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Fminer modify column data7/28/2023 ![]() ![]() ![]() It gets a bit trickier if you need to change a VARCHAR to an INT or something like that - obviously, if you have column values that don't "fit" into the new type, the conversion will fail. So I suggest you first try this on a copy of your data :-) Not sure what happens if you did have longer strings - either the conversion will fail with an error, or it will go ahead and tell you that some data might have been truncated. As long as you don't have any string longer than those 200 characters, you'll be fine. You can change a VARCHAR(50) to a VARCHAR(200) - again, types are compatible, size is getting bigger - no risk of truncating anything.īasically, you just need ALTER TABLE dbo.YourTableĪLTER COLUMN YourColumn VARCHAR(200) NULL You can change an INT to a BIGINT - the value range of the second type is larger, so you're not in danger of "losing" any data. nextval ALTER TABLE t1 ALTER c4 SET DATA TYPE VARCHAR ( 50 ), COLUMN c4 DROP DEFAULT ALTER TABLE t1 ALTER c5 COMMENT '50 character column' DESC TABLE t1 + -+-+-+-+-+-+-+-+-+-+ | name | type | kind | null? | default | primary key | unique key | check | expression | comment | |-+-+-+-+-+-+-+-+-+-| | C1 | NUMBER(38,0) | COLUMN | Y | NULL | N | N | NULL | NULL | NULL | | C2 | NUMBER(38,0) | COLUMN | Y | NULL | N | N | NULL | NULL | NULL | | C3 | NUMBER(38,0) | COLUMN | Y | long as the data types are somewhat "related" - yes, you can absolutely do this. nextval, c4 VARCHAR ( 20 ) DEFAULT 'abcde', c5 STRING ) DESC TABLE t1 + -+-+-+-+-+-+-+-+-+-+ | name | type | kind | null? | default | primary key | unique key | check | expression | comment | |-+-+-+-+-+-+-+-+-+-| | C1 | NUMBER(38,0) | COLUMN | N | NULL | N | N | NULL | NULL | NULL | | C2 | NUMBER(38,0) | COLUMN | Y | 3 | N | N | NULL | NULL | NULL | | C3 | NUMBER(38,0) | COLUMN | Y | | N | N | NULL | NULL | NULL | | C4 | VARCHAR(20) | COLUMN | Y | 'abcde' | N | N | NULL | NULL | NULL | | C5 | VARCHAR(16777216) | COLUMN | Y | NULL | N | N | NULL | NULL | NULL | + -+-+-+-+-+-+-+-+-+-+ĪLTER TABLE t1 ALTER COLUMN c1 DROP NOT NULL ALTER TABLE t1 MODIFY c2 DROP DEFAULT, c3 SET DEFAULT seq5. Regarding metadata (for example, the COMMENT field):ĬREATE OR REPLACE TABLE t1 ( c1 NUMBER NOT NULL, c2 NUMBER DEFAULT 3, c3 NUMBER DEFAULT seq1. POLICY_CONTEXT function to simulate a query on the column(s) protected by a masking policy and the When modifying one or more table columns with a masking policy or the table itself with a row access policy, use the Matches the columns specified in the policy. For details, see:Īpply a Conditional Masking Policy on a ColumnĪ single masking policy that uses conditional columns can be applied to multiple tables provided that the column structure of the table ![]() USING clause and the FORCE keyword can be used separately or together. ![]() The USING clause and the FORCE keyword are both optional neither are required to set a masking policy on a column. Table without first increasing the precision. If the precision of a column is decreased below the maximum precision of any column data retained in Time Travel, you cannot restore the Increase the precision of the specified number column.ĭecrease the precision of the specified number column if the new precision is sufficient to holdįor text data types, TYPE can be used only to increase the length of the column. type) must beįor the NUMBER data type, TYPE can be used to: When setting the TYPE for a column, the specified type (i.e. The default value for rows inserted after the column was added.ĭropping the default column value from any clone of the table is also prohibited. If the default were dropped, then the column would contain:Ī NULL value for rows inserted before the column was added. Rows inserted after the column was added. This restriction prevents inconsistency between values in rows inserted before the column was added and ALTER TABLE COLUMN UNSET TAG, COLUMN UNSET TAG. ![]()
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