I have an old application I am supporting that uses a Microsoft Access database. The original table design did not add primary keys to every table. I am working on a migration program that among other things is adding and filling in a new primary key field (GUID) when needed.
This is happening in three steps:
Add a new guid field with no constraints
Fill the field with new unique guids
Add the primary key constraints
My problem is setting the unique guids when the table has duplicate rows. Here is my code to set the guids.
Query.SQL.Add('SELECT * FROM ' + TableName);
Query.Open;
while Query.Eof = false do
begin
Query.Edit;
Query.FieldByName(NewPrimaryKeyFieldName).AsGuid := TGuid.NewGuid;
Query.Post;
Query.Next;
end;
FireDac generates an update statement that contains a where clause with all the original fields/values in the row (since there is no unique field for it to use). However, because the rows are complete duplicates the statement still updates two rows.
FireDac correctly errors with this message
Update command updated [2] instead of [1] record.
I can open up the database in Access and delete the duplicate records or assign them a unique guid by editing the table. I would like my conversion tool to automatically do this.
Is there some way to work with these duplicate rows in FireDac? Either to update just one at a time, or to delete just one of them?
In my opinion there is no way to do it with just one SQL Statement.
I would do this:
1. Copy the whole table without duplicates by using a new temp table
SELECT DISTINCT * FROM <TABLENAME>
Add the Keys
Delete old table content and copy new content from new table
Notes:
The DB Should be unavailable for everyone else for that Operation
2. Make BACKUP before
Related
I have following fields in table 1-
db,schema,jobnm,status,runtime, ins_tstmp, upd_tstmp.
A stream has been created on table 1.
A stored procedure was written to loop through another table's dataset (4 records) and write all 4 records to table 1 if they don't already exist else update (using merge sql here; ins_tstmp gets populated via insert part of merge while upd_tstmp gets updated via update part ).
As expected, table1 has all 4 records and Stream also has 4 records with metadata$action as INSERT . UPD_TSTMP is null here.
Now on 2nd run, same 4 records were retrieved. Since they were a match, upd_tstmp got populated in both table 1 and stream but why metadata$action is INSERT only? Not seeing 2 entries for an update. Could someone please explain what I am missing here?
Thanks
Since they were a match, upd_tstmp got populated in both table 1 and
stream but why metadata$action is INSERT only?
The METADATA$ACTION column can have 2 possible values: INSERT and DELETE. So you can't see "UPDATE" in this column.
METADATA$ISUPDATE: This is an extra column indicating whether the operation was part of an UPDATE statement. In your case, you should also see it "false" because Streams record the differences between two offsets. If a row is added and then updated in the current offset, the delta change is a new row. The METADATA$ISUPDATE row records a FALSE value.
https://docs.snowflake.com/en/user-guide/streams-intro.html#stream-columns
I have a Snowflake stored procedure and I want to use "insert into" without hard coding column names.
INSERT INTO MEMBERS_TARGET (ID, NAME)
SELECT ID, NAME
FROM MEMBERS_STREAM;
This is what I have and column names are hardcoded. The query should copy data from MEMBERS_STREAM to MEMBERS_TARGET. The stream has more columns such as
METADATA$ACTION | METADATA$ISUPDATE | METADATA$ROW_ID
which I am not intending to copy.
I don't know of a way to not copy the METADATA columns if not hardcoding. However if you don't want the data maybe the easiest thing to do is to add them to your target, INSERT using a SELECT * and later in the sp set them to NULL.
Alternatively, earlier in your sp, run an ALTER TABLE ADD COLUMN to add the columns, INSERT using SELECT * and then after that run an ALTER TABLE DROP COLUMN to remove the columns? That way your table structure stays the same, albeit briefly it will have some extra columns.
A SELECT * is not usually recommended but it's the easiest alternative I can think of
In my iOS app,I want to change the column data type in database.
ALTER TABLE XXX ALTER COLUMN myColumn INT.
I always get 'near ALTER Syntax error'
How to resolve the problem?
Thanks for your help.
You cannot change the column type. You can create a new table, using the correct data type for the column this time, and then select data from the old table and insert it into the new table. The full procedure is outlined in the ALTER TABLE documentation:
Remember the format of all indexes and triggers associated with table X. This information will be needed in step 7 below. One way to do this is to run a query like the following: SELECT type, sql FROM sqlite_master WHERE tbl_name='X'.
Use CREATE TABLE to construct a new table "new_X" that is in the desired revised format of table X. Make sure that the name "new_X" does not collide with any existing table name, of course.
Transfer content from X into new_X using a statement like: INSERT INTO new_X SELECT ... FROM X.
If foreign key constraints are enabled, disable them using PRAGMA foreign_keys=OFF.
