How to ignore nulls in BigQuery using LAG()?

When using LAG() (in BigQuery standard SQL), how do you skip NULL values so that it takes the first preceding value which is not NULL?

I've prepared some sample rows in the same format in the source table, but obfuscated. In the example, it only works for rows that do not have a preceding NULL value. Specifically, rows 3 & 4 should be assigned '2017-01-25 04:02:36' (as was the case for row 5), but they are NULL.

This makes sense. However, surely there is an easy way to do specify something like INGORE_NULLS?

--TEMP
with example as (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 03:19:50') as col_c, 'val_1' as col_d 
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 03:19:50') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 03:19:50') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:23') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:23') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:23') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:59') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:59') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:59') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:36') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:36') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:36') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:55') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:55') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 07:16:58') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 07:16:58') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:35:39') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:35:39') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:46:48') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:46:48') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:46:48') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 10:47:48') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 10:47:48') as col_c, 'val_3' as col_d))
--TEMP
SELECT col_a, col_b, col_c,
  case when val_1_transposed is null then LAG(val_1_transposed) over (order by col_c) else val_1_transposed end as val_1_transposed,
  case when val_2_transposed is null then LAG(val_2_transposed) over (order by col_c) else val_2_transposed end as val_2_transposed,
  case when val_3_transposed is null then LAG(val_3_transposed) over (order by col_c) else val_3_transposed end as val_3_transposed
FROM (
  SELECT col_a, col_b, col_c,
    MAX(IF(col_d = 'val_1', col_c, NULL)) AS val_1_transposed,
    MAX(IF(col_d = 'val_2', col_c, NULL)) AS val_2_transposed,
    MAX(IF(col_d = 'val_3', col_c, NULL)) AS val_3_transposed
  FROM (
    SELECT col_a, col_b, col_c, col_d FROM example) GROUP BY 1,2,3) ORDER BY col_c DESC

Solution

There are two solutions, described in detail here: http://sqlmag.com/t-sql/last-non-null-puzzle

I adapted one of the solutions, basically it uses a MAX window aggregate function to return the maximum relevant id so far. By using ROWS UNBOUNDED PRECEDING you can constantly reach new MAX levels, than are carried over and replace the NULL lag entries.

--TEMP
with example as (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 03:19:50') as col_c, 'val_1' as col_d 
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 03:19:50') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 03:19:50') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:23') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:23') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:23') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:59') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:59') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:01:59') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:36') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:36') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:36') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:55') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 04:02:55') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 07:16:58') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 07:16:58') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:35:39') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:35:39') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:46:48') as col_c, 'val_1' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:46:48') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 09:46:48') as col_c, 'val_3' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 10:47:48') as col_c, 'val_2' as col_d)
UNION ALL (select 'some_id' as col_a, 'foo' as col_b, timestamp('2017-01-25 10:47:48') as col_c, 'val_3' as col_d))
--TEMP
SELECT col_a, col_b, col_c,
  case when val_1_transposed is null then LAG(val_1_transposed) over (order by col_c) else val_1_transposed end as val_1_transposed,
  case when val_2_transposed is null then LAG(val_2_transposed) over (order by col_c) else val_2_transposed end as val_2_transposed,
  case when val_3_transposed is null then LAG(val_3_transposed) over (order by col_c) else val_3_transposed end as val_3_transposed,
  MAX(val_2_transposed) OVER( PARTITION BY grp ORDER BY col_a ROWS UNBOUNDED PRECEDING ) as lag_ignored_nulls
FROM (
select *, 
  MAX(CASE WHEN val_2_transposed IS NOT NULL THEN col_a END ) OVER( ORDER BY col_a ROWS UNBOUNDED PRECEDING ) AS grp
            from (
  SELECT col_a, col_b, col_c,
    MAX(IF(col_d = 'val_1', col_c, NULL)) AS val_1_transposed,
    MAX(IF(col_d = 'val_2', col_c, NULL)) AS val_2_transposed,
    MAX(IF(col_d = 'val_3', col_c, NULL)) AS val_3_transposed
  FROM (
    SELECT col_a, col_b, col_c, col_d FROM example) GROUP BY 1,2,3)) ORDER BY col_c DESC