Working with Presto: Unpivoting a Query to Get Column Names Based on Condition

Presto is an open-source distributed SQL query language that allows users to execute queries on large datasets stored in various data sources. In this article, we will explore how to unpivot a query in Presto to get column names based on a condition.

Introduction to Presto and Unpivoting

Unpivoting is a process of transforming a data set from wide format to long format or vice versa. In the context of Presto, unpivoting involves using various functions such as unnest(), array_agg(), and cross join to transform the data.

Presto’s unnest() function is used to expand an array into a table. This can be useful when you want to perform operations on individual elements of an array in your query.

Understanding the Problem

The problem presented in the Stack Overflow post is about selecting column names from a result set where each column has a null value count. The current query returns a concatenated string with all columns that have non-null values. However, we want to get the column names as separate rows rather than a concatenated string.

Solution Overview

To solve this problem, we will use Presto’s unnest() function along with arrays and cross joins. This approach involves selecting column counts for each column and then unpivoting those results using unnest().

Step 1: Select Column Counts

First, let’s select the count of null values for each column:

select 
    sum(case when Column_1 is null then 1 else 0 end) as Column_1,
    sum(case when Column_2 is null then 1 else 0 end) as Column_2,
    sum(case when Column_3 is null then 1 else 0 end) as Column_3
from TestTable 

Step 2: Unpivoting Using unnest()

Next, we will unpivot the result of sum() using Presto’s unnest() function. This will give us individual column names with their corresponding null counts:

select t2.key
from (
    select 
        sum(case when Column_1 is null then 1 else 0 end) as Column_1,
        sum(case when Column_2 is null then 1 else 0 end) as Column_2,
        sum(case when Column_3 is null then 1 else 0 end) as Column_3
    from TestTable 
) t1
cross join unnest(
    array['Column1', 'Column_2', 'Column_3'],
    array[Column_1, Column_2, Column_3]
) t2 (key, value)
where t2.value = 0

Explanation of unnest()

In the above query, unnest() is used in two ways:

• First, it takes an array of column names and converts them into individual rows. This results in a table with three columns: Column1, Column_2, and Column_3.

• Second, it also takes an array of arrays where each inner array contains the actual values for the corresponding column.

Cross Joining

We use cross join to combine the two arrays created by unnest(). The outer array is used to get the individual column names while the inner array is used to get their corresponding counts.

Filtering Null Values

The final step is filtering out rows where the value equals 0. This will give us only the columns with null values.

Example Use Cases

Unpivoting can be useful in various scenarios such as:

• Data Analysis: When working with pivot tables or aggregating data, unpivoting can help you get individual column names based on a condition.
• Data Visualization: In data visualization tools like Tableau or Power BI, unpivoting is often used to transform data from wide format to long format.
• Reporting and Analytics: Unpivoting can be helpful when creating reports that need to display specific columns based on certain conditions.

Conclusion

In this article, we explored how to unpivot a query in Presto to get column names based on a condition. By using unnest() along with arrays and cross joins, you can transform your data into the desired format for analysis or visualization. This approach is particularly useful when dealing with pivot tables or aggregating data where individual column names need to be extracted.

Note: The example SQL query provided in this article uses array and unnest functions available in Presto 0.14 and above. If you are using an older version of Presto, some features might not be available.

Last modified on 2024-04-29