Drop the old table X: DROP TABLE X.
Change the name of new_X to X using: ALTER TABLE new_X RENAME TO X.
Use CREATE INDEX and CREATE TRIGGER to reconstruct indexes and triggers associated with table X. Perhaps use the old format of the triggers and indexes saved from step 1 above as a guide, making changes as appropriate for the alteration.
If foreign key constraints were originally enabled (prior to step 4) then run PRAGMA foreign_key_check to verify that the schema change did not break any foreign key constraints, and run PRAGMA foreign_keys=ON to re-enable foreign key constraints.
If any views refer to table X in a way that is affected by the schema change, then drop those views using DROP VIEW and recreate them with whatever changes are necessary to accommodate the schema change using CREATE VIEW.
Note, SQLite uses type affinity (the column definition doesn't alter what type of data you insert into the table). So if you change the data type, you'll want to change the data, too.
ALTER TABLE table ADD newColumn INTEGER;
UPDATE table SET newColumn = oldColumn;
I want to update whole table from on query. Following is my update functionality is happened:
Database (Database A) stored in the iDevice
Temperory Database (Batabase B) downloads to the device and store in the temp folder inside the device. (Both DB has same database structure)
First I attach temp db to device database. Attached db name is SECOND1
Then I insert new records from temp db to device folder from following Insert code. It is working fine.
INSERT INTO main.fList SELECT * FROM SECOND1.fList WHERE not exists (SELECT 1 FROM main.fList WHERE main.fList.GUID = SECOND1.fList.GUID)
But when I use following code to update it is not working fine. It update same top value for all device db table's rows.
UPDATE fList SET Notes = (SELECT SECOND1.fList.Notes FROM SECOND1.fList WHERE SECOND1.fList.GUID = fDefectList.GUID) WHERE EXISTS (SELECT * FROM SECOND1.fList WHERE SECOND1.fList.GUID = fList.GUID
I found SQL query for bulk update. Following is the code,
UPDATE fTempRank7
SET
fTempRank7.int_key = fRank7.int_key,
fTempRank7.int_rank6 = fRank7.int_rank6,
fTempRank7.title = fRank7.title,
fTempRank7.sequence = fRank7.sequence,
fTempRank7.lastupdated = fRank7.lastupdated
FROM
fTempRank7 INNER JOIN fRank7 ON
fTempRank7.int_key = fRank7.int_key
But in sqlite this code does not work.
Anyone knows bulk update in sqlite?
SQLite does not support joins in an UPDATE statement.
When you use a table name without a database name, it refers to the first matching table in the innermost query. In other words, if you use SECOND1.fList in a subquery, any other occurrence of fList refers to the table in SECOND1.
To ensure that you always refer to the correct table, use the database name in all table references.
The main database is always named main, so all table references should be either main.fList or SECOND1.fList.
Anyway, if you are updating all columns, you can simplify the update by deleting the rows that would be updated, so that all new data can just be inserted:
BEGIN;
DELETE FROM fList WHERE GUID IN (SELECT GUID FROM SECOND1.fList);
INSERT INTO fList SELECT * FROM SECOND1.fList;
COMMIT;
When you have a UNIQUE constraint on the GUID column, this can be simplified into a single statement:
INSERT OR REPLACE INTO fList SELECT * FROM SECOND1.fList;
And here I don't use main. because I know what I'm doing. ☺
I'm searching a way to simulate "create table as select" in Firebird from SP.
We are using this statement frequently in another product, because it is very easy for make lesser, indexable sets, and provide very fast results in server side.
create temp table a select * from xxx where ...
create indexes on a ...
create temp table b select * from xxx where ...
create indexes on b ...
select * from a
union
select * from b
Or to avoid the three or more levels in subqueries.
select *
from a where id in (select id
from b
where ... and id in (select id from c where))
The "create table as select" is very good cos it's provide correct field types and names so I don't need to predefine them.
I can simulate "create table as" in Firebird with Delphi as:
Make select with no rows, get the table field types, convert them to create table SQL, run it, and make "insert into temp table " + selectsql with rows (without order by).
It's ok.
But can I create same thing in a common stored procedure which gets a select sql, and creates a new temp table with the result?
So: can I get query result's field types to I can create field creator SQL from them?
I'm just asking if is there a way or not (then I MUST specify the columns).
Executing DDL inside stored procedure is not supported by Firebird. You could do it using EXECUTE STATEMENT but it is not recommended (see the warning in the end of "No data returned" topic).
One way to do have your "temporary sets" would be to use (transaction-level) Global Temporary Table. Create the GTT as part of the database, with correct datatypes but without constraints (those would probably get into way when you fill only some columns, not all) - then each transaction only sees it's own version of the table and data...