MySQL: Update all Columns With Values From A Separate Table
Tag : mysql , By : Gabriel
Date : March 29 2020, 07:55 AM
Hope this helps The below UPDATES if there is no PK duplication and INSERTs is there is: REPLACE INTO table2(field1, field2, field3)
SELECT field1, field2,field3 FROM table1
WHERE id=1;
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Select from table where date and time values are in separate columns
Tag : mysql , By : Carlos Galdino
Date : March 29 2020, 07:55 AM
it should still fix some issue I have a dateColumn with value "2014-10-10" and startTimeColumn with value "10:10:44". How can I select everything from the table where dateColumn is between 'startDate' and 'endDate', and where the startTimeColumn is greater than or equal to 'startTime' on the 'startDate'? , Combine the date and time columns SELECT * FROM table1
WHERE timestamp(dateColumn, startTimeColumn) BETWEEN 'startDateAndTime'
AND 'endDateAndTime'
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Multi-JOIN - Have separate columns which reference same table, but have different values
Tag : mysql , By : John Miller
Date : March 29 2020, 07:55 AM
Does that help You want to join the type table one more time and this time with deck table. Try this: SELECT
A.name 'account name',
D.name 'deck name owned by account',
T2.name 'type name of the DECK',
C.name 'card name contained in deck',
T.name 'type name of the CARD'
FROM account A
JOIN deck D ON A.id=D.owner
JOIN deck_card DC ON D.id=DC.deck
JOIN card C ON DC.card=C.id
JOIN `type` T ON C.`type`=T.id
JOIN `type` T2 ON D.`type`=T2.id
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There are 2 tuples for same ID in an table and the values of some other columns for those two rows are different
Date : March 29 2020, 07:55 AM
it should still fix some issue I have used the below query : , You could filter unwanted records with a not exists condition: select distinct e.case_id, e.case_name, s.script_name, s.script_type, e.Result
from executions_table e
left outer join scripts_table s on s.case_id = e.case_id
where
e.case_id like '11%'
and (
s.script_type = 'Automation'
or not exists (
select 1
from scripts_table s1
where
s1.case_id = s.case_id
and s1.script_name <> s.script_name
and s1.script_type = 'Automation'
)
)
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R: Iteratively extract not NA values for columns in a data table and split into separate columns without typing column n
Date : March 29 2020, 07:55 AM
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