I want to update numerical columns of one table based on matching string columns from another table.i.e.,
I have a table (let's say table1) with 100 records containing 5 string (or text) columns and 10 numerical columns. Now I have another table that has the same structure (columns) and 20 records. In this, few records contain updated data of table1 i.e., numerical columns values are updated for these records and rest are new (both text and numerical columns).
I want to update numerical columns for records with the same text columns (in table1) and insert new data from table2 into table1 where text columns are also new.
I thought of taking an intersect of these two tables and then update but couldn't figure out the logic as how can I update the numerical columns.
Note: I don't have any primary or unique key columns.
Please help here.
Thanks in advance.
The simplest solution would be to use two separate queries, such as:
UPDATE b
SET b.[NumericColumn] = a.[NumericColumn],
etc...
FROM [dbo].[SourceTable] a
JOIN [dbo].[DestinationTable] b
ON a.[StringColumn1] = b.[StringColumn1]
AND a.[StringColumn2] = b.[StringColumn2] etc...
INSERT INTO [dbo].[DestinationTable] (
[NumericColumn],
[StringColumn1],
[StringColumn2],
etc...
)
SELECT a.[NumericColumn],
a.[StringColumn1],
a.[StringColumn2],
etc...
FROM [dbo].[SourceTable] a
LEFT JOIN [dbo].[DestinationTable] b
ON a.[StringColumn1] = b.[StringColumn1]
AND a.[StringColumn2] = b.[StringColumn2] etc...
WHERE b.[NumericColumn] IS NULL
--assumes that [NumericColumn] is non-nullable.
--If there are no non-nullable columns then you
--will have to structure your query differently
This will be effective if you are working with a small dataset that does not change very frequently and you are not worried about high contention.
There are still a number of issues with this approach - most notably what happens if either the source or destination table is accessed and/or modified while the update statement is running. Some of these issues can be worked around other ways but so much depends on the context of how the tables are used that it is difficult to provide a more effective generically-applicable solution.
Related
Prolog:
I have two tables in two different databases, one is an updated version of the other. For example we could imagine that one year ago I duplicated table 1 in the new db (say, table 2), and from then I started working on table 2 never updating table 1.
I would like to compare the two tables, to get the differences that have grown in this period of time (the tables has preserved the structure, so that comparison has meaning)
My way of proceeding was to create a third table, in which I would like to copy both table 1 and table 2, and then count the number of repetitions of every entry.
In my opinion, this, added to a new attribute that specifies for every entry the table where he cames from would do the job.
Problem:
Copying the two tables into the third table I get the (obvious) error to have two duplicate key values in a unique or primary key costraint.
How could I bypass the error or how could do the same job better? Any idea is appreciated
Something like this should do what you want if A and B have the same structure, otherwise just select and rename the columns you want to confront....
SELECT
*
FROM
B
WHERE NOT EXISTS (SELECT * FROM A)
if NOT EXISTS doesn't work in your DBMS you could also use a left outer join comparing the rows columns values.
SELECT
A.*
from
A left outer join B
on A.col = B.col and ....
I'm looking for a way to join two (sometimes more) tables.
I'll start with two and add as I get the pieces working.
Table1 has two columns that identify it
T1ContainerID
T1ObjectID
Table2 has similar columns but starts with T2 but the values will match
T2ContainerID
T2ObjectID
In Table2 there are two columns I am targeting
ObjectName
ObjectValue
There can be any number of ObjectName entries for a given record.
For instance one may have name, address,and a date
another may have Name, address,port,date,ServerName,Device,Status
What I need is a way to pivot all of the potential columns in Table2 in line with Table1 and is that value is not in Table2 for table1 then just make it NULL. I want the header of these columns to be the ObjectName and the value to be ObjectValue. If i can't get a wildcard to grab all potential values i can settle for just calling out each column manually. I was only hoping for a wildcard as it may change as different values for new records get added. Worst case i just adjust code to add anything new.
I do have a bunch of queries that rebuild the database every night and dump it into a different database but I'd like to have a query to pull the results from the main database to get current values rather than something that was run every morning.
So I need to figure out how to insert into a table, from another table, with a where clause that requires me to access the table that I am inserting into. I tried an alias from the table I am inserting into, but I quickly found out that you cannot do that. Basically, what I want to check is that the values that I am inserting into the table match a particular field within the table that I am inserting into. Here is what I've tried:
INSERT INTO "USER"."TABLE1" AS A1
SELECT *
FROM "USER"."TABLE2" AS A2
WHERE A2."HIERARCHYLEVEL" = 2
AND A2."PARENT" = A1."INSTANCE"
Obviously, this was to no avail. I've tried a couple other queries, but they didn't me anywhere, either. Any help would be much appreciated.
EDIT:
I would like to add rows to this table, not add columns to the table. The two tables are of the exact same structure -- in fact, I extracted the data already in table1 from table2. What I have in table1 currently is a bunch of records who have NO PARENT, but an instance. What I want to add is all the records who have a parent in table2 that are equal to the instance in table 1.
