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Scenario
Procedure
Preparations
Step 1: Upload Data to OBS
Step 2: Create an Elastic Resource Pool and Add Queues to the Pool
Step 3: Create a Database
Step 4: Create a Table
Step 5: Query Data

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Help Center/ Data Lake Insight/ Getting Started/ Using DLI to Submit a SQL Job to Query OBS Data

Using DLI to Submit a SQL Job to Query OBS Data

Updated on 2025-01-10 GMT+08:00

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Scenario

DLI can query data stored in OBS. This section describes how to use DLI to submit a SQL job to query OBS data.

To illustrate, create a new file called sampledata.csv and upload it to an OBS bucket. Then, create an elastic resource pool, create queues within it, and use DLI to create a database and table. Finally, use DLI's SQL editor to query 1,000 data records from the table.

Procedure

Table 1 shows the process for submitting a SQL job to query OBS data.

Complete the preparations in Preparations before performing the following operations.

**Table 1** Procedure for using DLI to submit a SQL job to query OBS data
Procedure	Description
Step 1: Upload Data to OBS	Upload data files to OBS.
Step 2: Create an Elastic Resource Pool and Add Queues to the Pool	Create compute resources required for submitting jobs.
Step 3: Create a Database	DLI metadata forms the foundation for SQL job development. Before executing a job, you need to define databases and tables based on your business scenario.
Step 4: Create a Table	Use the sample data stored in OBS to create tables in the db1 database.
Step 5: Query Data	Use standard SQL statements to query and analyze data.

Preparations

Register a Huawei ID and enable Huawei Cloud services. Make sure your account is not in arrears or frozen.
Configure an agency for DLI.
To use DLI, you need to access services such as Object Storage Service (OBS), Virtual Private Cloud (VPC), and Simple Message Notification (SMN). If it is your first time using DLI, you will need to configure an agency to allow access to these dependent services.
1. Log in to the DLI management console using your account. In the navigation pane on the left, choose Global Configuration > Service Authorization.
2. On the agency settings page, select the agency permissions under Basic Usage, Datasource, and O&M and click Update.
3. View and understand the notes for updating the agency and click OK. The DLI agency permissions are updated.
  Figure 1 Configuring an agency for DLI
4. Once configured, you can check the agency dli_management_agency in the agency list on the IAM console.

Step 1: Upload Data to OBS

Upload data files to OBS.

Log in to the OBS management console.
Create a bucket. In this example, the bucket name is obs1.
1. Click Create Bucket in the upper right corner.
2. On the displayed Create Bucket page, specify Region and enter the Bucket Name. Retain the default values for other parameters or adjust them as needed.
  NOTE:
  
  Select a region that matches the location of the DLI console.
3. Click Create Now.
Click obs1 to access its Objects tab page.
Click Upload Object. In the displayed dialog box, drag a desired file or folder, for example, sampledata.csv to the Upload Object area. Then, click Upload.
You can create a sampledata.txt file, copy the following content separated by commas (,), and save the file as sampledata.csv.
```
product_id,product_name
113,office_13
22,book_2
29,book_9
```
After the file is uploaded successfully, the file path is obs://obs1/sampledata.csv.

For more operations on the OBS console, see the Object Storage Service User Guide.

Step 2: Create an Elastic Resource Pool and Add Queues to the Pool

In this example, the elastic resource pool dli_resource_pool and queue dli_queue_01 are created.

Log in to the DLI management console.
In the navigation pane on the left, choose Resources > Resource Pool.
On the displayed page, click Buy Resource Pool in the upper right corner.

On the displayed page, set the parameters.

In this example, we will buy the resource pool in the CN East-Shanghai2 region. Table 2 describes the parameters.

**Table 2** Parameters
Parameter	Description	Example Value
Region	Select a region where you want to buy the elastic resource pool.	CN East-Shanghai2
Project	Project uniquely preset by the system for each region	Default
Name	Name of the elastic resource pool	dli_resource_pool
Specifications	Specifications of the elastic resource pool	Standard
CU Range	The maximum and minimum CUs allowed for the elastic resource pool	64-64
CIDR Block	CIDR block the elastic resource pool belongs to. If you use an enhanced datasource connection, this CIDR block cannot overlap that of the data source. Once set, this CIDR block cannot be changed.	172.16.0.0/19
Enterprise Project	Select an enterprise project for the elastic resource pool.	default

Click Buy.
Click Submit.
In the elastic resource pool list, locate the pool you just created and click Add Queue in the Operation column.

Set the basic parameters listed below.

**Table 3** Basic parameters for adding a queue
Parameter	Description	Example Value
Name	Name of the queue to add	dli_queue_01
Type	Type of the queue To execute SQL jobs, select For SQL. To execute Flink or Spark jobs, select For general purpose.	_
Engine	SQL queue engine. The options are Spark and HetuEngine.	_
Enterprise Project	Select an enterprise project.	default

Click Next and configure scaling policies for the queue.

Click Create to add a scaling policy with varying priority, period, minimum CUs, and maximum CUs.

Figure 2 shows the scaling policy configured in this example.

Figure 2 Configuring a scaling policy when adding a queue
Click to enlarge

**Table 4** Scaling policy parameters
Parameter	Description	Example Value
Priority	Priority of the scaling policy in the current elastic resource pool. A larger value indicates a higher priority. In this example, only one scaling policy is configured, so its priority is set to 1 by default.	1
Period	The first scaling policy is the default policy, and its Period parameter configuration cannot be deleted or modified. The period for the scaling policy is from 00 to 24.	00–24
Min CU	Minimum number of CUs allowed by the scaling policy	16
Max CU	Maximum number of CUs allowed by the scaling policy	64

Click OK.

Step 3: Create a Database

Before querying data, create a database, for example, db1.

NOTE:

The default database is a built-in database. You cannot create the default. database.

In the left navigation pane of the DLI management console, choose SQL Editor.
In the editing window on the right of the SQL Editor page, enter the following SQL statement and click Execute. Read and agree to the privacy agreement, and click OK.
```
create database db1;
```
After the database is successfully created, click in the middle pane to refresh the database list. The new database db1 is displayed in the list.

NOTE:

When you execute a query on the DLI management console for the first time, you need to read the privacy agreement. You can perform operations only after you agree to the agreement. For later queries, you will not need to read the privacy agreement again.

Step 4: Create a Table

After database db1 is created, create a table (for example, table1) containing data in the sample file obs://obs1/sampledata.csv stored on OBS in db1.

In the SQL editing window of the SQL Editor page, select the default queue and database db1.
Enter the following SQL statement in the job editor window and click Execute:
```
create table table1 (product_id int, product_name string) using csv options (path 'obs://obs1');
```
When creating a table, you only need to specify the OBS storage path where the data file is located, without specifying the file name at the end of the directory.

After the table is successfully created, click the Databases tab then db1. The created table table1 is displayed in the table list.

Step 5: Query Data

After performing the preceding steps, you can start querying data.

In the Table tab on the SQL Editor page, double-click the created table table1. The SQL statement is automatically displayed in the SQL job editing window in the right pane. Run following statement to query 1,000 records in the table1 table:
```
select * from db1.table1 limit 1000;
```
Click Execute. The system starts the query.
After the SQL statement is successfully executed or fails to be executed, you can view the query result on the View Result tab under the SQL job editing window.