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Merge pull request #35 from oracle-sql-features/23c-features
More 23c features
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‎features/ceil-floor-round-for-datetime-types.adoc‎

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= CEIL, FLOOR, and ROUND for datetime data types
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:database-version: 23.2
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:database-category: sql
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[[feature_summary]]
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You can now pass `DATE`, `TIMESTAMP`, and `INTERVAL` values to the `CEIL` and `FLOOR` functions. These functions include an optional second argument to specify a rounding unit. You can also pass `INTERVAL` values to `ROUND` and `TRUNC` functions.
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[source,sql]
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[subs="verbatim"]
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----
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with vals as (
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select
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interval '+123-5' year(9) to month ymi,
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interval '+0 12:34:56' day to second dsi,
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to_date ( '12-APR-2023 12:34:56', 'DD-MON-YYYY HH24:MI:SS' ) dt,
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to_timestamp ( '12-APR-2023 12:34:56', 'DD-MON-YYYY HH24:MI:SS' ) ts
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)
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select
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-- CEIL rounds up values
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ceil ( ymi ) as year_ceil,
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ceil ( dsi ) as day_ceil,
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ceil ( dt ) as dt_day_ceil,
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ceil ( ts ) as ts_day_ceil,
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-- FLOOR rounds down the datetime value to the units in the second paramter
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floor ( ymi, 'year' ) as ymi_year_floor,
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floor ( dsi, 'hh24' ) as dsi_hour_floor,
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floor ( dt, 'hh24' ) as dt_hour_floor,
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floor ( ts, 'hh24' ) as ts_hour_floor,
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-- ROUND now supports INTERVALs
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round ( dsi, 'mi' ) as dsi_minute_round
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from vals;
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----
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.Result
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[source,sql]
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[subs="verbatim"]
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----
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SQL> with vals as (
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2 select
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3 interval '+123-5' year(9) to month ymi,
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4 interval '+0 12:34:56' day to second dsi,
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5 to_date ( '12-APR-2023 12:34:56', 'DD-MON-YYYY HH24:MI:SS' ) dt,
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6 to_timestamp ( '12-APR-2023 12:34:56', 'DD-MON-YYYY HH24:MI:SS' ) ts
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7 )
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8 select
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9 -- CEIL rounds up values
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10 ceil ( ymi ) as year_ceil,
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11 ceil ( dsi ) as day_ceil,
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12 ceil ( dt ) as dt_day_ceil,
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13 ceil ( ts ) as ts_day_ceil,
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14 -- FLOOR rounds down the datetime value to the units in the second paramter
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15 floor ( ymi, 'year' ) as ymi_year_floor,
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16 floor ( dsi, 'hh24' ) as dsi_hour_floor,
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17 floor ( dt, 'hh24' ) as dt_hour_floor,
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18 floor ( ts, 'hh24' ) as ts_hour_floor,
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19 -- ROUND now supports INTERVALs
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20 round ( dsi, 'mi' ) as dsi_minute_round
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21 from vals;
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YEAR_CE DAY_CEIL DT_DAY_CEIL TS_DAY_CEIL YMI_YEA DSI_HOUR_FLOOR DT_HOUR_FLOOR TS_HOUR_FLOOR DSI_MINUTE_ROUND
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------- ------------------- ----------------- ----------------- ------- ------------------- ----------------- ----------------- -------------------
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+124-00 +01 00:00:00.000000 13-APR-2023 00:00 13-APR-2023 00:00 +123-00 +00 12:00:00.000000 12-APR-2023 12:00 12-APR-2023 12:00 +00 12:35:00.000000
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----
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== Benefits
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These functions make it easy to find the upper and lower bounds for date and time values for a specified unit.
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== Further information
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* Availability: All Offerings
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* https://docs.oracle.com/en/database/oracle/oracle-database/23/sqlrf/ROUND-and-TRUNC-Date-Functions.html#GUID-8E10AB76-21DA-490F-A389-023B648DDEF8[CEIL, FLOOR, ROUND, and TRUNC Date Functions Documentation]

