MapReduce Service

MapReduce Service (MRS) provides enterprise-level big data clusters on the cloud. Tenants can fully control clusters and easily run big data components such as Hadoop, Spark, HBase, Kafka, and Storm.

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Product Advantages
  • Enterprise Level

    MRS is based on the Huawei FusionInsight platform. It provides enterprise-level scheduling to isolate resources, and ensures Service Level Agreements (SLAs) for multi-level users. MRS has been deployed on tens of thousands of nodes.

  • Easy O&M

    MRS leverages a dedicated enterprise-level cluster management system so you can easily manage big data platforms. Platform exceptions are reported by SMS or email. O&M has never been easier.

  • High Security

    With Kerberos authentication, Huawei's security expertise, and Germany PSA security certification, MRS provides role-based access control and sound audit functions to ensure 360-degree protection.

  • Low Cost

    Equipped with a diversified cloud infrastructure, MRS offers extensive computing and storage choices for those on a budget, meaning on-demand operations for MRS clusters and cluster capacities.

Application Scenarios
  • Cloud Migration

  • IoV

  • Finance & Insurance

  • Smart Logistics

  • IoE

  • Smart Water Mgmt.

  • Gaming

  • Energy

Cloud Migration

Migrating an On-premises Big Data Platform to the Cloud

On-premises Hadoop big data platforms (CDH/HDP/...) can be quickly migrated to the cloud, and customers' services and data can be migrated to MRS all at one time. An off-cloud system can be quickly built based on the cloud environment, making it possible to perform rapid service expansion in the future.


No Service Interruption

Online migration of service data ensures no service interruption. More than 100 TB data can be migrated to the cloud within 7 days.

No Modification of Service Code

During offline system migration, service codes are not modified, allowing the service to be migrated quickly.

Massive Data Migration

Petabytes of data can be migrated to the cloud.

Professional Assurance Service

O&M services are provided by Huawei's professional technical team.

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Internet of Vehicles (IoV)

MRS leverages the open-source ecosystem to provide a fast and efficient data processing computing engine that helps automobile enterprises quickly migrate services to the cloud. It also flexibly builds an open, unified, and full-stack big data platform for data analysis.


Unified, Full-Stack, Scalable Data Platform

MRS is an enterprise-level big data platform that isolates computing from storage, providing flexibility and convenience.

Multi-engine Processing for Hybrid Loads

MRS provides various open-source components that can be combined freely, supporting real-time/offline complex service processing.

High Performance at a Low Cost

MRS Kafka and Storm can obtain real-time stream data to implement real-time computing and analysis with high throughput and low latency.

Compatible with Open-Source Standard APIs

MRS is based on open source. It is fully compatible with APIs of the Apache Hadoop ecosystem.

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Finance & Insurance

Finance and Insurance

MRS leverages the advantages of the big data platform on DeC to meet the strict requirements of the insurance industry with regards to compliance, security, and reliability. It reconstructs the IT architecture of traditional insurance enterprises, and quickly builds and deploys insurance service systems. This helps insurance enterprises achieve fast digital transformation, easy service innovation, and agile service evolution.


Robust Security

Meets industry regulatory requirements and protects customers' sensitive data.

Dedicated Resources

Provides dedicated MRS clusters and exclusive resources, and separates compute resources from storage resources.

Flexible Creation, Full-Stack, Easy O&M

Allows users to create a full-stack big data platform with just one click and provides an enterprise-class platform management interface, simplifying O&M.

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Smart Logistics

Smart Logistics

MRS big data analysis platform is used to implement intelligent management of logistics activities, improving service operation efficiency and greatly reducing costs.


High Throughput and Low Latency

Dedicated MRS Kafka clusters with high-throughput, high availability, and low latency capabilities facilitate real-time access of millions of messages.

Large-scale Data Analysis and Processing

MRS Spark supports large-scale data computing. MRS HBase can load and update logistics data in milliseconds, and query and analyze petabytes of time series data.

More Intelligence with AI

MRS uses MLS for big data mining, and provides precise and intelligent prediction and analysis capabilities for logistics organizations, marketing, and operation management.

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Internet of Elevators (IoE)

To adapt to the rapid business innovation and flexible service modes involved in IoE, MRS functions as an open one-stop big data processing platform to implement intelligent elevator management.


Open and Flexible

MRS provides a wide variety of computing products and storage hardware for your choices to meet scenario-specific needs and build a unified and open big data platform. In addition, it offers powerful computing engines and a massive amount of storage, and enables flexible integration of service components.

High Performance and Large Capacity

MRS Kafka works with high-performance general network enhancement (C3ne) ECSs to implement real-time data access for millions of elevators.

AI Supported

MRS supports GPUs that provide real-time high-speed parallel computing and floating-point computing capabilities. These are applicable to video encoding and decoding, deep learning, and scientific computing.

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Smart Water Mgmt.

Smart Water Management

MRS Hadoop provides high-performance, reliable, unified big data storage and analysis functions for water management scenarios.


Unified and Scalable Data Platform

MRS builds an enterprise-level big data platform and provides various open-source components that can be flexibly combined, supporting real-time/offline complex service processing.

High Throughput and Low Latency

Storm can obtain real-time stream data from Kafka to implement real-time computing and analysis with high throughput and low latency.

Integration of Various Types of Data

Various structured, semi-structured, and unstructured data can be computed and processed, and traditional data warehouse data can be easily migrated, facilitating cross-source data exploration and analysis.

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Game log data is accessed through Kafka and Flume in real time. Spark Streaming processes and analyzes the data in real time and stores the analysis results to HBase or Hive for quick game advertisement analysis, data query and analysis, and revenue analysis.


Unified and Scalable Data Platform

MRS functions as an enterprise-level big data platform and provides various open-source components that can be combined flexibly to meet even highly complex service processing needs.

Real Time and High Throughput

MRS Kafka and Flume collect real-time data and integrate with high-performance general network enhancement (C3ne) ECSs to implement real-time access of massive amounts of data.



MRS provides enterprise-level big data cloud services that enable PV plant operators to easily run Hadoop, Spark, HBase, Storm, and other big data components for the purpose of predictive device maintenance.


Unified Big Data platform

MRS functions as an enterprise-level big data platform and provides various big data components that support flexible use in different combinations, meeting customers' requirements for complex service processing.

Mass Data Collection

MRS Kafka and Sqoop support multiple data collection methods, facilitating real-time access of millions of messages.

Easy of Use

SQL APIs can be used to support querying multi-dimensional data for easy data exploration and analysis.

New Features


  • On Demand

    On-demand cluster creation and pay-per-use operations

  • Enterprise-Level Big Data Edition

    Secure, reliable, efficient, and with high availability (HA)

  • Compatibility

    Compatible with x86, Arm, and open source big data ecosystems

On Demand

  • Diversified node and disk specifications

  • Various big data software and versions

  • Temporary clusters, automatically deleted after job execution

  • On-demand cluster scale

  • On-demand cluster capacity expansion

Enterprise-Level Big Data Edition

  • HA deployment on all management nodes

  • Multi-level tenant management

  • Service health and performance management

  • Kerberos security authentication and RBAC

  • Encryption of file systems and data tables

  • High-performance local disks


  • Huawei-developed ARM servers integrated with Huawei-developed OS and databases, forging a home-grown software and hardware integrated platform

  • CarbonData, a high-performance file storage format

  • Various open source computing frameworks, such as, MapReduce, Spark/SparkSQL, Hive, and Storm

  • Spark SQL, compatible with the Hive SQL syntax

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