CODEWITHSUNDEEP
sqlgoogle-bigquerypartitioningrolling-computation
matt_pjlp
matt_pjlp

Reputation: 33

How to apply: count(distinct ...) over (partition by ... order by) in big query?

I currently have this source table.

I am trying to get this second table from the first table, in SQL on GCP BigQuery.

My Query is the following :

        SELECT
            SE.MARKET_ID,
            SE.LOCAL_POS_ID,
            SE.BC_ID,
            LEFT(SE.SALE_CREATION_DATE,6) AS DATE_ID_MONTH,

            COUNT(DISTINCT
                CASE
                    WHEN FLAG
                    THEN SE.CUST_ID
                END)
            OVER (PARTITION BY SE.MARKET_ID, SE.LOCAL_POS_ID, SE.BC_ID, LEFT(SE.SALE_CREATION_DATE,4) ORDER BY LEFT(SE.SALE_CREATION_DATE,6)) AS NB_ACTIVE_CUSTOMERS

        FROM
            SE
        GROUP BY
            SE.MARKET_ID, SE.LOCAL_POS_ID, SE.BC_ID, LEFT(SE.SALE_CREATION_DATE,6)

However, I get this error that I did not succeed to bypass :

Window ORDER BY is not allowed if DISTINCT is specified at [12:107]

I can't create a previous table with the following request :

SELECT DISTINCT
        SE.MARKET_ID,
        SE.LOCAL_POS_ID,
        SE.BC_ID,
        LEFT(SE.SALE_CREATION_DATE,6) AS DATE_ID_MONTH,
        CASE
            WHEN FLAG
            THEN SE.CUST_ID
            ELSE NULL
        END AS VALID_CUST_ID
FROM
        SE

in order to use a dense_rank() after that because I have 50 others indicators (and 500M rows) to add to this table (indicators based on other flags) and I can't obviously create a WITH for each of them, I need to have it in only a few WITH or none (exactly like my current query is supposed to do).

Has anyone got a clue on how I can handle that please ?

Upvotes: 3

Views: 4077

Answers (2)

Mikhail Berlyant
Mikhail Berlyant

Reputation: 173076

Consider below approach

select * except(ids), 
  array_length(array(
    select distinct id
    from unnest(split(ids)) id
  )) as nb_active_customers, 
  format('%t', array(
    select distinct id
    from unnest(split(ids)) id
  )) as distinct_values
from (
  select market_id, local_pos_id, bc_id, date_id_month,
    string_agg('' || ids) over(partition by market_id order by date_id_month) ids
  from (
    select market_id, local_pos_id, bc_id, left(sale_creation_date,6) AS date_id_month,
      string_agg('' || cust_id) ids
    from se
    where flag = 1
    group by market_id, local_pos_id, bc_id, date_id_month
  )
) t

if applied to sample data in your question - output is

enter image description here

Upvotes: 2

shawnt00
shawnt00

Reputation: 17935

I think some of your sample data is incorrect but I did play with it and get a matching result, for the MPE data at least. You can accomplish this by first tagging the "distinctly counted" rows with an extra partition on CUST_ID and then first ordering on FLAG DESC. Then you would sum over that in the same way you hoped to apply count(distinct <expr>) over ...

WITH SE AS (
    SELECT  1 LINE_ID, 'TW' MARKET_ID, 'X' LOCAL_POS_ID, 'MPE' BC_ID,
            1 CUST_ID, '20200201' SALE_CREATION_DATE, 1 FLAG UNION ALL
    SELECT  2, 'TW', 'X', 'MPE', 2, '20201005', 1 UNION ALL
    SELECT  3, 'TW', 'X', 'MPE', 3, '20200415', 0 UNION ALL
    SELECT  4, 'TW', 'X', 'MPE', 1, '20200223', 1 UNION ALL
    SELECT  5, 'TW', 'X', 'MPE', 6, '20200217', 1 UNION ALL
    SELECT  6, 'TW', 'X', 'MPE', 9, '20200715', 1 UNION ALL
    SELECT  7, 'TW', 'X', 'MPE', 4, '20200223', 1 UNION ALL
    SELECT  8, 'TW', 'X', 'MPE', 1, '20201008', 1 UNION ALL
    SELECT  9, 'TW', 'X', 'MPE', 2, '20201019', 1 UNION ALL
    SELECT 10, 'TW', 'X', 'MPE', 1, '20200516', 1 UNION ALL
    SELECT 11, 'TW', 'X', 'MPE', 1, '20200129', 1 UNION ALL
    SELECT 12, 'TW', 'X', 'MPE', 1, '20201007', 1 UNION ALL
    SELECT 13, 'TW', 'X', 'MPE', 2, '20201005', 1 UNION ALL
    SELECT 14, 'TW', 'X', 'MPE', 3, '20200505', 1 UNION ALL
    SELECT 15, 'TW', 'X', 'MPE', 8, '20201103', 1 UNION ALL
    SELECT 16, 'TW', 'X', 'MPE', 9, '20200820', 1
),
DATA AS (
    SELECT *,
        LEFT(SALE_CREATION_DATE, 6) AS SALE_MONTH,
        LEFT(SALE_CREATION_DATE, 4) AS SALE_YEAR,
        CASE ROW_NUMBER() OVER (
            PARTITION BY MARKET_ID, LOCAL_POS_ID, BC_ID,
                         LEFT(SALE_CREATION_DATE, 4), CUST_ID
            ORDER BY FLAG DESC, LEFT(SALE_CREATION_DATE, 6)
        ) WHEN 1 THEN FLAG END AS COUNTER /* assumes possible to have no flagged row */
    FROM SE
)
SELECT MARKET_ID, LOCAL_POS_ID, BC_ID, SALE_MONTH,
    SUM(SUM(COUNTER)) OVER (
            PARTITION BY MARKET_ID, LOCAL_POS_ID, BC_ID, SALE_YEAR
            ORDER BY SALE_MONTH
    ) AS NB_ACTIVE_CUSTOMERS
FROM DATA
GROUP BY MARKET_ID, LOCAL_POS_ID, BC_ID, SALE_YEAR, SALE_MONTH
ORDER BY MARKET_ID, LOCAL_POS_ID, BC_ID, SALE_YEAR, SALE_MONTH

Upvotes: 1

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