How to simulate a pivot table with BigQuery?

Question

I need to organize the results of a query in columns, as if it was a pivot table. How can I do that?

Answer 1

2020 update: fhoffa.x.pivot()

• https://towardsdatascience.com/easy-pivot-in-bigquery-one-step-5a1f13c6c710

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Use conditional statements to organize the results of a query into rows and columns. In the example below, results from a search for most revised Wikipedia articles that start with the value 'Google' are organized into columns where the revision counts are displayed if they meet various criteria.

SELECT
  page_title,
  /* Populate these columns as True or False, depending on the condition */
  IF(page_title CONTAINS 'search', INTEGER(total), 0) AS search,
  IF(page_title CONTAINS 'Earth' OR page_title CONTAINS 'Maps', INTEGER(total), 0) AS geo,
FROM
  /* Subselect to return top revised Wikipedia articles containing 'Google'
   * followed by additional text.
   */
  (SELECT
    TOP(title, 5) as page_title,
    COUNT(*) as total
   FROM
     [publicdata:samples.wikipedia]
   WHERE
     REGEXP_MATCH (title, r'^Google.+') AND wp_namespace = 0
  );

Result:

+---------------+--------+------+
|  page_title   | search | geo  |
+---------------+--------+------+
| Google search |   4261 |    0 |
| Google Earth  |      0 | 3874 |
| Google Chrome |      0 |    0 |
| Google Maps   |      0 | 2617 |
| Google bomb   |      0 |    0 |
+---------------+--------+------+

A similar example, without using a subquery:

SELECT SensorType, DATE(DTimestamp), AVG(data) avg, 
FROM [data-sensing-lab:io_sensor_data.moscone_io13]
WHERE DATE(DTimestamp) IN ('2013-05-16', '2013-05-17')
GROUP BY 1, 2
ORDER BY 2, 3 DESC;

Generates a 3 column table: sensor type, date, and avg data. To "pivot" and have the dates as columns:

SELECT
  SensorType,
  AVG(IF(DATE(DTimestamp) = '2013-05-16', data, null)) d16,
  AVG(IF(DATE(DTimestamp) = '2013-05-17', data, null)) d17
FROM [data-sensing-lab:io_sensor_data.moscone_io13]
GROUP BY 1
ORDER BY 2 DESC;

Answer 2

Same approach/result, but using BigQuery Standard SQL:

-- top revised Wikipedia articles containing 'Google'
WITH articles AS (
  SELECT title AS page_title,
         COUNT(*) AS total
    FROM `publicdata.samples.wikipedia`
   WHERE REGEXP_CONTAINS(title, r'^Google.+') AND wp_namespace = 0
   GROUP BY title
   ORDER BY total DESC
   LIMIT 5
)

SELECT page_title,
       -- Populate these columns as True or False, depending on the condition
       IF(page_title LIKE '%search%', total, 0) AS search,
       IF(page_title LIKE '%Earth%' OR page_title LIKE '%Maps%', total, 0) AS geo
  FROM articles
;