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Tag: union

Replace “OR” on 2 indexes with a faster solution (UNION?)

I’m querying shopping-carts in a shop-system, like: I need to query records of c with a column which shows the number of carts which have the same user OR the same email. So I do: This works, but the problem is that the OR is very slow, because MySQL/MariaDB doesn’t use any key in the subquery: Even forcing the index

SQL combining tables to single rows

A problem with combining tables into single rows. TABLE GAMES: ID player1_ID player2_ID des 11 23 68 something 82 34 23 whatever 302 13 34 mmmmmmmm TABLE PLAYERS: ID alias 23 Jeex 34 Jack 68 Jill 13 John The key I start my query with is one of the Player ID’s. I want to show all the games that Player

Hive Union of two queries is giving compile error

I am not sure what is wrong with following hive query. However, it’s throwing error. I am able to run this queries individually. However, facing issues while running with union Error Answer Hive versions prior to 1.2.0 only support UNION ALL Workaround: Use UNION ALL instead of UNION, wrap all into subquery and apply distinct UNION is the same as

How to go convert to CTE

I am a little confused out a CTE works. I need to convert my statement from a rollup with a UNION to a CTE… but the CTE is a bit confusing me. Any Ideas how to approach this? Answer You can express this using a CTE as:

SQL union grouped by rows

Assume I have a table like this: col1 col2 col3 col4 commonrow one two null commonrow null null three How to produce a result to look like this: col1 col2 col3 col4 commonrow one two three Thanks Answer like this, you can group by col1 and get the maximum in each group:

Combining 3 Tables and Finding Average Age in SQL

I need to combine three tables and find the average age after combining the three tables using SQL. The name of the age columns in the three tables are pr16pnk.age, pr16puf.age, and pr16yag.age. I have successfully found the results when the tables are separated, but I am having trouble combining the results. Listed below is the code that I used.

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