Compute
Elastic Cloud Server
Huawei Cloud Flexus
Bare Metal Server
Auto Scaling
Image Management Service
Dedicated Host
FunctionGraph
Cloud Phone Host
Huawei Cloud EulerOS
Networking
Virtual Private Cloud
Elastic IP
Elastic Load Balance
NAT Gateway
Direct Connect
Virtual Private Network
VPC Endpoint
Cloud Connect
Enterprise Router
Enterprise Switch
Global Accelerator
Management & Governance
Cloud Eye
Identity and Access Management
Cloud Trace Service
Resource Formation Service
Tag Management Service
Log Tank Service
Config
OneAccess
Resource Access Manager
Simple Message Notification
Application Performance Management
Application Operations Management
Organizations
Optimization Advisor
IAM Identity Center
Cloud Operations Center
Resource Governance Center
Migration
Server Migration Service
Object Storage Migration Service
Cloud Data Migration
Migration Center
Cloud Ecosystem
KooGallery
Partner Center
User Support
My Account
Billing Center
Cost Center
Resource Center
Enterprise Management
Service Tickets
HUAWEI CLOUD (International) FAQs
ICP Filing
Support Plans
My Credentials
Customer Operation Capabilities
Partner Support Plans
Professional Services
Analytics
MapReduce Service
Data Lake Insight
CloudTable Service
Cloud Search Service
Data Lake Visualization
Data Ingestion Service
GaussDB(DWS)
DataArts Studio
Data Lake Factory
DataArts Lake Formation
IoT
IoT Device Access
Others
Product Pricing Details
System Permissions
Console Quick Start
Common FAQs
Instructions for Associating with a HUAWEI CLOUD Partner
Message Center
Security & Compliance
Security Technologies and Applications
Web Application Firewall
Host Security Service
Cloud Firewall
SecMaster
Anti-DDoS Service
Data Encryption Workshop
Database Security Service
Cloud Bastion Host
Data Security Center
Cloud Certificate Manager
Edge Security
Managed Threat Detection
Blockchain
Blockchain Service
Web3 Node Engine Service
Media Services
Media Processing Center
Video On Demand
Live
SparkRTC
MetaStudio
Storage
Object Storage Service
Elastic Volume Service
Cloud Backup and Recovery
Storage Disaster Recovery Service
Scalable File Service Turbo
Scalable File Service
Volume Backup Service
Cloud Server Backup Service
Data Express Service
Dedicated Distributed Storage Service
Containers
Cloud Container Engine
SoftWare Repository for Container
Application Service Mesh
Ubiquitous Cloud Native Service
Cloud Container Instance
Databases
Relational Database Service
Document Database Service
Data Admin Service
Data Replication Service
GeminiDB
GaussDB
Distributed Database Middleware
Database and Application Migration UGO
TaurusDB
Middleware
Distributed Cache Service
API Gateway
Distributed Message Service for Kafka
Distributed Message Service for RabbitMQ
Distributed Message Service for RocketMQ
Cloud Service Engine
Multi-Site High Availability Service
EventGrid
Dedicated Cloud
Dedicated Computing Cluster
Business Applications
Workspace
ROMA Connect
Message & SMS
Domain Name Service
Edge Data Center Management
Meeting
AI
Face Recognition Service
Graph Engine Service
Content Moderation
Image Recognition
Optical Character Recognition
ModelArts
ImageSearch
Conversational Bot Service
Speech Interaction Service
Huawei HiLens
Video Intelligent Analysis Service
Developer Tools
SDK Developer Guide
API Request Signing Guide
Terraform
Koo Command Line Interface
Content Delivery & Edge Computing
Content Delivery Network
Intelligent EdgeFabric
CloudPond
Intelligent EdgeCloud
Solutions
SAP Cloud
High Performance Computing
Developer Services
ServiceStage
CodeArts
CodeArts PerfTest
CodeArts Req
CodeArts Pipeline
CodeArts Build
CodeArts Deploy
CodeArts Artifact
CodeArts TestPlan
CodeArts Check
CodeArts Repo
Cloud Application Engine
MacroVerse aPaaS
KooMessage
KooPhone
KooDrive

Preparing Data in an MRS Cluster

Updated on 2022-08-16 GMT+08:00

Before importing data from MRS to a GaussDB(DWS) cluster, you must have:

  1. Created an MRS cluster.
  2. Created the Hive/Spark ORC table in the MRS cluster and stored the table data to the HDFS path corresponding to the table.

