Google BigQuery - Execute dynamically generated queries from a select statement - google-cloud-platform

Question

Have a huge table in Google BigQuery with following structure (> 100 million rows):
name | departments
abc | 1,2,5,6
xyz | 4,5
pqr | 3,4,6
Want to convert the data into following format:
name | 1 | 2 | 3 | 4 | 5 | 6
abc | 1 | 1 | | | 1 | 1
xyz | | | | 1 | 1 |
pqr | | | 1 | 1 | | 1
As of now, able to generate the queries required to prepare the dataset in this format by using CONCAT and REGEX_REPLACE functions:
SELECT ' insert into dataset.output ( name, ' +
CONCAT(
'_' , replace(departments,',',',_') )
+ ' ) values( \'' + name +'\','+ REGEXP_REPLACE(departments, "([^,\n]+)", "1") +')'
FROM (
select name, departments from dataset.input )
This generates the output with the 100 M insert queries which can be used to create the data in the required structure.
However, now below are my questions:
Can we execute the output of this query (100 M insert queries) directly by using Big Query SQL or we would need to fire each insert one by one?
I believe there is no way to pivoting or transposing the data in a column with multiple comma separated values. Is that right?
Is there a more optimal way of achieving this using BigQuery SQL and not writing custom Java code?
Thanks.

Answer 1

Below example for BigQuery Standard SQL
#standardSQL
WITH `project.dataset.table` AS (
SELECT 'abc' name, '1,2,5,6' departments UNION ALL
SELECT 'xyz', '4,5' UNION ALL
SELECT 'pqr', '3,4,6'
)
SELECT
name,
IF(departments LIKE '%1%', 1, 0) AS d1,
IF(departments LIKE '%2%', 1, 0) AS d2,
IF(departments LIKE '%3%', 1, 0) AS d3,
IF(departments LIKE '%4%', 1, 0) AS d4,
IF(departments LIKE '%5%', 1, 0) AS d5,
IF(departments LIKE '%6%', 1, 0) AS d6
FROM `project.dataset.table`
with result as
Row name d1 d2 d3 d4 d5 d6
1 abc 1 1 0 0 1 1
2 xyz 0 0 0 1 1 0
3 pqr 0 0 1 1 0 1
So you need to run above with destination to whatever new table you prepared
Note, above assumes you have just 6 departments and most important there is no ambiguity in numbers like 1 does not conflict with 10 for example
If you do have such case - you need transform below lines
IF(departments LIKE '%2%', 1, 0) AS d2,
into
IF(CONCAT(',', departments, ',') LIKE '%,2,%', 1, 0) AS d2 ...
And of course, you can use just one simple INSERT statement
INSERT `project.dataset.new_table` (name, d1, d2, d3, d4, d5, d6)
SELECT
name,
IF(departments LIKE '%1%', 1, 0) AS d1,
IF(departments LIKE '%2%', 1, 0) AS d2,
IF(departments LIKE '%3%', 1, 0) AS d3,
IF(departments LIKE '%4%', 1, 0) AS d4,
IF(departments LIKE '%5%', 1, 0) AS d5,
IF(departments LIKE '%6%', 1, 0) AS d6
FROM `project.dataset.table`
So, the final point of all this is:
instead of generating INSERT STATEMENT for each and every row in original table - you should generate simple SELECT statement that does "pivoting"
Update for "extreme" minimizing generated code
See an example:
#standardSQL
CREATE TEMP FUNCTION c(departments STRING, department INT64) AS (
IF(departments LIKE CONCAT('%',CAST(department AS STRING),'%'), 1, 0)
);
WITH `project.dataset.table` AS (
SELECT 'abc' name, '1,2,5,6' departments UNION ALL
SELECT 'xyz', '4,5' UNION ALL
SELECT 'pqr', '3,4,6'
), temp AS (
SELECT name, departments AS d
FROM `project.dataset.table`
)
SELECT
name,
c(d,1)d1,
c(d,2)d2,
c(d,3)d3,
c(d,4)d4,
c(d,5)d5,
c(d,6)d6
FROM temp
as you can see - now each of your 10000 lines will be like c(d,N)dN, with max in length as c(d,10000)d10000, so you have chance to fit into query size limit