Combining cloud computing and community open-source technologies such as Hadoop, Hive, Spark, HBase, Presto, and Storm, Tencent Cloud Elastic MapReduce (EMR) provides secure and cost-effective cloud-based Hadoop services featuring high reliability and elastic scalability. Using EMR, you can create a secure and reliable Hadoop cluster in just minutes to analyze petabytes of data stored on the data nodes in the cluster or in Cloud Object Storage (COS).
Overview
Benefits
Flexibility
EMR allows you to launch a secure and reliable dedicated Hadoop cluster in minutes in the web-based console or via APIs. You can mix and match suitable editions of big data components such as Hive, Spark, HBase and Presto to cater to your different business departments. You can easily monitor alarm configurations and perform OPS operations for nodes, components and processes in the console.
Elasticity
EMR enables you to scale the managed Hadoop clusters manually or automatically according to your business curves or monitoring metrics. EMR's storage-computation separation even allows you to terminate a cluster to maximize resource efficiency.
Reliability
EMR supports hot failover for CBS-based nodes. It features a primary/secondary disaster recovery mechanism where the secondary node starts within seconds when the primary node fails, ensuring the high availability of big data services. The metadata of its components such as Hive supports remote disaster recovery. Computation-storage separation ensures high data persistence for COS data storage. EMR is equipped with a comprehensive monitoring system that helps you quickly identify and locate cluster exceptions to ensure stable cluster operations.
Security
VPCs provide a convenient network isolation method that facilitates your network policy planning for managed Hadoop clusters. Network ACLs and security groups can be created to filter traffic at the subnet and host levels to comprehensively meet your network security needs. Tencent Cloud's security reinforcement service provides an integrated security solution for EMR clusters, covering network protection, intrusion detection and vulnerability protection.
Features
Quick Deployment
It takes just three steps to launch a dedicated big data cluster in the EMR console. EMR provides a wide range of open-source big data components that can be mixed and matched as needed during cluster creation, including but not limited to Hive, Spark, HBase, Presto, Flink and Storm. EMR also offers secure and cost-effective cloud-based Hadoop services featuring high reliability and elastic scalability. In addition, you can use APIs to retain creation parameters to recreate and terminate clusters as often as you want.
EMR supports cluster deployment on a variety of models, allowing you to configure the type and amount of cluster CPU, memory and storage capacity for different business scenarios.
Elasticity
Cluster creation in minutes
A secure and stable cloud-based Hadoop cluster can be created in the console in just minutes.
Cluster scaling in minutes
Existing EMR clusters scale seamlessly in a matter of minutes to accommodate the rapid changes of your Internet-based businesses.
API support
EMR clusters can easily be created, scaled, or terminated through APIs.
Storage-computation Separation
Separated in-cluster storage and computation
Storage and compute nodes in cloud-hosted Hadoop clusters can be separated so that you can scale the compute nodes as needed to lower hardware costs.
COS-based storage-computation separation
COS stores massive amounts of data for analytics, which facilitates the creation of various versions of EMR clusters to analyze the same data, thereby optimizing architectural flexibility and reducing storage costs.
OS Support
Multi-channel monitoring and alarms
EMR boasts comprehensive monitoring and OPS systems, which can instantly detect exceptions in components such as Spark, Hive and Presto and in tasks to ensure the stable operations of big data clusters.
Technical support
In addition to EMR documentation, we provide all-round technical support via email.
Scenarios
Offline Data Analytics
HBase
Streaming Data Processing
COS Data Analytics
After syncing massive amounts of logs from game, web application and mobile app business servers to EMR nodes or COS, you can use tools like Hue to leverage Hive, Spark, Presto and other mainstream computing frameworks to quickly gain data insights.
HBase is a highly scalable column-based distributed big data storage system. EMR supports native HBase components, allowing you to create and use the managed HBase clusters conveniently and promptly. Low-latency SQL access to HBase databases is made possible with the aid of the Phoenix tool.
After the data generated in real time on business servers is pushed to the messaging middleware through APIs and SDKs in programs/tools, you can analyze it in EMR by selecting the appropriate streaming data processing engine to implement real-time data computation and decision-making.
Massive amounts of data stored in COS can be quickly analyzed by EMR for complete storage-computation separation, enabling you to take full advantage of various data synchronization tools provided by COS. In addition, you can use multiple Hadoop cluster versions to analyze the same data to achieve data consistency and resolve legacy issues caused by the coexistence of multi-version Hadoop clusters.
Pricing
Tencent Cloud Elastic MapReduce offers flexible usage and billing plans. Billing is accurate to the node level. You can select nodes with different specifications to form a cluster and adjust the number of nodes as your business scale changes. For product pricing details, see Billing Overvie.