‎features/default-on-null-update.adoc‎

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= Default ON NULL for UPDATE statements
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:database-version: 23.2
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:database-category: sql
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[[feature_summary]]
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You can specify a default value when updating a column to `NULL`. The database assigns the default value to the column instead of `NULL`.
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[source,sql]
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[subs="verbatim"]
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----
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create table default_values (
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id integer,
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c1 number default extract ( second from systimestamp ),
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c2 number default on null extract ( second from systimestamp ),
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c3 number default on null for insert only extract ( second from systimestamp ),
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c4 number default on null for insert and update extract ( second from systimestamp )
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);
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-- For the columns with DEFAULT ON NULL, the database replaces NULL with the timestamp value
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insert into default_values
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values ( 1, null, null, null, null );
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select * from default_values;
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-- The standard DEFAULT clause has no impact on UPDATEs, so C1 remains NULL
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update default_values
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set c1 = null;
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-- DEFAULT ON NULL adds an implicit NOT NULL constraint to the column
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-- The default only applies on insert, so this raises an ORA-01407 error
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update default_values
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set c2 = null;
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-- DEFAULT ON NULL FOR INSERT ONLY is equivalent to DEFAULT ON NULL
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-- So this also raises an ORA-01407 error
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update default_values
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set c3 = null;
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-- C4 is DEFAULT ON NULL FOR INSERT AND UPDATE
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-- So the database replaces NULL with its default value
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update default_values
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set c4 = null;
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-- The value of C4 has changed; all other columns retain their INSERT value
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select * from default_values;
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----
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.Result
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[source,sql]
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[subs="verbatim"]
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----
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SQL> create table default_values (
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2 id integer,
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3 c1 number default extract ( second from systimestamp ),
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4 c2 number default on null extract ( second from systimestamp ),
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5 c3 number default on null for insert only extract ( second from systimestamp ),
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6 c4 number default on null for insert and update extract ( second from systimestamp )
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7 );
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Table created.
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SQL>
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SQL> -- For the columns with DEFAULT ON NULL, the database replaces NULL with the timestamp value
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SQL> insert into default_values
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2 values ( 1, null, null, null, null );
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1 row created.
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SQL>
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SQL> select * from default_values;
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ID C1 C2 C3 C4
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---------- ---------- ---------- ---------- ----------
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1 <null> 1.585189 1.585189 1.585189
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SQL>
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SQL> -- The standard DEFAULT clause has no impact on UPDATEs, so C1 remains NULL
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SQL> update default_values
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2 set c1 = null;
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1 row updated.
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SQL>
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SQL> -- DEFAULT ON NULL adds an implicit NOT NULL constraint to the column
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SQL> -- The default only applies on insert, so this raises an ORA-01407 error
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SQL> update default_values
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2 set c2 = null;
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set c2 = null
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*
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ERROR at line 2:
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ORA-01407: cannot update ("CHRIS"."DEFAULT_VALUES"."C2") to NULL
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SQL>
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SQL> -- DEFAULT ON NULL FOR INSERT ONLY is equivalent to DEFAULT ON NULL
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SQL> -- So this also raises an ORA-01407 error
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SQL> update default_values
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2 set c3 = null;
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set c3 = null
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*
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ERROR at line 2:
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ORA-01407: cannot update ("CHRIS"."DEFAULT_VALUES"."C3") to NULL
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SQL>
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SQL> -- C4 is DEFAULT ON NULL FOR INSERT AND UPDATE
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SQL> -- So the database replaces NULL with its default value
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SQL> update default_values
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2 set c4 = null;
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1 row updated.
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SQL>
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SQL> -- The value of C4 has changed; all other columns retain their INSERT value
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SQL> select * from default_values;
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ID C1 C2 C3 C4
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---------- ---------- ---------- ---------- ----------
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1 <null> 1.585189 1.585189 1.608401
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----
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== Benefits
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Providing a default value for `NULL` on `UPDATE` simplifies code to map `NULL` to a non `NULL` value when changing data.
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== Further information
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* Availability: All Offerings
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* https://docs.oracle.com/en/database/oracle/oracle-database/23/sqlrf/CREATE-TABLE.html#GUID-F9CE0CC3-13AE-4744-A43C-EAC7A71AAAB6__CJABFBAA[CREATE TABLE Documentation]