If you have completed the preparations, skip this section.

In this tutorial, the Hive ORC table will be created in the MRS cluster as an example to complete the preparation work. The process for creating the Spark ORC table in the MRS cluster and the SQL syntax are similar to those of Hive.

Data File

The sample data of the product_info.txt data file is as follows:

100,XHDK-A-1293-#fJ3,2017-09-01,A,2017 Autumn New Shirt Women,red,M,328,2017-09-04,715,good
205,KDKE-B-9947-#kL5,2017-09-01,A,2017 Autumn New Knitwear Women,pink,L,584,2017-09-05,406,very good!
300,JODL-X-1937-#pV7,2017-09-01,A,2017 autumn new T-shirt men,red,XL,1245,2017-09-03,502,Bad.
310,QQPX-R-3956-#aD8,2017-09-02,B,2017 autumn new jacket women,red,L,411,2017-09-05,436,It's really super nice
150,ABEF-C-1820-#mC6,2017-09-03,B,2017 Autumn New Jeans Women,blue,M,1223,2017-09-06,1200,The seller's packaging is exquisite
200,BCQP-E-2365-#qE4,2017-09-04,B,2017 autumn new casual pants men,black,L,997,2017-09-10,301,The clothes are of good quality.
250,EABE-D-1476-#oB1,2017-09-10,A,2017 autumn new dress women,black,S,841,2017-09-15,299,Follow the store for a long time.
108,CDXK-F-1527-#pL2,2017-09-11,A,2017 autumn new dress women,red,M,85,2017-09-14,22,It's really amazing to buy
450,MMCE-H-4728-#nP9,2017-09-11,A,2017 autumn new jacket women,white,M,114,2017-09-14,22,Open the package and the clothes have no odor
260,OCDA-G-2817-#bD3,2017-09-12,B,2017 autumn new woolen coat women,red,L,2004,2017-09-15,826,Very favorite clothes
980,ZKDS-J-5490-#cW4,2017-09-13,B,2017 Autumn New Women's Cotton Clothing,red,M,112,2017-09-16,219,The clothes are small
98,FKQB-I-2564-#dA5,2017-09-15,B,2017 autumn new shoes men,green,M,4345,2017-09-18,5473,The clothes are thick and it's better this winter.
150,DMQY-K-6579-#eS6,2017-09-21,A,2017 autumn new underwear men,yellow,37,2840,2017-09-25,5831,This price is very cost effective
200,GKLW-l-2897-#wQ7,2017-09-22,A,2017 Autumn New Jeans Men,blue,39,5879,2017-09-25,7200,The clothes are very comfortable to wear
300,HWEC-L-2531-#xP8,2017-09-23,A,2017 autumn new shoes women,brown,M,403,2017-09-26,607,good
100,IQPD-M-3214-#yQ1,2017-09-24,B,2017 Autumn New Wide Leg Pants Women,black,M,3045,2017-09-27,5021,very good.
350,LPEC-N-4572-#zX2,2017-09-25,B,2017 Autumn New Underwear Women,red,M,239,2017-09-28,407,The seller's service is very good
110,NQAB-O-3768-#sM3,2017-09-26,B,2017 autumn new underwear women,red,S,6089,2017-09-29,7021,The color is very good 
210,HWNB-P-7879-#tN4,2017-09-27,B,2017 autumn new underwear women,red,L,3201,2017-09-30,4059,I like it very much and the quality is good.
230,JKHU-Q-8865-#uO5,2017-09-29,C,2017 Autumn New Clothes with Chiffon Shirt,black,M,2056,2017-10-02,3842,very good

Creating a Hive ORC Table in an MRS Cluster

  1. Create an MRS cluster.

    For details, see "Creating a Cluster > Custom Creation of a Cluster" in the MapReduce Service User Guide.

