Redundant Data in Update Statements

Redundant data in update statements

Due to PostgreSQL MVCC, an UPDATE is effectively much like a DELETE plus an INSERT. With the notable exception of toasted values - see:

• Does Postgres rewrite entire row on update?

(And minor differences for heap only tuples - DELETE + INSERT starts a new HOT chain - but that has no bearing on the case at hand.)

To be precise, the "deleted" row is just invisible to any transaction starting after the delete has been committed, and vacuumed later. Therefore, on the database side, including index manipulation, there is in effect no difference between the two statements. (Exceptions apply, keep reading.) It increases network traffic a bit (depending on your data) and needs a bit of parsing.

I studied HOT updates some more after @araqnid's input and ran some tests. Updates on columns that don't actually change the value make no difference whatsoever as far as HOT updates are concerned. My answer holds. See details below.

This also applies to toasted attributes, since those are also not touched unless the values actually change.

However, if you use per-column triggers (introduced with pg 9.0), this may have undesired side effects!

I quote the manual on triggers:

... a command such as UPDATE ... SET x = x ... will fire a trigger on
column x, even though the column's value did not change.

Bold emphasis mine.

Abstraction layers are for convenience. They are useful for SQL-illiterate developers or if the application needs to be portable between different RDBMS. On the downside, they can butcher performance and introduce additional points of failure. I avoid them wherever possible.

HOT (Heap-only tuple) updates

Heap-Only Tuples were introduced with Postgres 8.3, with important improvements in 8.3.4 and 8.4.9.

The release notes for Postgres 8.3:

UPDATEs and DELETEs leave dead tuples behind, as do failed INSERTs.
Previously only VACUUM could reclaim space taken by dead tuples. With
HOT dead tuple space can be automatically reclaimed at the time of
INSERT or UPDATE if no changes are made to indexed columns. This
allows for more consistent performance. Also, HOT avoids adding
duplicate index entries.

Emphasis mine. And "no changes" includes cases where columns are updated with the same value as they already hold. I actually tested, as I wasn't sure.

Ultimately, the extensive README.HOT in the source code confirms it.

Toasted columns also don't stand in the way of HOT updates. The HOT-updated tuple just links to the same, unchanged tuple(s) in the toast fork of the relation. HOT updates even work with toasted values in the target list (actually changed or not). If toasted values are changed, it entails writes to the toast relation fork, obviously. I tested all of that, too.

Don't take my word for it, see for yourself. Postgres provides a couple of functions to check statistics. Run your UPDATE with and without all columns and check if it makes any difference.

-- Number of rows HOT-updated in table:
SELECT pg_stat_get_tuples_hot_updated('table_name'::regclass::oid)

-- Number of rows HOT-updated in table, in the current transaction:
SELECT pg_stat_get_xact_tuples_hot_updated('table_name'::regclass::oid)

Or use pgAdmin. Select your table and inspect the "Statistics" tab in the main window.

Be aware that HOT updates are only possible when there is room for the new tuple version on the same page of the main relation fork. One simple way to force that condition is to test with a small table that holds only a few rows. Page size is typically 8k, so there must be free space on the page.

Update one of 2 duplicates in an sql server database table

Try This with CTE and PARTITION BY

;WITH cte AS
(
  SELECT
      ROW_NUMBER() OVER(PARTITION BY Column1  ORDER BY Column1 ) AS rno,
      Column1 
  FROM Clients
)

UPDATE cte SET Column1 =Column1 +' 1 '
WHERE rno=2

Avoid redundant updates

Given the nature of how SQL works, this is exactly what you need to do. If you tell it:

update table_name    
   set field_one = 'one';

that means something entirely different in SQL than

update table_name
   set field_one = 'one'
 where field_one != 'one';

The database can only process what you told it to process, In the first case, because there is no where clause, you have told it to process all the records.

In the second case you have put a filter on it to process only some specific records.

It is up to the code writer not the database to determine the content of the query. If you didn't want every record updated, you should not have told it to do so. The database is quite literal about the commands you give it. Yes the second set of queries are longer becasue they are being more specific. They havea differnt meaning than the orginal queries. That is all to the good as it is far faster to update the ten records you are interested in than all 1,000,000 records in the table.

You need to get over the idea that longer is somehow a bad thing in database queries. Often it is a good thing as you are being more correct in what you are asking for. Your orginal queries were simply incorrect. And now you have pay the price to fix what was a systemically bad practice.

How to update the duplicate records instead of deleting them

(Can only answer based on the info you've provided on your question up to now)

You could group by id as you are already doing and get the max t_id_pk (assuming they are integers), then feed those max primary keys into an update query, excluding them from processing.

Use that update query to turn all the remaining t_version_ind into FALSE.

This is best explained in the following code:

UPDATE T1 
SET t_version_ind = 'FALSE'
where t_id_pk NOT IN (
    SELECT t_id_pk FROM 
        (
        SELECT t_id, MAX(t_id_pk) as t_id_pk FROM T1 
        WHERE t_version_ind ='TRUE'
        GROUP BY t_id 
        HAVING count(*)>1)
        )

Update Query For Duplicate Records Oracle

You may use the count analytic function with LPAD

SELECT card_no
    ,LPAD('D', count(civil_no) OVER (
            PARTITION BY civil_no ORDER BY card_no
            ), 'D') || civil_no as output
FROM t;

Demo

It's not clear which table you want to update, you may do so with a correlated update using the above select or a MERGE INTO

UPDATE t t1 
SET    output = (SELECT output 
                 FROM   (SELECT card_no, 
                                lpad('D', COUNT(civil_no) 
                                            over ( 
                                              PARTITION BY civil_no 
                                              ORDER BY card_no ), 'D') 
                                || civil_no AS output 
                         FROM   t) t2 
                 WHERE  t1.card_no = t2.card_no); 

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