fixed vulnerabilities in the feature and integrated platforms, components, libraries, and open source and third-party software.

Basic Acceleration Features

Application Acceleration Features

  • OmniRuntime Features

    OmniRuntime consists of a series of features provided by Kunpeng BoostKit for Big Data in terms of application acceleration. It aims to improve the performance of end-to-end data loading, computing, and exchange through plugins, thereby improving the performance of big data analytics.

  • Machine Learning Algorithm Library

    The machine learning algorithm library is compatible with native Spark APIs. It has optimized machine learning algorithms, greatly improving the computing performance in big data algorithm scenarios. This library supports the architecture of the Kunpeng processor.

Integration of Big Data Features with openEuler

Open Source Enablement

  • Hadoop

    Guide for Hadoop porting and deployment.

  • Spark

    Guide for porting, deployment, and tuning of Spark.

  • Hive

    Guide for porting, deployment, and tuning of Hive.

  • HBase

    Guide for porting, deployment, and tuning of HBase.

  • Doris

    Guide for Doris deployment and instruction optimization.

  • ClickHouse

    Guide for porting, deployment, and tuning of ClickHouse.

  • Flink

    Guide for porting, deployment, and tuning of Flink.

  • Kafka

    Guide for porting, deployment, and tuning of Kafka.

  • ZooKeeper

    Guide for ZooKeeper deployment.

  • Storm

    Guide for porting, deployment, and tuning of Storm.

  • Phoenix

    Guide for Phoenix porting.

  • Druid

    Guide for Druid porting.

  • Solr

    Guide for Solr deployment.

  • ELK

    Guide for porting, deployment, and tuning of Elasticsearch.

  • Third-Party Dependency Libraries

    Guide for porting third-party libraries for big data to a Kunpeng server to ensure compatibility and performance across various data processing, analytics, and software development tasks.

  • Porting and Tuning Using the Kunpeng DevKit

    Cases of using the Kunpeng Porting Advisor for porting and the Kunpeng System Profiler for tuning.

Test Guide

  • Test Guide

    Explains how to install and use the big data test tool.

Troubleshooting

  • Troubleshooting Cases

    Provides answers to FAQs raised during the installation and use of Kunpeng BoostKit for Big Data.