  2. Download the client.
    1. Go back to the MRS cluster page. Click the cluster name. On the Dashboard tab page of the cluster details page, click Access Manager. If a message is displayed indicating that EIP needs to be bound, bind an EIP first.
    2. Enter the username admin and its password for logging in to MRS Manager. The password is the one you entered when creating the MRS cluster.
    3. Choose Services > Download Client. Set Client Type to Only configuration files and set Download To to Server. Click OK.

  3. Log in to the Hive client of the MRS cluster.
    1. Log in to a Master node.

      For details, see "Remote Login Guide > Logging In to a Master Node" in the MapReduce Service User Guide.

    2. Run the following command to switch the user:
      sudo su - omm
    3. Run the following command to go to the client directory:
      cd /opt/client
    4. Run the following command to configure the environment variables:
      source bigdata_env
    5. If Kerberos authentication is enabled for the current cluster, run the following command to authenticate the current user. The current user must have the permission for creating Hive tables. For details, see "Creating a Role" in the MapReduce Service User Guide. Configure a role with the required permissions. For details, see "Creating a Role" in the MapReduce Service User Guide. Bind a role to the user. If the Kerberos authentication is disabled for the current cluster, skip this step.
      kinit MRS cluster user

      Example: kinit hiveuser

    6. Run the following command to start the Hive client:
      beeline
  4. Create a database demo on Hive.

    Run the following command to create the database demo:

    CREATE DATABASE demo;
  5. Create table product_info of the Hive TEXTFILE type in the database demo and import the Data File (product_info.txt) to the HDFS path corresponding to the table.

    Run the following command to switch to the database demo:

    USE demo;

    Run the following command to create table product_info and define the table fields based on data in the Data File.

    DROP TABLE product_info;
    
    CREATE TABLE product_info 
    (    
        product_price                int            ,
        product_id                   char(30)       ,
        product_time                 date           ,
        product_level                char(10)       ,
        product_name                 varchar(200)   ,
        product_type1                varchar(20)    ,
        product_type2                char(10)       ,
        product_monthly_sales_cnt    int            ,
        product_comment_time         date           ,
        product_comment_num          int        ,
        product_comment_content      varchar(200)                   
    ) 
    row format delimited fields terminated by ',' 
    stored as TEXTFILE;

    For details about how to import data to an MRS cluster, see "Cluster Operation Guide > Managing Active Clusters > Managing Data Files" in the MapReduce Service User Guide.

  6. Create a Hive ORC table named product_info_orc in the database demo.

    Run the following command to create the Hive ORC table product_info_orc. The table fields are the same as those of the product_info table created in the previous step.

    DROP TABLE product_info_orc;
    
    CREATE TABLE product_info_orc
    (    
        product_price                int            ,
        product_id                   char(30)       ,
        product_time                 date           ,
        product_level                char(10)       ,
        product_name                 varchar(200)   ,
        product_type1                varchar(20)    ,
        product_type2                char(10)       ,
        product_monthly_sales_cnt    int            ,
        product_comment_time         date           ,
        product_comment_num          int            ,
        product_comment_content      varchar(200)                   
    ) 
    row format delimited fields terminated by ',' 
    stored as orc;
  7. Insert data in the product_info table to the Hive ORC table product_info_orc.
    insert into product_info_orc select * from product_info;

    Query table product_info_orc.

    select * from product_info_orc;

    If data displayed in the Data File can be queried, the data has been successfully inserted to the ORC table.

We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out more

Feedback

Feedback

Feedback

0/500

Selected Content

Submit selected content with the feedback