MapReduce Service (MRS)
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MapReduce Service (MRS)

MapReduce Service (MRS)

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Over 300,000 Nodes

A global presence spanning 300,000+ nodes across 60+ countries and serving 3,000+ customers.

Over 10,000 Commercial Cases

Each of our largest commercial clusters can host over 10,000 nodes and manage more than 500 PB data.

21,000 Nodes in a Single Cluster

Our cluster federation allows for infinite expansion.

IDC MarketScape Report 2020

Recognized by IDC as a leader in both market share and technology among China's big data platform vendors.

A range of MRS cluster options and pre-installed components

A range of MRS cluster options and pre-installed components

  • Hadoop cluster
  • Doris cluster
  • ClickHouse cluster
  • HBase cluster

Why Huawei Cloud MRS?

Decoupled Storage and Compute

Decoupled Storage and Compute

  • Unified data lake utilization across multiple computing engines eliminates data silos, offering flexible resource allocation and on-demand scaling for higher cost-effectiveness.

Superb Performance and Experience

Superb Performance and Experience

  • Millisecond-level query response thanks to four-level vertical optimization on hardware, data organization, computing engines, and AI-driven enhancements.

Cutting-Edge Open-Source Technologies

Cutting-Edge Open-Source Technologies

  • In-depth reconstruction of mainstream engines Spark, Hive, and Flink, with indexing, caching, and metadata; millisecond-level point queries thanks to Huawei-developed CarbonData; Superior Scheduler for 20,000+ nodes in a single cluster.

High Security and Availability

High Security and Availability

  • High availability of a single cluster across AZs; rolling patch installation/upgrade and reconnection, no service interruption; network resource isolation, account security, and data access control.

Process, analyze, query, or mine huge amounts of data with a variety of components

Big Data
Rapid Migration

Effortlessly migrate from on-premises or other big data platforms (IDC, CDH, Hontonwoks, and FusionInsight) to MRS. On-premises systems can also be built for rapid business growth.

Advantages
Decoupled Storage and Compute

Use multi-core Kunpeng-powered compute resources and storage at low costs.

Elastic Scaling

Combine diverse compute and storage resources that can be automatically scaled based on demand.

Open Source Compatibility

Migrate your workloads with open source APIs, no service code modification.

Simple and Fast Migration

Use a set of migration tools to minimize errors and service interruption.

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Internet
Internet

Cloud-based big data platform with decoupled storage and Kunpeng computing power for scalable, cost-effective service management, freeing you from low utilization and high O&M costs.

Advantages
Cost-effective architecture and flexible data sharing

-Decoupled compute and storage: service data and engine-level metadata

- Heterogeneous computing power: Kunpeng, x86, bare metal servers, VMs, and containers

Engines originating from, but superior to, open-source engines

-Interfaces of mainstream engines Hadoop, Spark, and Hive are used, and the engine kernels are optimized to deliver higher performance.

-MRS CarbonData supports millisecond-level point query of massive data and minute-level data updates, and Hetu supports unified SQL for cross-source and cross-domain queries.

High Availability

MRS is the first big data service to provide cross-AZ clusters.

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IoV
IoV

MRS leverages open source compatibilities to provide fast data processing engines that allow you to analyze huge amounts of car data.

Advantages
Unified, Full-Stack, Scalable Data Platform

MRS is an enterprise-level, big data platform with decoupled storage and compute, for more convenient, flexible scalability.

Multi-engine Processing for Hybrid Workloads

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

High Performance at a Low Cost

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

Compatible with Open Source Standard APIs

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

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Finance
Finance and Insurance

MRS meets the strict requirements of the insurance industry, ensuring compliance, security, and reliability. A traditional architecture can be rapidly rebuilt and deployed for insurance enterprises that need to transform fast. Digital transformation makes innovating and evolving services easier and faster.

Advantages
Robust Security

Protects customers' sensitive data.

