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Room: DAO query that removes duplicates given multiple columns as criteria


Room: DAO query that removes duplicates given multiple columns as criteria

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Room: DAO query that removes duplicates given multiple columns as criteria
Tag : android , By : snapshooter
Date : November 28 2020, 04:01 AM

I think the issue was by ths following , Assuming we are using Room and have a DAO which implements our interactions with an SQLite table. Is there a way to construct a query that can identify one or more columns that have the same value, i.e. considered duplicates, and remove them? , Try creating the following Query in your DAO interface:
@Dao
public interface MyDaoTest {

    ...

    @Query("DELETE FROM test
            WHERE id NOT IN (SELECT MIN(id) FROM test GROUP BY name, lastName)")
    void deleteDuplicates();

    ...
}
SELECT MIN(id)
FROM test
GROUP BY name, lastName;
DELETE
FROM test
WHERE id NOT IN
(SELECT MIN(id)
FROM test
GROUP BY name, lastName);

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How to Query Function Google Spreadsheet - Data filtering based on multiple criteria (multiple columns to check at once)


Tag : development , By : Brian
Date : March 29 2020, 07:55 AM
I wish did fix the issue. It's just a matter of quotes. Try this, with single quotes around the name 'AL':
=QUERY(TaksRecords!A2:I17; "select A, B, C, D, E, F, H, I where G='AL'"; 1)

Access 2010 - Query Multiple Table Columns in one Query field to create a list based upon a specific criteria


Tag : sql , By : Rb.Ridge
Date : March 29 2020, 07:55 AM
To fix this issue Ah ok. It's actually your where clause that is causing this. If you need to treat each skill individually, for purposes of filtering the query and pulling back people, you're going to need to change all those ANDs to ORs in your where clause. Basically, that where clause says "only give me people who have anything but zero in ALL columns"
Try this:
SELECT  tblWorkArea.ID_LaborCore ,
        tblWorkArea.[Labor Core] ,
        tblWorkArea.Position ,
        tblSkills.[Reading Schematics] ,
        tblSkills.Wiring ,
        tblSkills.[Wire Type] ,
        tblSkills.[Terminal Types] ,
        tblSkills.[NEMA Ratings] ,
        tblSkills.[UL 508] ,
        tblSkills.[Attention to Detail] ,
        tblSkills.[Lifting 50lbs] ,
        tblSkills.[Knowledge of Procedure] ,
        tblSkills.Crimper ,
        tblSkills.[Heat Gun] ,
        tblSkills.Screwdriver ,
        tblSkills.Stripper ,
        tblSkills.[Impact Drill] ,
        tblSkills.[Radial Saw] ,
        tblSkills.Multimeter ,
        tblSkills.[Torque Screwdriver/Wrench] ,
        tblSkills.[Tape Measure] ,
        tblSkills.Vacuum ,
        tblSkills.[Drill Press] ,
        tblSkills.[Jig Saw] ,
        tblSkills.[Troubleshooting Components] ,
        tblSkills.[Problem Solving] ,
        tblSkills.Organization ,
        tblSkills.[Large Panel] ,
        tblSkills.[Test Procedures] ,
        tblSkills.[Functional Testing] ,
        tblSkills.[Writing Test Procedures] ,
        tblSkills.[Material Management] ,
        tblSkills.[Set Meter Ability] ,
        tblSkills.[Tone Generator] ,
        tblSkills.[Megger Testing] ,
        tblSkills.[Network Tracer] ,
        tblSkills.Components ,
        tblSkills.Fuses ,
        tblSkills.[Heat Shrink Color Codes] ,
        tblSkills.[Proper Lug or Crimping] ,
        tblSkills.[Resistors Knowledge] ,
        tblSkills.Oscilloscopes ,
        tblSkills.Waveforms ,
        tblSkills.[Voltage Separation] ,
        tblSkills.[Skill x_Stapling]
FROM    ( tblWorkArea
          INNER JOIN tblPosition ON tblWorkArea.Position = tblPosition.Postion
        )
        INNER JOIN tblSkills ON tblWorkArea.ID_LaborCore = tblSkills.ID_LaborCore
WHERE   ( ( ( tblWorkArea.[Labor Core] ) = [Enter labor core] )
          AND ( ( tblWorkArea.Position ) = [Enter Position] )
          AND ( ( ( tblSkills.[Reading Schematics] ) <> 0 )
                OR ( ( tblSkills.Wiring ) <> 0 )
                OR ( ( tblSkills.[Wire Type] ) <> 0 )
                OR ( ( tblSkills.[Terminal Types] ) <> 0 )
                OR ( ( tblSkills.[NEMA Ratings] ) <> 0 )
                OR ( ( tblSkills.[UL 508] ) <> 0 )
                OR ( ( tblSkills.[Attention to Detail] ) <> 0 )
                OR ( ( tblSkills.[Lifting 50lbs] ) <> 0 )
                OR ( ( tblSkills.[Knowledge of Procedure] ) <> 0 )
                OR ( ( tblSkills.Crimper ) <> 0 )
                OR ( ( tblSkills.[Heat Gun] ) <> 0 )
                OR ( ( tblSkills.Screwdriver ) <> 0 )
                OR ( ( tblSkills.Stripper ) <> 0 )
                OR ( ( tblSkills.[Impact Drill] ) <> 0 )
                OR ( ( tblSkills.[Radial Saw] ) <> 0 )
                OR ( ( tblSkills.Multimeter ) <> 0 )
                OR ( ( tblSkills.[Torque Screwdriver/Wrench] ) <> 0 )
                OR ( ( tblSkills.[Tape Measure] ) <> 0 )
                OR ( ( tblSkills.Vacuum ) <> 0 )
                OR ( ( tblSkills.[Drill Press] ) <> 0 )
                OR ( ( tblSkills.[Jig Saw] ) <> 0 )
                OR ( ( tblSkills.[Troubleshooting Components] ) <> 0 )
                OR ( ( tblSkills.[Problem Solving] ) <> 0 )
                OR ( ( tblSkills.Organization ) <> 0 )
                OR ( ( tblSkills.[Large Panel] ) <> 0 )
                OR ( ( tblSkills.[Test Procedures] ) <> 0 )
                OR ( ( tblSkills.[Functional Testing] ) <> 0 )
                OR ( ( tblSkills.[Writing Test Procedures] ) <> 0 )
                OR ( ( tblSkills.[Material Management] ) <> 0 )
                OR ( ( tblSkills.[Set Meter Ability] ) <> 0 )
                OR ( ( tblSkills.[Tone Generator] ) <> 0 )
                OR ( ( tblSkills.[Megger Testing] ) <> 0 )
                OR ( ( tblSkills.[Network Tracer] ) <> 0 )
                OR ( ( tblSkills.Components ) <> 0 )
                OR ( ( tblSkills.Fuses ) <> 0 )
                OR ( ( tblSkills.[Heat Shrink Color Codes] ) <> 0 )
                OR ( ( tblSkills.[Proper Lug or Crimping] ) <> 0 )
                OR ( ( tblSkills.[Resistors Knowledge] ) <> 0 )
                OR ( ( tblSkills.Oscilloscopes ) <> 0 )
                OR ( ( tblSkills.Waveforms ) <> 0 )
                OR ( ( tblSkills.[Voltage Separation] ) <> 0 )
                OR ( ( tblSkills.[Skill x_Stapling] ) <> 0 )
              )
        )

