3/20/2023 0 Comments Redshift window functions![]() ![]() If you have to build analytics for multiple mutually exclusive use cases, prepare a separate table for each use case.Ĭhoose the best distribution style.Those columns are typically mapped to attributes that are most frequently used for aggregations in insights. Use the columns that are most frequently used for JOIN and aggregation operations.Because Amazon Redshift is a columnar database, queries read only the required columns and each column is compressed separately. If your database holds a large amount of data, consider the following practices:ĭenormalize the relational data model of your database. Window functions (running aggregations like RUNSUM, RUNMAX or RUNVARP) with unbounded beginning of frames.Period-over-period comparison with periodical date granularity (for example HourInDay or DayOfWeek).GoodData.CN does not support the following features: GoodData Cloud Native (GoodData.CN) uses the driver with version 1. If you use native authentication inside your cloud platform (for example, Google Cloud Platform, Amazon Web Services, or Microsoft Azure), you do not have to provide the username and password. The JDBC URL must be in the following format:īasic authentication is supported. Hopefully having both of these queries posted will help other fix correlated subquery errors.Use the following information when creating a data source for your Amazon Redshift database: Needing to make a data segment that had all the possible Max(version) for all possible week_of values was the key. JOIN dates ON f2.last_update <= dates.week_of JOIN (SELECT MAX(MAX(version)) OVER(Partition by id, type Order by dates.weeks_of rows unbounded preceding) AS feature_version, This works: WITH dates ASĬOUNT(DISTINCT features.carrier_id) AS total We thought others might be helped by posting the final solution. This was an interesting replacement of a correlated query with a join due to the inequality in the correlated sub query. WHERE features.version = (SELECT MAX(version) JOIN dates ON features.last_update <= dates.week_of 'W' || CEILING(DATE_PART('week',dates.week_of +INTERVAL '1 day')) AS week_number, SELECT (DATE_TRUNC('week',getdate () +INTERVAL '1 day')::DATE- 7*(ROW_NUMBER() OVER (ORDER BY TRUE) - 1) -INTERVAL '1 day')::DATE AS week_ofįROM (SELECT 1 AS X UNION ALL SELECT 1 AS X UNION ALL SELECT 1 AS X UNION ALL SELECT 1 AS X UNION ALL SELECT 1 AS X UNION ALL SELECT 1 AS X UNION ALL SELECT 1 AS X UNION ALL SELECT 1 AS X) As shown in this somewhat modified query: WITH dates AS ![]() Seqnum doesn't exists until the CTE runs but does exist when the result of the CTE is consumed.Īfter moving the where clause AndyP got a correlated subquery error coming from a WHERE clause not included in the posted query. Just move your WHERE clause to the outer SELECT. Something like this you mean? WITH dates AS ( SELECT (date_trunc('week', getdate() + INTERVAL '1 day')::date - 7 * (row_number() over (order by true) - 1) - INTERVAL '1 day')::date AS week_column, If I modify my dates CTE query like this, then it gives me error as window function is not allowed in where clause. Is there any way to avoid using limit 8 in my CTE query and still get same output? Our platform doesn't allow us to run queries if it has limit clause in it so trying to see if I can rewrite it differently in sql redshift? JOIN dates ON features.last_update <= dates.week_columnīelow is the output I get from my inner dates CTE query: SELECT (date_trunc('week', getdate() + INTERVAL '1 day')::date - 7 * (row_number() over (order by true) - 1) - INTERVAL '1 day')::date AS week_column 'W' || ceiling(date_part('week', dates.week_column + INTERVAL '1 day')) AS week_number,ĬOUNT(DISTINCT features.client_id) AS total SELECT (date_trunc('week', getdate() + INTERVAL '1 day')::date - 7 * (row_number() over (order by true) - 1) - INTERVAL '1 day')::date AS week_column I am trying to understand on how to rewrite my dates CTE so that I can avoid using limit 8 query. I have a dates CTE in my below query where I am using limit clause which I don't want to use it. ![]()
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