Query to Divide Data: Understanding Quarters and Activity

As data analysts, we often encounter complex datasets that require us to extract insights from large amounts of information. One such problem involves dividing data into quarters based on a specific month ID column and calculating activity levels for each quarter. In this article, we’ll delve into the world of Hive queries and explore how to achieve this using a combination of hierarchical queries, self-joins, and clever use of Hive functions.

Understanding Quarters

Before we dive into the query, let’s understand what quarters mean in the context of month IDs. Typically, a year is divided into four quarters:

1st quarter: January to March
2nd quarter: April to June
3rd quarter: July to September
4th quarter: October to December

To calculate activity levels for each quarter, we need to determine which month IDs fall within each quarter.

Query Approach

The provided Hive query uses a combination of self-joins, Hive functions, and clever logic to achieve this. Let’s break down the query step by step:

1. Creating a Temporary Table for Quarters

CREATE TABLE qtrs (
    month INT
);

INSERT INTO qtrs VALUES (1), (2), (3), (4);

This creates a temporary table qtrs with four rows, each representing a quarter of the year.

2. Joining Patient IDs with Quarters

SELECT DISTINCT NVL(ims.id, qtr.id) as patient_id,
       qtr.year as year,
       qtr.month as month,
       CASE WHEN ims.id > 0 THEN 1 ELSE 0 END as activity  
FROM sandbox_grwi.ims_patient_activity_diagnosis ims
RIGHT JOIN (SELECT distinct ims.id,YEAR(ims.month_dt) as year,qtrs.month from sandbox_grwi.ims_patient_activity_diagnosis ims join dbo.qtrs qtrs) qtr 
ON (ims.id=qtr.id and YEAR(ims.month_dt)=qtr.year and INT((MONTH(month_dt)-1)/3)+1=qtr.month)
ORDER BY patient_id, year, month;

This joins the ims_patient_activity_diagnosis table with the temporary qtrs table on multiple conditions:

ims.id matches qtr.id
YEAR(ims.month_dt) equals qtr.year
The month ID in ims Patient Activity Diagnosis falls within a specific quarter based on (MONTH(month_dt)-1)/3+1

The NVL function is used to assign the id column from either ims or qtrs, ensuring that we always get a value for each patient ID.

3. Calculating Activity Levels

SELECT DISTINCT NVL(ims.id, qtr.id) as patient_id,
       qtr.year as year,
       qtr.month as month,
       CASE WHEN ims.id > 0 THEN 1 ELSE 0 END as activity  
FROM sandbox_grwi.ims_patient_activity_diagnosis ims
RIGHT JOIN (SELECT distinct ims.id,YEAR(ims.month_dt) as year,qtrs.month from sandbox_grwi.ims_patient_activity_diagnosis ims join dbo.qtrs qtrs) qtr 
ON (ims.id=qtr.id and YEAR(ims.month_dt)=qtr.year and INT((MONTH(month_dt)-1)/3)+1=qtr.month)
ORDER BY patient_id, year, month;

This is where the magic happens! The CASE statement calculates activity levels based on whether an ID exists in a quarter or not:

If an ID has activities for a specific quarter (ims.id > 0), set the activity level to 1.
Otherwise, set the activity level to 0.

Sample Data and Results

To test this query, additional sample data is inserted into the sandbox_grwi.ims_patient_activity_diagnosis table:

INSERT INTO sandbox_grwi.ims_patient_activity_diagnosis values
(200, '2012-03-01'), 
(200, '2013-04-01');

The final result set includes patient IDs, years, months, and activity levels for each quarter:

p_id    year    month   activity
100     2012    1       1
100     2012    2       0
100     2012    3       0
100     2012    4       0
...
200     2012    1       1
200     2012    2       0
200     2012    3       0
200     2012    4       0

This concludes our journey into dividing data into quarters and calculating activity levels. By leveraging Hive queries, temporary tables, and clever logic, we can extract valuable insights from large datasets.

Takeaways

Divide data into quarters using month IDs.
Use Hive functions to calculate activity levels for each quarter.
Employ self-joins to combine multiple conditions in a single query.
Leverage NVL and CASE statements to handle missing values and logical calculations.

Last modified on 2024-12-12