Creating a Flink OpenSource SQL Job

Prerequisites

• You have prepared the source and sink streams.
• A datasource connection has been created to enable the network between the queue where the job is about to run and external data sources.
  • For details about the external data sources that can be accessed by Flink jobs, see Common Development Methods for DLI Cross-Source Analysis.
  • For how to create a datasource connection, see Configuring the Network Connection Between DLI and Data Sources (Enhanced Datasource Connection).

    On the Resources > Queue Management page, locate the queue you have created, click More in the Operation column, and select Test Address Connectivity to check if the network connection between the queue and the data source is normal. For details, see Testing Address Connectivity.

Precautions

Before creating jobs and submitting tasks, you are advised to enable CTS to record DLI operations for queries, audits, and tracking. Using CTS to Audit DLI lists DLI operations that can be recorded by CTS.

For how to enable CTS and view trace details, see the Cloud Trace Service Getting Started.

Creating a Flink OpenSource SQL Job

1. In the left navigation pane of the DLI management console, choose Job Management > Flink Jobs. The Flink Jobs page is displayed.
2. In the upper right corner of the Flink Jobs page, click Create Job.
   Figure 1 Creating a Flink OpenSource SQL job
   

3. Set job parameters.

   Table 1 Job parameters

   Parameter	Description
   Type	Set Type to Flink OpenSource SQL. You will need to start jobs by compiling SQL statements.
   Name	Job name. Enter 1 to 57 characters. Only letters, numbers, hyphens (-), and underscores (_) are allowed. NOTE: The job name must be globally unique.
   Description	Description of a job. It can contain a maximum of 512 characters.
   Template Name	You can select a sample template or a custom job template. For details about templates, see Managing Flink Job Templates.
   Tags	Tags used to identify cloud resources. A tag includes the tag key and tag value. If you want to use the same tag to identify multiple cloud resources, that is, to select the same tag from the drop-down list box for all services, you are advised to create predefined tags on the Tag Management Service (TMS). If your organization has configured tag policies for DLI, add tags to resources based on the policies. If a tag does not comply with the tag policies, resource creation may fail. Contact your organization administrator to learn more about tag policies. For details, see Tag Management Service User Guide. NOTE: A maximum of 20 tags can be added. Only one tag value can be added to a tag key. The key name in each resource must be unique. Tag key: Enter a tag key name in the text box. NOTE: A tag key can contain a maximum of 128 characters. Only letters, numbers, spaces, and special characters (_.:=+-@) are allowed, but the value cannot start or end with a space or start with _sys_. Tag value: Enter a tag value in the text box. NOTE: A tag value can contain a maximum of 255 characters. Only letters, numbers, spaces, and special characters (_.:=+-@) are allowed. The value cannot start or end with a space.

4. Click OK to enter the editing page.
5. Edit an OpenSource SQL job.

   Enter detailed SQL statements in the statement editing area. For details about SQL statements, see the Data Lake Insight Flink OpenSource SQL Syntax Reference.

6. Click Check Semantics.
   • You can Start a job only after the semantic verification is successful.
   • If verification is successful, the message "The SQL semantic verification is complete. No error." will be displayed.
   • If verification fails, a red "X" mark will be displayed in front of each SQL statement that produced an error. You can move the cursor to the "X" mark to view error details and change the SQL statement as prompted.
   

   Flink 1.15 does not support syntax verification.

