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
Help Center/ Cloud Data Migration/ Best Practices/ Scheduling a CDM Job by Transferring Parameters Using DataArts Factory

Scheduling a CDM Job by Transferring Parameters Using DataArts Factory

Updated on 2024-08-30 GMT+08:00

You can use EL expressions in DataArts Factory to transfer parameters to a CDM job to schedule it.

NOTE:
  • The parameter transfer function is supported by CDM 2.8.6 or later versions.
  • This section uses a CDM job for migrating data from Oracle to MRS Hive as an example.

Prerequisites

A CDM incremental package is available.

Creating a CDM Migration Job

  1. Log in to the console, locate an instance, click Access, and click DataArts Migration.
  2. On the Cluster Management page, click Job Management in the Operation column.

    Figure 1 Cluster Management

  3. Click the Links tab and then Create Link to create an Oracle link and an MRS Hive link. For details, see Link to an Oracle Database and Link to Hive.
  4. Click the Table/File Migration tab and then Create Job to create a data migration job.
  5. Configure parameters for the source Oracle link and destination MRS Hive link, and configure the parameter to transfer in ${varName} format (${cur_date} in this example).

    Figure 2 Creating a job
    NOTE:

    The Retry upon Failure parameter is unavailable in the CDM migration job. You can configure this parameter on the CDM node in DataArts Factory.

Creating and Executing a Data Development Job

  1. On the DataArts Studio console, locate a workspace and click DataArts Factory.
  2. In the navigation pane of the DataArts Factory homepage, choose Data Development > Develop Job.
  3. On the Develop Job page, click Create Job.

    Figure 3 Create Job

  4. In the displayed dialog box, configure job parameters and click OK.

    Table 1 Job parameters

    Parameter

    Description

    Job Name

    Name of the job. The name must contain 1 to 128 characters, including only letters, numbers, hyphens (-), underscores (_), and periods (.).

    Job Type

    Type of the job.

    • Batch processing: Data is processed periodically in batches based on the scheduling plan, which is used in scenarios with low real-time requirements. This type of job is a pipeline that consists of one or more nodes and is scheduled as a whole. It cannot run for an unlimited period of time, that is, it must end after running for a certain period of time.

      You can configure job-level scheduling tasks for batch processing jobs. For details, see Setting Up Scheduling for a Job Using the Batch Processing Mode.

    • Real-time processing: Data is processed in real time, which is used in scenarios with high real-time performance. This type of job is a business relationship that consists of one or more nodes. You can configure a scheduling policy for each node, and the tasks started by nodes can keep running for an unlimited period of time. In this type of job, lines with arrows represent only service relationships, rather than task execution processes or data flows.

      You can configure node-level scheduling tasks for real-time processing jobs. For details, see Setting Up Scheduling for Nodes of a Job Using the Real-Time Processing Mode.

    Creation Method

    Job creation method

    • Create Empty Job: Create an empty job.
    • Create Based on Template: Use a template provided by DataArts Factory to create a job.

    Select Directory

    Directory to which the job belongs. The default value is the root directory.

    Owner

    Owner of the job

    Priority

    Priority of the job. The options are High, Medium, and Low.

    Agency

    After an agency is configured, the job interacts with other services as an agency during job execution.

    NOTE:

    A job-level agency takes precedence over a workspace-level agency.

    Log Path

    Path of the OBS bucket for storing job logs. By default, logs are stored in an OBS bucket named dlf-log-{Projectid}.

    NOTE:
    • If you want to customize a storage path, select the bucket that you have created on OBS by following the instructions provided in (Optional) Changing a Job Log Storage Path.
    • Ensure that you have the read and write permissions on the OBS bucket specified by this parameter, or the system cannot write or display logs.

  5. Add a CDM Job node in the data development job and associate the node with the created CDM job.

    Figure 4 Associating the CDM Job node with the created CDM job

  6. Configure the parameter to be transferred to the CDM job.

    Figure 5 Configuring the parameter to be transferred
    NOTE:

    When the job is scheduled and executed, the value of the configured parameter will be transferred to the CDM job. The value of the parameter cur_date can be set to a fixed value (for example, 2021-11-10 00:00:00) or an EL expression (for example, #{DateUtil.format(DateUtil.addDays(Job.planTime,-1),"yyyy-MM-dd")} which means the day before the scheduled job execution date. For more EL expressions, see EL expressions.

  7. Save and submit a job version and click Test to execute the data development job.
  8. After the data development job is executed, click Monitor in the upper right corner to go to the Monitor Job page and check whether the generated task or instance meets requirements.

    Figure 6 Viewing the execution result

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