Introduction
The Japan Population problem on HackerRank is a straightforward exercise that helps you practice using the SUM()
function in SQL. The task is to calculate the total population of all cities in Japan by querying a database table named CITY
. This problem helps you understand how to perform aggregation on specific subsets of data using SQL.
Problem Statement
You are provided with a table named CITY
that contains records for various cities, including their population and the country code. The goal is to calculate the total population of all cities in Japan (where the COUNTRYCODE
is 'JPN'
) using the SQL SUM()
function.
Solution
The SQL query to calculate the total population of all cities in Japan is as follows:
SELECT SUM(POPULATION)
FROM CITY
WHERE COUNTRYCODE = 'JPN';
Explanation
Let's break down the query:
- SUM(POPULATION): The
SUM()
function is an aggregation function that calculates the sum of all the values in the specified column. In this case, we're summing the values in thePOPULATION
column. - FROM CITY: This part of the query specifies the table from which we are retrieving the data. The
CITY
table contains information about different cities, including their populations and country codes. - WHERE COUNTRYCODE = 'JPN': The
WHERE
clause filters the data to include only rows where theCOUNTRYCODE
column is equal to'JPN'
, which corresponds to Japan. This ensures that we are only summing the population of cities in Japan.
Example Test Case
Consider the following sample data from the CITY
table:
+----------------+-------------+------------+ | CITY | POPULATION | COUNTRYCODE| +----------------+-------------+------------+ | Tokyo | 9000000 | JPN | | Osaka | 2700000 | JPN | | Kyoto | 1500000 | JPN | | Sapporo | 2000000 | JPN | | Fukuoka | 1400000 | JPN | +----------------+-------------+------------+
The total population of these cities is:
9000000 + 2700000 + 1500000 + 2000000 + 1400000 = 20,000,000
The query will return 20000000 as the total population of cities in Japan.
Why Use SUM() in This Query?
The SUM()
function is ideal for calculating the total value of a numeric column. In this problem, we are interested in finding the total population of cities in Japan, which is a common use case for the SUM()
function. By using SUM()
, we can efficiently aggregate the population values of all cities that meet the specified condition (COUNTRYCODE = 'JPN'
).
The SUM()
function ensures that you get a single result that represents the total population, which is crucial for business and governmental applications. For example, calculating the total population can help in making decisions related to resource allocation, infrastructure planning, and other important aspects of urban development.
Real-World Use Case
In a real-world scenario, government agencies or international organizations might use SQL queries like this one to analyze demographic data for policy-making or planning purposes. For instance, a government agency could use this query to determine the total population of cities in Japan to allocate resources such as healthcare, transportation, or education funding.
Similarly, businesses operating in Japan could use this data to understand the population distribution across cities. For instance, a retail company may use population data to identify target markets and decide where to open new stores based on the cities with the highest populations.
Complexity Analysis
The time complexity of this query is O(n), where n is the number of rows in the CITY
table. This is because the query needs to scan all the rows in the table to calculate the sum of the population values for cities in Japan. The SUM()
function operates in linear time with respect to the number of rows.
The space complexity is O(1) since the query does not require any additional storage for intermediate results. It only returns a single aggregated value (the total population).
Conclusion
The SUM() function is a simple yet powerful SQL aggregation tool that allows you to calculate the total of a numeric column. In this problem, we used the SUM()
function to calculate the total population of cities in Japan. By applying the WHERE
clause, we filtered the data to include only cities in Japan, and then used SUM()
to aggregate the population values. This technique is widely used in data analysis and can be applied to many real-world scenarios.