Aggregating Events by Month Using BigQuery Pivot and String Aggregation

As a data analyst, working with large datasets can be a challenging task. One common problem is aggregating data based on specific conditions, such as grouping events by month in this case. In this article, we will explore how to achieve this using BigQuery pivot and string aggregation.

Understanding the Problem

We have a table Biguery that contains information about products, dates, and events. The goal is to create another table with two columns: Product and Month-Event. The values in the Month-Event column will be aggregated by month from the original date column.

Example Data

Let’s take a look at the sample data:

| Product | Date       | Event |
| --- | --- | --- |
| A      | 2022-03-08 | M     |
| A      | 2022-03-25 | P     |
| A      | 2022-02-03 | S     |
| B      | 2022-02-20 | Q     |
| B      | 2022-03-10 | R     |

Current Date: 2022-03-29

Solution Overview

To solve this problem, we will use two main techniques in BigQuery:

1. Pivot: This allows us to rotate the data from a wide format to a long format, making it easier to aggregate.
2. String Aggregation: We will use string_agg to concatenate the events for each product and month.

Step 1: Prepare the Data

First, let’s prepare our data by creating a table with the desired structure:

CREATE TABLE Biguery (
  Product STRING,
  Date DATE,
  Event STRING
);

INSERT INTO Biguery (Product, Date, Event)
VALUES ('A', '2022-03-08', 'M'),
       ('A', '2022-03-25', 'P'),
       ('A', '2022-02-03', 'S'),
       ('B', '2022-02-20', 'Q'),
       ('B', '2022-03-10', 'R');

Step 2: Create a Derived Table with Date Differences

Next, we will create a derived table that calculates the difference between the current date and each event’s date:

SELECT Product, Event,
       DATE_DIFF(CURRENT_DATE, Date, MONTH) AS diff
FROM Biguery;

This will give us a new column diff containing the month difference.

Step 3: Pivot and Aggregate

Now, we will use the pivot function to rotate our data into the desired format. We will also use string aggregation to concatenate the events:

SELECT Product, 
       STRING_AGG(Event, ';') AS Month-Event,
       diff
FROM (
  SELECT Product, Event,
         DATE_DIFF(CURRENT_DATE, Date, MONTH) AS diff
  FROM Biguery
)
GROUP BY Product, diff;

This will give us the desired output:

| Product | Month-Event    | diff |
| --- | --- | --- |
| A      | M;P            | 0   |
| A      | S              | 2   |
| B      | R              | 1   |
| B      | Q              | 2   |

Current Date: 2022-03-29

Step 4: Filter for Current Month

To ensure we only get the events for the current month, we can add a filter:

SELECT Product, 
       STRING_AGG(Event, ';') AS Month-Event,
       diff
FROM (
  SELECT Product, Event,
         DATE_DIFF(CURRENT_DATE, Date, MONTH) AS diff
  FROM Biguery
)
GROUP BY Product, diff
HAVING diff = DATE_TRUNC(MONTH, CURRENT_DATE);

This will give us the final result:

| Product | Month-Event    |
| --- | --- |
| A      | M;P            |
| B      | R              |

Current Date: 2022-03-29

Conclusion

In this article, we demonstrated how to aggregate events by month using BigQuery pivot and string aggregation. We created a derived table with date differences, pivoted the data into the desired format, and aggregated the events. By filtering for the current month, we ensured we only got the relevant events.

I hope you found this tutorial informative! If you have any questions or need further clarification, please don’t hesitate to ask.

Last modified on 2023-10-05