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Help Center/ MapReduce Service/ User Guide/ Buying MRS Clusters/ Quickly Buying an MRS Cluster

Quickly Buying an MRS Cluster

Updated on 2024-09-23 GMT+08:00

MRS consists of multiple big data components, and you can select the cluster type that best fits your service requirements, data types, reliability expectations, and resource budget.

This section uses an HBase query cluster as an example to describe how to quickly purchase an MRS cluster. An HBase cluster uses Hadoop and HBase components to provide a column-oriented distributed cloud storage system featuring enhanced reliability, great performance, and elastic scalability. It applies to the storage and distributed computing of massive amounts of data. You can use HBase to build a storage system capable of storing TB- or even PB-level data. With HBase, you can filter and analyze data with ease and get responses in milliseconds, rapidly mining data value.

Procedure

  1. Go to the Buy Cluster page.
  2. On the displayed page, click the Quick Config tab.
  3. Configure basic cluster information by referring to the following table.

    Table 1 MRS cluster parameters

    Parameter

    Description

    Example Value

    Billing Mode

    Billing mode of a cluster. MRS provides two billing modes: yearly/monthly and pay-per-use.

    Pay-per-use: If you select this mode, a prepaid balance will be frozen. For details, see Billing Description.

    Pay-per-use

    Region

    Region where the resource to be created is located. Resources located in different regions cannot communicate with each other using an internal network. To improve access speed and reduce network latency, choose a region that is close to your own.

    -

    Cluster Name

    MRS cluster name. You can use the default name. However, you are advised to include a project name abbreviation or date for consolidated memory and easy distinguishing.

    After a cluster is created, you can change the cluster name in the cluster list.

    mrs-test

    Cluster Type

    Select a proper MRS cluster type based on service requirements.

    • Analysis cluster: It is used for offline data analysis and comprises data analysis tools like Hadoop, Spark, HBase, Hive, Flink, Oozie, and Tez.
    • Streaming cluster: It processes streaming data to quickly analyze real-time data sources, and it mainly includes streaming data processing tools such as Kafka and Flume.
    • Hybrid cluster: It is utilized for both offline data analysis and stream processing.
    • Custom: You can select from a variety of components that are supported by the corresponding version of the MRS cluster.

    Custom

    Version Type

    MRS provides two types of clusters: LTS and Normal. Different versions provide different components. You can select a version as required.

    • LTS: employs MRS's own components to provide highly reliable clusters with strong DR capabilities, making long-term support and evolution possible.
    • Normal: integrates MRS's mature and stable features and functions with open-source capabilities, offering high performance and stability.

    LTS

    Cluster Version

    Version of the MRS cluster. Different versions may contain different open source component versions and functions. You are advised to select the latest version.

    MRS 3.2.0-LTS.1

    Component

    Cluster templates containing preset opensource components you will need for your business.

    HBase Query Cluster

    AZ

    Resources are assigned to the AZ of the current region during creation. An AZ is a physical region that operates on independent power supplies and networks for resource usage.

    AZ1

    VPC

    VPC to which the MRS cluster node belongs. If no VPC is available, click View VPC to access the network console and create a VPC.

    -

    Subnet

    Subnet information in the VPC. If no subnet is available, click View Subnet to access the network console and create a subnet.

    -

    Cluster Node

    Specifications and quantity of nodes in an MRS cluster.

    For MRS 3.x or later, the memory of the master node must be greater than 64 GB.

    Select the number of cluster node specifications as required.

    Kerberos Authentication

    Whether to enable Kerberos authentication for each component in the MRS cluster. If Kerberos authentication is enabled, users can access component resources only after being authenticated.

    This function cannot be changed after you buy a cluster.

    Switch this function on.

    Username

    Default user for logging in to Manager and nodes in the MRS cluster. User admin is used to log in to Manager, while user root is used to log in to the OS of nodes in the cluster.

    -

    Password/Confirm Password

    Set the passwords for the root and admin users. The passwords are user-defined and must be kept secure.

    -

    Enterprise Project

    Enterprise project is a way to manage cloud resources. It allows you to manage resources and members within a project, and you can choose to use the system-defined enterprise project default or create your own.

    default

    Secure Communications

    To allow the MRS console to access big data components in the user VPC, you need to activate the relevant security group rules. For details, see Configuring Secure Communication Authorization for an MRS Cluster.

    Select this function.

  4. Click Buy Now.

    If Kerberos authentication is enabled, check whether this function is required. If it is, click Continue. If not, click Back to disable it and then proceed with the subsequent step. This function cannot be changed after you buy a cluster.
    NOTE:

    For any doubt about the pricing, click Pricing details in the lower left corner.

  5. Click Back to Cluster List to view the cluster status. Click Access Cluster to view cluster details.

    For details about cluster status during creation, see the description of the status parameters in Table 1.

    It takes some time to create a cluster. The initial status of the cluster is Starting. After the cluster has been created successfully, the cluster status becomes Running.

    On the MRS management console, a maximum of 10 clusters can be concurrently created, and a maximum of 100 clusters can be managed.

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