7. Set job running parameters.
   Figure 2 Setting running parameters for Flink OpenSource SQL
   

   Table 2 Running parameters

   Parameter	Description
   Queue	Select a queue to run the job.
   UDF Jar	UDF JAR file, which contains UDFs that can be called in subsequent jobs. There are the following ways to manage UDF JAR files: Upload packages to OBS: Upload Jar packages to an OBS bucket in advance and select the corresponding OBS path. Upload packages to DLI: Upload JAR files to an OBS bucket in advance and create a package on the Data Management > Package Management page of the DLI management console. For details, see Creating a DLI Package. For Flink 1.15 or later, only OBS packages can be selected when creating jobs, and DLI packages are not supported.
   Flink Version	Flink version used for job running. Flink versions have varying feature support. If you choose to use Flink 1.15, make sure to configure the agency information for the cloud service that DLI is allowed to access in the job. For the syntax of Flink 1.15, see Flink OpenSource SQL 1.15 Usage and Flink OpenSource SQL 1.15 Syntax. For the syntax of Flink 1.12, see Flink OpenSource SQL 1.12 Syntax. NOTE: You are not advised to use Flink of different versions for a long time. Doing so can lead to code incompatibility, which can negatively impact job execution efficiency. Doing so may result in job execution failures due to conflicts in dependencies. Jobs rely on specific versions of libraries or components.
   Agency	If you choose Flink 1.15 to execute your job, you can create a custom agency to allow DLI to access other services.
   CUs	Sum of the number of compute units and job manager CUs of DLI. CU is also the billing unit of DLI. One CU equals 1 vCPU and 4 GB. The value is the number of CUs required for job running and cannot exceed the number of CUs in the bound queue.
   Job Manager CUs	Number of CUs of the management unit.
   Parallelism	Number of tasks concurrently executed by each operator in a job. NOTE: This value cannot be greater than four times the compute units (number of CUs minus the number of job manager CUs).
   Task Manager Config	Whether Task Manager resource parameters are set If selected, you need to set the following parameters: CU(s) per TM: Number of resources occupied by each Task Manager. Slot(s) per TM: Number of slots contained in each Task Manager. If not selected, the system automatically uses the default values. CU(s) per TM: The default value is 1. Slot(s) per TM: The default value is (Parallelism x CU(s) per TM)/(CUs – Job Manager CUs).
   OBS Bucket	OBS bucket to store job logs and checkpoint information. If the OBS bucket you selected is unauthorized, click Authorize.
   Save Job Log	Whether job running logs are saved to OBS. The logs are saved in the following path: Bucket name/jobs/logs/Directory starting with the job ID. CAUTION: You are advised to configure this parameter. Otherwise, no run log is generated after the job is executed. If the job fails, the run log cannot be obtained for fault locating. If this option is selected, you need to set the following parameters: OBS Bucket: Select an OBS bucket to store job logs. If the OBS bucket you selected is unauthorized, click Authorize. NOTE: If Enable Checkpointing and Save Job Log are both selected, you only need to authorize OBS once.
   Alarm on Job Exception	Whether to notify users of any job exceptions, such as running exceptions or arrears, via SMS or email. If this option is selected, you need to set the following parameters: SMN Topic Select a custom SMN topic. For how to create a custom SMN topic, see Creating a Topic.
   Enable Checkpointing	Whether to enable job snapshots. If this function is enabled, jobs can be restored based on the checkpoints. If this option is selected, you need to set the following parameters: Checkpoint Interval: interval for creating checkpoints, in seconds. The value ranges from 1 to 999999, and the default value is 30. Checkpoint Mode can be set to either of the following values: At least once: Events are processed at least once. Exactly once: Events are processed only once. If you select Enable Checkpointing, you also need to set OBS Bucket. OBS Bucket: Select an OBS bucket to store your checkpoints. If the OBS bucket you selected is unauthorized, click Authorize. The checkpoint path is Bucket name/jobs/checkpoint/Directory starting with the job ID. NOTE: If Enable Checkpointing and Save Job Log are both selected, you only need to authorize OBS once.
   Auto Restart upon Exception	Whether automatic restart is enabled. If enabled, jobs will be automatically restarted and restored when exceptions occur. If this option is selected, you need to set the following parameters: Max. Retry Attempts: maximum number of retries upon an exception. The unit is times/hour. Unlimited: The number of retries is unlimited. Limited: The number of retries is user-defined. Restore Job from Checkpoint: This parameter is available only when Enable Checkpointing is selected.
   Idle State Retention Time	Clears intermediate states of operators such as GroupBy, RegularJoin, Rank, and Depulicate that have not been updated after the maximum retention time. The default value is 1 hour.
   Dirty Data Policy	Policy for processing dirty data. The following policies are supported: Ignore, Trigger a job exception, and Save. If you set this field to Save, the Dirty Data Dump Address must be set. Click the address box to select the OBS path for storing dirty data. This parameter is available only when a DIS data source is used.

8. (Optional) Set the runtime configuration as required. For details about related parameters, seeHow Do I Optimize Performance of a Flink Job?
   Figure 3 Runtime configuration
   

9. Click Save.
10. Click Start. On the displayed Start Flink Jobs page, confirm the job specifications and the price, and click Start Now to start the job.

    After the job is started, the system automatically switches to the Flink Jobs page, and the created job is displayed in the job list. You can view the job status in the Status column. Once a job is successfully submitted, its status changes from Submitting to Running. After the execution is complete, the status changes to Completed.

    If the job status is Submission failed or Running exception, the job fails to submit or run. In this case, you can hover over the status icon in the Status column of the job list to view the error details. You can click to copy these details. Rectify the fault based on the error information and resubmit the job.

    

    Other buttons are as follows:

    • Save As: Save the created job as a new job.
    • Static Stream Graph: Provide the static concurrency estimation function and stream graph display function. See Figure 5.
    • Simplified Stream Graph: Display the data processing flow from the source to the sink. See Figure 4.
    • Format: Format the SQL statements in the editing box.
    • Set as Template: Set the created SQL statements as a job template.
    • Theme Settings: Set the theme related parameters, including Font Size, Wrap, and Page Style.
    • Help: Redirect to the help center to provide you with the SQL syntax for stream jobs.

Simplified Stream Graph

On the OpenSource SQL job editing page, click Simplified Stream Graph.

Simplified stream graph viewing is only supported in Flink 1.12 and Flink 1.10.

Figure 4 Simplified stream graph

Static Stream Graph

On the OpenSource SQL job editing page, click Static Stream Graph.

• Simplified stream graph viewing is only supported in Flink 1.12 and Flink 1.10.
• If you use a UDF in a Flink OpenSource SQL job, it is not possible to generate a static stream graph.

The Static Stream Graph page also allows you to:

• Estimate concurrencies. Click Estimate Concurrencies on the Static Stream Graph page to estimate concurrencies. Click Restore Initial Value to restore the initial value after concurrency estimation.
• Zoom in or out the page.
• Expand or merge operator chains.
• You can edit Parallelism, Output rate, and Rate factor.
  • Parallelism: indicates the number of concurrent tasks.
  • Output rate: indicates the data traffic of an operator. The unit is piece/s.
  • Rate factor: indicates the retention rate after data is processed by operators. Rate factor = Data output volume of an operator/Data input volume of the operator (Unit: %)

Figure 5 Static stream graph