‎features/fuzzy-match-operator.adoc‎

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= FUZZY_MATCH operator
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:database-version: 23.2
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:database-category: sql
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[[feature_summary]]
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The `FUZZY_MATCH` operator enables you to compare strings for similarity using algorithms such as Jaro-Winkler and Levenshtein distance.
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[source,sql]
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[subs="verbatim"]
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----
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/* Compare the team names to "Champions City" with the different fuzzy matching algorithms */
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with teams as (
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select * from (
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values ( 'Champions United' ),
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( 'Runner-up City' ),
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( 'Midtable Town' ),
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( 'Underdogs United' ),
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( 'Upstart FC' ),
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( 'Relegated Athletic' )
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) t ( team_name )
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), match_value as (
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select 'Champions City' match_team
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)
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select team_name, match_team,
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fuzzy_match ( levenshtein, team_name, match_team ) as levenshtein,
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fuzzy_match ( jaro_winkler, team_name, match_team ) as jaro_winkler,
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fuzzy_match ( bigram, team_name, match_team ) as bigram,
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fuzzy_match ( trigram, team_name, match_team ) as trigram,
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fuzzy_match ( whole_word_match, team_name, match_team ) as wwm,
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fuzzy_match ( longest_common_substring, team_name, match_team ) as lcs
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from teams
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cross join match_value;
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/* Find the team names that match "Champions City" with Jaro-Winkler score > 90 */
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with teams as (
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select * from (
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values ( 'Champions United' ),
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( 'Runner-up City' ),
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( 'Midtable Town' ),
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( 'Underdogs United' ),
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( 'Upstart FC' ),
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( 'Relegated Athletic' )
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) t ( team_name )
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), match_value as (
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select 'Champions City' match_team
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)
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select team_name, match_team
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from teams
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join match_value
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on fuzzy_match ( jaro_winkler, team_name, match_team ) > 90;
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----
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.Result
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[source,sql]
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[subs="verbatim"]
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----
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SQL> /* Compare the team names to "Champions City" for the different fuzzy matching algorithms */
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SQL> with teams as (
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2 select * from (
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3 values ( 'Champions United' ),
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4 ( 'Runner-up City' ),
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5 ( 'Midtable Town' ),
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6 ( 'Underdogs United' ),
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7 ( 'Upstart FC' ),
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8 ( 'Relegated Athletic' )
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9 ) t ( team_name )
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10 ), match_value as (
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11 select 'Champions City' match_team
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12 )
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13 select team_name, match_team,
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14 fuzzy_match ( levenshtein, team_name, match_team ) as levenshtein,
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15 fuzzy_match ( jaro_winkler, team_name, match_team ) as jaro_winkler,
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16 fuzzy_match ( bigram, team_name, match_team ) as bigram,
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17 fuzzy_match ( trigram, team_name, match_team ) as trigram,
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18 fuzzy_match ( whole_word_match, team_name, match_team ) as wwm,
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19 fuzzy_match ( longest_common_substring, team_name, match_team ) as lcs
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20 from teams
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21 cross join match_value;
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TEAM_NAME MATCH_TEAM LEVENSHTEIN JARO_WINKLER BIGRAM TRIGRAM WWM LCS
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------------------ -------------- ----------- ------------ ---------- ---------- ---------- ----------
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Champions United Champions City 75 92 66 57 50 62
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Runner-up City Champions City 36 57 30 25 50 35
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Midtable Town Champions City 8 44 0 0 0 7
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Underdogs United Champions City 32 49 13 0 0 12
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Upstart FC Champions City 8 56 0 0 0 7
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Relegated Athletic Champions City 12 41 0 0 0 5
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6 rows selected.
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SQL>
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SQL> /* Find the team names that match "Champions City" with Jaro-Winkler score > 90 */
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SQL> with teams as (
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2 select * from (
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3 values ( 'Champions United' ),
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4 ( 'Runner-up City' ),
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5 ( 'Midtable Town' ),
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6 ( 'Underdogs United' ),
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7 ( 'Upstart FC' ),
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8 ( 'Relegated Athletic' )
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9 ) t ( team_name )
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10 ), match_value as (
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11 select 'Champions City' match_team
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12 )
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13 select team_name, match_team
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14 from teams
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15 join match_value
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16 on fuzzy_match ( jaro_winkler, team_name, match_team ) > 90;
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TEAM_NAME MATCH_TEAM
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------------------ --------------
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Champions United Champions City
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----
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== Benefits
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This operator makes it easier to find similar strings with SQL.
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== Further information
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* Availability: All Offerings
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* https://docs.oracle.com/en/database/oracle/oracle-database/23/sqlrf/data-quality-operators.html#GUID-C13A179C-1F82-4522-98AA-E21C6504755E[FUZZY_MATCH Documentation]

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