How to Pivot Rows into Columns in BigQuery Without Native Pivot Functionality?

Transpose Rows into Columns in BigQuery (Pivot Implementation)

In this BigQuery tutorial, we aim to address a prevalent need for data transformation: converting rows into columns while preserving key-value pairs. This technique, known as pivoting, is widely used in data analysis and reporting. However, unlike conventional database systems that support pivot operations natively, BigQuery currently lacks this functionality.

Pivoting with an Additional Grouping Column

To overcome this limitation, we present a workaround solution that involves an additional column in the input data, which serves to group rows that should be merged into a single row in the output. Here's how the approach works:

Step 1: Construct the Pivot Query

We begin by crafting a query that will generate the actual pivot query. This query dynamically constructs the code necessary to perform the pivoting operation based on the input dataset.

SELECT 'SELECT id, ' + 
   GROUP_CONCAT_UNQUOTED(
      'MAX(IF(key = "' + key + '", value, NULL)) as [' + key + ']'
   ) 
   + ' FROM yourTable GROUP BY id ORDER BY id'
FROM (
  SELECT key 
  FROM yourTable
  GROUP BY key
  ORDER BY key
) 

This query identifies all unique key values in the input data and generates a string that, when executed as a separate query, will perform the pivoting operation.

Step 2: Execute the Generated Pivot Query

The result of the first query is a string that defines the actual pivot query. We simply need to copy this string and run it as a regular BigQuery query. The result will be a transposed dataset with the keys as column names and the values as column values.

Example Input and Output

Consider the following input table:

id	Key	Value
1	channel_title	Mahendra Guru
1	youtube_id	ugEGMG4-MdA
1	channel_id	UCiDKcjKocimAO1tV
1	examId	72975611-4a5e-11e5
1	postId	1189e340-b08f
2	channel_title	Ab Live
2	youtube_id	3TNbtTwLY0U
2	channel_id	UCODeKM_D6JLf8jJt
2	examId	72975611-4a5e-11e5
2	postId	0c3e6590-afeb

The resulting pivoted dataset would appear as follows:

id	channel_id	channel_title	examId	postId	youtube_id
1	UCiDKcjKocimAO1tV	Mahendra Guru	72975611-4a5e-11e5	1189e340-b08f	ugEGMG4-MdA
2	UCODeKM_D6JLf8jJt	Ab Live	72975611-4a5e-11e5	0c3e6590-afeb	3TNbtTwLY0U

Limitations and Alternatives

While this approach effectively mimics pivoting behavior, it comes with limitations. Most notably, BigQuery imposes a limit of 10,000 columns per table, which can hinder pivoting of large datasets with numerous unique keys. In such scenarios, consider exploring alternative solutions such as external pivoting using Python or R or using a federated query approach with a database system that supports pivoting natively.

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