I have one problem, where i have one main table one other table. I have in one table (Accidents), attribute named Accident_ID (Values goes like this 1,4,7,10 and so on)
In other table named casualties, i have the same attribute Accident_ID (But values here goes like this 1,2,2, 3,4,4,4,5,6,7,8, 9, 10, 11 and so on). => There are several same ID-s because each Accident can have more Casualties.
The question is how can i delete in table casualties lines, which don't have same ID-s as in table Accidents (So i want to delete lines in table Casualties with ID-s 2,3,5,6,8,9,11 etc) => i have like 100k ID-s so i can't do manually.
Thank you for help.
You don't need PDI to do that. A simple SQL query can solve your problem.
DELETE FROM Casualties WHERE Accident_ID NOT IN (SELECT DISTINCT Accident_ID FROM Accidents)
Use the Merge Diff step. It compares two streams (or tables) and tell the rows which are added, deleted, modified or identical. Then Filter out the rows you do not want.
Related
I am looking for a reject link type of solution in a dedup scenario. For example in the following code:
MERGE
temp.many_random t
USING
( SELECT DISTINCT * FROM temp.many_random WHERE d=CURRENT_DATE() )
ON FALSE
WHEN NOT MATCHED
BY SOURCE AND d=CURRENT_DATE() THEN DELETE
WHEN NOT MATCHED BY TARGET THEN INSERT ROW
Can I replace THEN DELETE with something like INSERT INTO TABLE (different than the compare tables) so that we can capture these rejects and troubleshoot for pipeline analysis?
If I understand the problem, you want the result of a MERGE query to write to 2 different tables.
Since MERGE can't do that, I'll suggest to write 2 queries:
One that does whatever the primary query is doing.
A second almost identical one, but that writes the wrong records to a different table.
I've 250+ columns in customer table. As per my process, there should be only one row per customer however I've found few customers who are having more than one entry in the table
After running distinct on entire table for that customer it still returns two rows for me. I suspect one of column may be suffixed with space / junk from source tables resulting two rows of same information.
select distinct * from ( select * from customer_table where custoemr = '123' ) a;
Above query returns two rows. If you see with naked eye to results there is not difference in any of column.
I can identify which column is causing duplicates if I run query every time for each column with distinct but thinking that would be very manual task for 250+ columns.
This sounds like very dumb question but kind of stuck here. Please suggest if you have any better way to identify this, thank you.
Solving this one-time issue with sql is too much effort. Simply copy-paste to excel, transpose data into columns and use some simple function like "if a==b then 1 else 0".
I have a table people with less than 100,000 records and I have taken a backup of this table using the following:
create table people_backup as select * from people
I add some new records to my people table over time, but eventually I want to merge the records from my backup table into people. Unfortunately I cannot simply DROP my table as my new records will be lost!
So I want to update the records in my people table using the records from people_backup, based on their primary key id and I have found 2 ways to do this:
MERGE the tables together
use some sort of fancy correlated update
Great! However, both of these methods use SET and make me specify what columns I want to update. Unfortunately I am lazy and the structure of people may change over time and while my CTAS statement doesn't need to be updated, my update/merge script will need changes, which feels like unnecessary work for me.
Is there a way merge entire rows without having to specify columns? I see here that not specifying columns during an INSERT will direct SQL to insert values by order, can the same methodology be applied here, is this safe?
NB: The structure of the table will not change between backups
Given that your table is small, you could simply
DELETE FROM table t
WHERE EXISTS( SELECT 1
FROM backup b
WHERE t.key = b.key );
INSERT INTO table
SELECT *
FROM backup;
That is slow and not particularly elegant (particularly if most of the data from the backup hasn't changed) but assuming the columns in the two tables match, it does allow you to not list out the columns. Personally, I'd much prefer writing out the column names (presumably those don't change all that often) so that I could do an update.
I have an array of 50+ elements that dictates how many hours were worked for a given week.
What is the proper way to store this information into a database table?
My initial idea was to use a delimiter, but the text is too large (280 characters) to fit.
Additionally, there seems something "wrong" with creating a table column for each element.
Ideas?
Array using delimiter (comma):
37.5,37.5,37.5,37.5,37.5,37.5,37.5,37.5,37.5,37.5, ...
The "proper" way is to store the array's contents as multiple rows in a whole other table, each with a foreign key referencing the record they belong to back in the first table. There may be other things that work for you, though.
[EDIT]: From the details you added I'm guessing your array elements consist of a number of hours worked each week and you have 50+ of them because a year has 52-ish weeks. So what I think you're looking for, is I guess that your current (main) table is called something like "employees," is that each row there should have some unique identifier for each employee record. So your new table might be called "work_weeks" and consist of something like employee_id (which matches the employee id in the current table), week_number, and hours_worked.
Seems like a 1 to many relationship. For this example, tableA is the 1 and tableBlammo is the many.
tableA => column blammoId
tableBlammo => column blammoId, column data
One row in tableA joins to multiple rows in tableBlammo via the blammoId column.
Each row in tableBlammo has one element of the array in the data column.
How do delete duplicate records in a DB2 table? I want to be left with a single record for each group of dupes.
Create another table "no_dups" that has exactly the same columns as the table you want to eliminate the duplicates from. (You may want to add an identity column, just to make it easier to identify individual rows).
Insert into "no_dups", select distinct column1, column2...columnN from the original table. The "select distinct" should only bring back one row for every duplicate in the original table. If it doesn't you may have to alter the list of columns or have a closer look at your data, it may look like duplicate data but actually is not.
When step 2 is done, you will have your original table, and "no_dups" will have all the rows without duplicates. At this point you can do any number of things - drop and rename tables, or delete all from the original and insert into the original, select * from no_dups.
If you're running into problems identifying duplicates, and you've added an identity column to "no_dups," you should be able to delete rows one by one using the identity column value.