Currently there is no way to join on a table when inserting. The solution with the subselect where you select from the table, is the correct.
Aliasing the table you want to change is only possible with UPDATE, UPSERT and MERGE. For these operations it makes sense, as you need to match a column and then decide if you need to update it or insert something instead. In your example the line from table1 that you match is not relevant, as you don't want to change it, so from the statement point of view it is not really relevant that the table you use in your subselect is the same that the one you insert into.
As alternative, I can suggest you following solution, which is equivalent with yours:
INSERT INTO "user"."table1"
SELECT
A1."ROOT",
A1."INSTANCE",
A1."PARENT",
A1."HIERARCHYLEVEL"
FROM "user"."table2" AS A1
WHERE A1."INSTANCE" in (select "PARENT" from "user"."table1")
AND A2."HIERARCHYLEVEL" = 2
This gave me the answer I was looking for, although I am sure there is an easier -- or more efficient -- way to do it.
INSERT INTO "user"."table1"
SELECT
A1."ROOT",
A1."INSTANCE",
A1."PARENT",
A1."HIERARCHYLEVEL"
FROM "user"."table2" AS A1,
"user"."table1" AS A2
WHERE A1."INSTANCE" = A2."PARENT"
AND A2."HIERARCHYLEVEL" = 2
We have two large tables (Clients and Contacts) which undergo an ETL process every night, being inserted into a single "People" table in the data warehouse. This table is used in many places and cannot be significantly altered without a lot of work.
The source tables are populated by third party software; we used to assume that we could identify the rows that had been updated since last night by using the "UpdateDate" column in each, but more recently identified some rows that were not touched by the ETL, as the "UpdateDate" column was not behaving as we had thought; the software company do not see this as a bug, so we have to live with this fact.
As a result, we now take all source rows, transformed into a temp staging table and then Merge that into the data warehouse, using the Merge to identify any changed values. We have noticed that this process is taking too long on some days and would like to limit the number of rows that the ETL process looks at, as we believe that the reason for the hold-up is the principally the sheer volume of data that is examined and stored on the temp database. We can see no way to look purely at the source data and identify when each row last changed.
Here is a simplified pseudocode of the ETL stored procedure, although what the procedure actually does is not really relevant to the question (included just in case you disagree with me!)
CREATE #TempTable (ClientOrContact BIT NOT NULL, Id INT NOT NULL, [Some_Other_Columns])
INSERT #TempTable
SELECT 1 AS ClientOrContact, C.Id, [SomeColumns] FROM
(SELECT [SomeColumns]
FROM Source_ClientsTable C
JOIN FieldsTable F JOIN [SomeOtherTables])
PIVOT (MAX(F.FieldValue) FOR F.FieldName IN ([SomeFieldNames]));
INSERT #TempTable
SELECT 0 AS ClientOrContact, C.Id, [SomeColumns] FROM
(SELECT [SomeColumns]
FROM Source_ContactsTable C
JOIN FieldsTable F JOIN [SomeOtherTables])
PIVOT (MAX(F.FieldValue) FOR F.FieldName IN ([SomeFieldNames]));
ALTER #TempTable ADD PRIMARY KEY (ClientOrContact, Id);
MERGE Target_PeopleTable AS Tgt
USING (SELECT [SomeColumns] FROM #TempTable JOIN [SomeOtherTables]) AS Src
ON Tgt.ClientOrContact = Src.ClientOrContact AND Tgt.Id = Src.Id
WHEN MATCHED AND NOT EXISTS (SELECT Tgt.* INTERSECT SELECT Src.*)
THEN UPDATE SET ([All_NonKeyTargetColumns] = [All_NonKeySourceColumns])
WHEN NOT MATCHED BY Target THEN INSERT [All_TargetColumns] VALUES [All_SourceColumns]
OUTPUT $Action INTO #Changes;
RETURN COUNT(*) FROM #Changes;
GO
The source tables have about 1.5M rows each, but each day only a relatively small number of rows are inserted or updated (never deleted). There are about 50 columns in each table, of those, about 40 columns can have changed values each night. Most columns are VARCHAR and each table contains an independent incremental primary key column. We can add indexes to the source tables, but not alter them in any other way (They have already been indexed by a predecessor) The source tables and target table are on the same server, but different databases. Edit: The Target Table has a composite primary key on the ClientOrContact and Id columns, matching that shown on the temp table in the script above.
So, my question is this - please could you suggest any general possible strategies that might be useful to limit the number of rows we look at or copy across each night? If we only touched the rows that we needed to each night, we would be touching less than 1% of the data we do at the moment...
Before you try the following suggestion, just one thing to check is that the Target_PeopleTable has an index or primary key on the id column. It probably does but without schema information to verify I am making no assumptions and this might speed up the merge stage.
As you've identified if you could somehow limit the records in TempTable to just the changed rows then this could offer a performance win for the actual MERGE statement (depending on how expensive determining just the changed rows is).
