Distinct on postgresql11/12/2023 QUALIFY COUNT() OVER (PARTITION BY wallet_transaction. Snowflake: SELECT wallet_transaction.walletId, According to these pages:ĭISTINCT ON and QUALIFY should work in the same way, so I'm not exactly sure why I am having different results? While in Postgres it returns the correct result each time regardless of the size of the result set. This can even happen with a UNIQUE constraint on (walletId, transactionDate) if transactionDate can be NULL, as NULL compares distinct for the purpose of a UNIQUE constraint. For only 400 stations, this query will be massively faster: SELECT s.stationid, l.submittedat, l.levelsensor FROM station s CROSS JOIN LATERAL ( SELECT submittedat, levelsensor FROM stationlogs WHERE stationid s. Snowflake has a completely different storage architecture and may arrive at a different pick. However, when I use the QUALIFY Clause in my query it returns different results from that in Postgres, and each time I run this snowflake for a result set of thousands of records it returns a different answer while if I run it for a few hundreds of records it provides the correct result each time. Postgres typically picks the first row in physical sort order from duplicates. I imagine constraints similar to these is what drives a lot of use for features like DISTINCT ON, where the more “correct” approach might just be to fix your schema.I am trying to use the QUALIFY Clause in Snowflake since it does not support the use of DISTINCT ON as Postgres does. The DISTINCT clause can be used for a single column or for a list of columns. It keeps one row for each group of duplicates. This particular DB is a large component in a generally spaghttified architecture, that lots of stakeholders write to and consume data from, so over the years it’s grown too complex to reliably tolerate simple changes. Removing duplicate rows from a query result set in PostgreSQL can be done using the SELECT statement with the DISTINCT clause. It can be used with or without an ORDER BY clause. That would be all that’s required to bring this schema (or at least this particular portion of it) in line with a normal form. DISTINCT is a PostgreSQL specific keyword used to remove duplicate rows from the result set of a query. It could be solved by adding a row to table A (or creating a new related table), and then adding an update to the code that inserts the transaction logs (or even just with a table trigger - though that’s a bit more spaghetti). In reality there’s other even more trivial solutions to this problem. Which is perhaps a bit of a contrived situation, but it’s absolutely not my first time dealing with it. It’s a bit of a moot point for me in this case though, as I’m not allowed to make any DDL changes to this DB, I just have to produce periodic reports. Postgres typically picks the first row in physical sort order from duplicates. For instance Oracle achieves this with MATERIALIZED VIEW LOGs, which are essentially just transaction logs for the MV. But as per the improvement in PostgreSQL version 15, this can be changed by creating. Other DB engines support a FAST or INCREMENTAL refresh, which can even support queries with aggregates (as long as certain conditions are met). In PostgreSQL, null values were always indexed as distinct values. As this can work on most of the DBMS and this is expected to be faster than group by solution as you are avoiding the grouping functionality. Now, let’s look into a few examples for better understanding. Multi select in general can be executed safely as follows: select distinct from (select col1, col2 from table ) as x. Note: The DISTINCT ON expression must always match the leftmost expression in the ORDER BY clause. You do not want to use the asterisk most of the time. It is good practice to use the ORDER BY clause with the DISTINCT ON(expression) to make the result set in the desired order. You do not want to use the asterisk most of the time. eventlist Table.query.\ distinct (Table.name).\ filterby (filterbyquery).\ filter (queries).\ orderby (Table.name, ()).\ all () This will end up selecting rows 'grouped' by name, having the greatest timestamp value. all () This will end up selecting rows 'grouped' by name, having the greatest timestamp value. So instead of grouping and aggregating just. So refreshing the view just kinda kicks the can down the road a little bit. So instead of grouping and aggregating just. This particular use-case wouldn’t be suited to MVs, because it’s infrequently accessed, and cannot tolerate stale data.
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