How do I bulk or batch update multiple fields or columns with multiple conditions or criteria with a single mysql query


Tag : mysql , By : hammer_1968
Date : March 29 2020, 07:55 AM
I wish this helpful for you Here is what ended up working. I needed to change the purl name in the second SET CASEs to what it was changing to, not to the original name. So that kind of answers that side question whether it does it column at a time or row at a time.
UPDATE localhost_campaigns.list_data 
SET purl = CASE purl 
WHEN 'temp_dingo' THEN 'dingo' 
WHEN 'temp_wombat' THEN 'wombat' 
WHEN 'temp_platypus' THEN 'platypus' 
WHEN 'temp_koala' THEN 'koala' 
END, 
purl_full = CASE purl 
WHEN 'dingo' THEN 'http://dingo.domain.com' 
WHEN 'wombat' THEN 'http://wombat.domain.com' 
WHEN 'platypus' THEN 'http://platypus.domain.com' 
WHEN 'koala' THEN 'http://koala.domain.com' 
END 
WHERE (purl IN ('temp_dingo', 'temp_wombat', 'temp_platypus', 'temp_koala') AND cid = 2050);

How can I delete duplicates group 3 columns using two criteria (first two columns)?


Tag : python-3.x , By : adbanginwar
Date : March 29 2020, 07:55 AM
wish help you to fix your issue I believe need drop_duplicates:
df = df.drop_duplicates(['Year created', 'Week created'])
print (df)
   Year created  Week created  SUM_New  SUM_Closed  SUM_Open
0          2018             1       17           0        82
1          2018             6       62          47        18

Remove duplicates based on criteria in multiple columns across two data frames


Tag : r , By : appdelivery
Date : March 29 2020, 07:55 AM
I wish this helpful for you You can do this using an inner join with sqldf
Example data . Please provide this yourself in the future.
df1 <- data.frame(a = 1:10, b = 1:10, c = 1:10, g = tail(letters, 10))
set.seed(2019)
df2 <- as.data.frame(lapply(df1, function(x) sample(x, replace = TRUE)))
library(sqldf)
sqldf("
select  a.*
from    df1 a
        join df2 b      
          on  (a.a = b.a or a.b = b.b)
              and a.c = b.c
where   b.g <> 'y'
")

#   a b c g
# 1 2 2 2 r
# 2 1 1 1 q
# 3 5 5 5 u
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