As a general strategy I would consider some kind of checksum to try and identify the changed records only. The T-SQL Checksum function could be used to calculate a check sum across the required columns by specifying the columns as a comma separated list to that function or there are actual column types available for this such as Binary_Checksum.
Since you cannot change the source schema you would have to maintain a list of record ids and associated checksums in your target database so that you can readily compare the source checksums to the target checksums from the last run in order to identify a difference.
You can then only insert into the Temp table where there is a checksum difference between the target and source or the id does not exist in the target db.
This might just be moving the performance problem to the temp insert part but I think it's worth a try.
Have you considered triggers? I avoid them like the plague, but they really are the solution to some problems.
Put an INSERT/UPDATE [/DELETE?] trigger on your two source tables. Program it such that when rows are added or updated, the trigger will log the IDs of these rows in a (you'll have to create this) audit table, where that table would contain the ID, the type of change (update or insert – and delete, if you have to worry about those) and when the change was made. When you run ETL, join this list of “to be merged” items with the source tables. When you’re done, delete the table and it’s reset for the next run. (Use the “added on” datetime column to make sure you don’t delete rows that may have been added while you were running ETL.)
There’s lots of details behind proper use and implementation, but overall this idea should do what you need.
I have a table with 32 Million rows and 31 columns in PostgreSQL 9.2.10. I am altering the table by adding columns with updated values.
For example, if the initial table is:
id initial_color
-- -------------
1 blue
2 red
3 yellow
I am modifying the table so that the result is:
id initial_color modified_color
-- ------------- --------------
1 blue blue_green
2 red red_orange
3 yellow yellow_brown
I have code that will read the initial_color column and update the value.
Given that my table has 32 million rows and that I have to apply this procedure on five of the 31 columns, what is the most efficient way to do this? My present choices are:
Copy the column and update the rows in the new column
Create an empty column and insert new values
I could do either option with one column at a time or with all five at once. The columns types are either character varying or character.
The columns types are either character varying or character.
Don't use character, that's a misunderstanding. varchar is ok, but I would suggest just text for arbitrary character data.
Any downsides of using data type "text" for storing strings?
Given that my table has 32 million rows and that I have to apply this
procedure on five of the 31 columns, what is the most efficient way to do this?
If you don't have objects (views, foreign keys, functions) depending on the existing table, the most efficient way is create a new table. Something like this ( details depend on the details of your installation):
BEGIN;
LOCK TABLE tbl_org IN SHARE MODE; -- to prevent concurrent writes
CREATE TABLE tbl_new (LIKE tbl_org INCLUDING STORAGE INCLUDING COMMENTS);
ALTER tbl_new ADD COLUMN modified_color text
, ADD COLUMN modified_something text;
-- , etc
INSERT INTO tbl_new (<all columns in order here>)
SELECT <all columns in order here>
, myfunction(initial_color) AS modified_color -- etc
FROM tbl_org;
-- ORDER BY tbl_id; -- optionally order rows while being at it.
-- Add constraints and indexes like in the original table here
DROP tbl_org;
ALTER tbl_new RENAME TO tbl_org;
COMMIT;
If you have depending objects, you need to do more.
Either was, be sure to add all five at once. If you update each in a separate query you write another row version each time due to the MVCC model of Postgres.
Related cases with more details, links and explanation:
Updating database rows without locking the table in PostgreSQL 9.2
Best way to populate a new column in a large table?
Optimizing bulk update performance in PostgreSQL
While creating a new table you might also order columns in an optimized fashion:
Calculating and saving space in PostgreSQL
Maybe I'm misreading the question, but as far as I know, you have 2 possibilities for creating a table with the extra columns:
CREATE TABLE
This would create a new table and filling could be done using
CREATE TABLE .. AS SELECT.. for filling with creation or
using a separate INSERT...SELECT... later on
Both variants are not what you seem to want to do, as you stated solution without listing all the fields.
Also this would require all data (plus the new fields) to be copied.
ALTER TABLE...ADD ...
This creates the new columns. As I'm not aware of any possibility to reference existing column values, you will need an additional UPDATE ..SET... for filling in values.
So, I' not seeing any way to realize a procedure that follows your choice 1.
Nevertheless, copying the (column) data just to overwrite them in a second step would be suboptimal in any case. Altering a table adding new columns is doing minimal I/O. From this, even if there would be a possibility to execute your choice 1, following choice 2 promises better performance by factors.
Thus, do 2 statements one ALTER TABLE adding all your new columns in on go and then an UPDATE providing the new values for these columns will achieve what you want.
create new column (modified colour), it will have a value of NULL or blank on all records,
run an update statement, assuming your table name is 'Table'.
update table
set modified_color = 'blue_green'
where initial_color = 'blue'
if I am correct this can also work like this
update table set modified_color = 'blue_green' where initial_color = 'blue';
update table set modified_color = 'red_orange' where initial_color = 'red';
update table set modified_color = 'yellow_brown' where initial_color = 'yellow';
once you have done this you can do another update (assuming you have another column that I will call modified_color1)
update table set 'modified_color1'= 'modified_color'