Dedicated Resources

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

Flexible Creation, Full-Stack, Easy O&M

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

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Smart Logistics
Smart Logistics

MRS is used for the intelligent management of logistics and supply chain routes, improving service efficiency and greatly reducing costs.

Advantages
High Throughput and Low Latency

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

Large-Scale Data Analysis and Fast 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.

Greater Intelligence with AI

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

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Water
Smart Water Management

MRS Hadoop offers reliable, high-performance big data storage and analysis for intelligent water management.

Advantages
Unified and Scalable Data Platform

MRS gives you an enterprise-class big data platform with open source components that can be flexibly stacked, to support real-time/offline complex service processing.

High Throughput and Low Latency

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

Integration of Various Types of Data

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

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Gaming
Gaming

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

Advantages
Unified and Scalable Data Platform

MRS offers an enterprise-class big data platform with open source components that can be flexibly stacked to meet 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 for real-time access of massive amounts of data.

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Energy
Energy

MRS provides enterprise-class big data cloud services for predictive device maintenance in power plants using Hadoop, Spark, HBase, Flink, and other big data components.

Advantages
Unified Big Data Platform

MRS gives you an enterprise-class big data platform with open source components that can be flexibly stacked to support real-time/offline complex service processing.

Mass Data Ingestion

MRS Kafka and Sqoop support multiple data ingestion methods to facilitate real-time ingestion of millions of messages.

Easy of Integration

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

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Featured Functions

Featured Functions

Converged Platform

Utilize data lakes, data warehouses, BI, and AI workloads in one place on the full-stack big data platform that supports Kafka, Flink, Spark, HBase, ClickHouse, and Presto.

One-Click Migration

Your on-premises platforms can be smoothly migrated without service interruptions or code changes.

Flexible Scaling

Both Kunpeng and x86 servers can be deployed heterogeneously in a cluster and flexibly scaled as you configured for peak and off-peak hours, with hundreds of nodes provisioned in minutes.

Enterprise-level Cockpit

Centrally manage clusters with intuitive UIs, monitor your clusters with refined metrics and alarms, change configurations and update patches without service interruption, and retrieve logs in real time.

Continuous Innovation with Millions of Customers

Continuous Innovation with Millions of Customers

Meitu Mogujie China Merchants Bank T3Go
Meitu Runs Big Data Services on MRS to Serve Over 2 Billion Users Worldwide

Meitu is able to expand resources flexibly and independently thanks to the decoupled storage and compute of FusionInsight. Using only one set of data for multiple types of analysis and computing, the company achieved 40% higher resource utilization and reduced overall costs by 30%.

Mogujie Used MRS to Build Its IT System, Manage O&M, and Quickly Innovate

Mogujie upgraded its Spark big data and machine learning system with Huawei's cloud-native high-performance computing for faster data analysis and AI training. This helped the company greatly improve its O&M efficiency.

China Merchants Bank Provides Users with Real-Time Self Service

CMB decreased its promotional SMS messages by 82%, using FusionInsight big data platform to cover all users who purchased its wealth management services.

Storage and Compute of T3Go's Lakehouse Architecture Now Decoupled

T3Go's lakehouse is built based on the open source Hudi framework and hosted on Huawei Cloud FusionInsight for both BI and AI workloads.

Industry Recognition

Industry Recognition

Excellent Solution at Big Data Industry Conference 2021

Huawei FusionInsight Intelligent Data Lake won the Excellent Solution Award at China's Big Data Industry Conference 2021 in recognition of Huawei Cloud's continuous technological innovation.

Excellent Project at Big Data Expo 2022

Huawei Cloud FusionInsight MRS won the Excellent Project for Leading Technology Achievement Award at the Big Data Expo 2022, hosted by the National Development and Reform Commission and Ministry of Industry and Information Technology (MIIT).

IDC: No. 1 in China's Big Data Market Share

IDC ranked Huawei Cloud No. 1 in its China Big Data Platform Market Share 2022 report. This is the third time that Huawei Cloud has ranked No. 1 in the market.

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