Typical Application Scenario

Scenario Description

Assume that you need to develop an Impala data analysis application to manage the employee information of an enterprise. Table 1 and Table 2 provide employee information.

Development Guidelines

1. Prepare data.
   1. Create three tables: employee information table employees_info, employee contact table employees_contact, and extended employee information table employees_info_extended.
      • Employee information table employees_info contains fields such as employee ID, name, salary currency, salary, tax category, work place, and hire date. In salary currency, R indicates RMB and D indicates USD.
      • Fields in the employees_contact table include the employee ID, phone number, and email address.
      • Fields in the employees_info_extended table include the employee ID, name, mobile phone number, e-mail address, salary currency, salary, tax category, and work place. The partition field is the hire date.

        For details about table creation codes, see Creating a Table.

   2. Load employee information to employees_info.

      For details about data loading codes, see Loading Data.

      Table 1 provides employee information.

      Table 1 Employee information

      Employee ID	Name	Salary Currency	Salary	Tax Category	Work Place	Hire Date
      1	Wang	R	8000.01	personal income tax&0.05	China:Shenzhen	2014
      3	Tom	D	12000.02	personal income tax&0.09	America:NewYork	2014
      4	Jack	D	24000.03	personal income tax&0.09	America:Manhattan	2014
      6	Linda	D	36000.04	personal income tax&0.09	America:NewYork	2014
      8	Zhang	R	9000.05	personal income tax&0.05	China:Shanghai	2014

   3. Load employee contact information to employees_contact.

      Table 2 provides employee contact information.

      Table 2 Employee contact information

      Employee ID	Phone Number	Email
      1	135 XXXX XXXX	xxxx@xx.com
      3	159 XXXX XXXX	xxxxx@xx.com.cn
      4	186 XXXX XXXX	xxxx@xx.org
      6	189 XXXX XXXX	xxxx@xxx.cn
      8	134 XXXX XXXX	xxxx@xxxx.cn

2. Analyze data.

   For details about data analysis codes, see Querying Data.

   • Query contact information of employees whose salaries are paid in USD.
   • Query the IDs and names of employees who were hired in 2014, and load the query results to the partition with the hire date of 2014 in the employees_info_extended table.
   • Collect the number of records in the employees_info table.
   • Query information about employees whose email addresses end with "cn".

3. Submit a data analysis task to collect the number of records in the employees_info table. For details, see Sample Program Guide.