How to remove/avoid a particular string in SQL output - sql

Below is the SQL Query:
select '"'|| trim(COLUMN1) ||'"|"'|| trim(COLUMN2) ||'"|"'|| trim(COLUMN3) ||'"'
from TABLE1 where ....
The output I get is:
"DATA1"|""|"DATA3"
"DATA4"|""|"DATA6"
But, I want it to display the output like below:
"DATA1"||"DATA3"
"DATA4"||"DATA6"
That means, if there is some null value of a particular column, it must not display "". I hope you all got it.
Please help me achieving this, as I am automating this process where in the output file goes directly to the destination application (i.e. I won't be able to modify it manually).
Thanks!


You can use case to avoid printing anything if the column is null
select '"'|| trim(COLUMN1) || '"|' ||
case when COLUMN2 is null then '' else '"' || trim(COLUMN2) || '"' end
|| '|"' || trim(COLUMN3) ||'"'
from TABLE1 where ....


You can use NVL2( value, value_if_not_null, value_if_null ):
SELECT NVL2( COLUMN1, '"' || TRIM( COLUMN1 ) || '"', NULL )
|| '|' || NVL2( COLUMN2, '"' || TRIM( COLUMN2 ) || '"', NULL )
|| '|' || NVL2( COLUMN3, '"' || TRIM( COLUMN3 ) || '"', NULL )
FROM table1
WHERE -- ...
Or CASE:
SELECT CASE WHEN COLUMN1 IS NOT NULL THEN '"' || TRIM( COLUMN1 ) || '"' END
|| '|' || CASE WHEN COLUMN2 IS NOT NULL THEN '"' || TRIM( COLUMN2 ) || '"' END
|| '|' || CASE WHEN COLUMN3 IS NOT NULL THEN '"' || TRIM( COLUMN3 ) || '"' END
FROM table1
WHERE -- ...


replace Function
select replace('"'|| trim(COLUMN1) ||'"|"'|| trim(COLUMN2) ||'"|"'|| trim(COLUMN3) ||'"', '""','')
from TABLE1 where ....


Use
REPLACE(String, '""', '')
select REPLACE('"'|| trim(COLUMN1) ||'"|"'|| trim(COLUMN2) ||'"|"'|| trim(COLUMN3) ||'"', '""', '') from TABLE1 where ....

Related

Search and return multiple wildcard values in a single column

All -
I'm looking at a large volume of sql query history data. Ultimately I need to create a distinct list of tables used by each from a list of their executed queries. Let's say my simplified table for this example is:
create table zwork_example (
username varchar2(50),
sql_text clob);
insert into zwork_example (username, sql_text)
values ('user1', 'schema1.table1, schema1.table2, schema2.table1, schema1.table1');
insert into zwork_example (username, sql_text)
Values ('user2', 'schema1.table3, schema1.table2, schema2.table1, schema1.table6');
Does anyone have any ideas on how I can search for schema1* and return N number of table names that belong to schema1? In this example I have a particular schema I'm interested in, so I can explicitly state that schema1 is the only schema I'm interested in returning the table names from.
The output I would look for given this example is:
User Schema Tables
-------- -------- --------
User1 schema1 table1, table2
User2 schema1 table3, table2, table6

CLOB, large data set ... doesn't sound promising. Read: it'll probably take some time to get the result. For such a small data set, see if this helps.
SQL> with
2 search_for (schema) as
3 (select 'schema1' from dual),
4 temp as
5 (select distinct
6 username,
7 trim(regexp_substr(dbms_lob.substr(sql_text, 32767), '[^,]+', 1, column_value)) col
8 from zwork_example cross join
9 table(cast(multiset(select level from dual
10 connect by level <= regexp_count(sql_text, ',') + 1
11 ) as sys.odcinumberlist))
12 )
13 select
14 t.username,
15 s.schema,
16 listagg(trim(replace(t.col, s.schema ||'.', null)), ', ') within group (order by null) tables
17 from temp t join search_for s on instr(t.col, s.schema) > 0
18 group by t.username, s.schema;
USERNAME SCHEMA TABLES
---------- ------- --------------------------------------------------
user1 schema1 table1, table2
user2 schema1 table2, table3, table6
SQL>
What does it do?
search_for CTE contains a schema you're searching for (schema1, right?)
temp CTE splits the sql_text into rows
moreover, in order to get distinct list of tables, I applied dbms_lob.substr to the column, hoping that you don't actually have strings longer than that (32767, that is)
final query just aggregates tables it found - rows where schemas match

For a large dataset you can use:
WITH search_string ( schema_name ) AS (
SELECT 'schema1' FROM DUAL
),
matches ( username, sql_text, schema_name, end_pos, matches ) AS (
SELECT username,
sql_text,
schema_name,
CASE
WHEN sql_text LIKE schema_name || '%'
THEN INSTR( sql_text, ',' )
WHEN sql_text NOT LIKE ', ' || schema_name || '.'
THEN 0
ELSE INSTR(
sql_text,
', ' || schema_name || '.',
INSTR( sql_text, ', ' || schema_name || '.' ) + 3
)
END,
CASE
WHEN sql_text LIKE schema_name || '%'
THEN EMPTY_CLOB() || SUBSTR(
sql_text,
LENGTH(schema_name || '.') + 1,
INSTR( sql_text, ',' ) - LENGTH(schema_name || '.') - 1
)
WHEN INSTR( sql_text, ', ' || schema_name || '.' ) = 0
THEN NULL
WHEN INSTR( sql_text, ',', INSTR( sql_text, ', ' || schema_name || '.' ) + 3 ) = 0
THEN EMPTY_CLOB() || SUBSTR(
sql_text,
INSTR( sql_text, ', ' || schema_name || '.' )
+ LENGTH(', ' || schema_name || '.')
)
ELSE EMPTY_CLOB() || SUBSTR(
sql_text,
INSTR( sql_text, ', ' || schema_name || '.' )
+ LENGTH(', ' || schema_name || '.'),
INSTR( sql_text, ',', INSTR( sql_text, ', ' || schema_name || '.' ) + 3 )
- INSTR( sql_text, ', ' || schema_name || '.' )
- LENGTH(', ' || schema_name || '.')
)
END
FROM zwork_example
CROSS JOIN search_string
UNION ALL
SELECT username,
sql_text,
schema_name,
INSTR(
sql_text,
', ' || schema_name || '.',
end_pos + 3
),
matches
|| ', '
|| CASE
WHEN INSTR( sql_text, ',', end_pos + 1 ) = 0
THEN SUBSTR(
sql_text,
end_pos + LENGTH(', ' || schema_name || '.')
)
ELSE SUBSTR(
sql_text,
end_pos + LENGTH(', ' || schema_name || '.'),
INSTR( sql_text, ',', end_pos + 1 )
- end_pos - LENGTH(', ' || schema_name || '.')
)
END
FROM matches
WHERE end_pos > 0
)
SELECT username,
matches
FROM matches
WHERE end_pos = 0;
Which, for the sample data:
create table zwork_example (
username varchar2(50),
sql_text clob
);
DECLARE
v_text CLOB;
BEGIN
insert into zwork_example (username, sql_text)
values ('user1', 'schema1.table1, schema1.table2, schema2.table1, schema1.table1');
insert into zwork_example (username, sql_text)
Values ('user2', 'schema1.table3, schema1.table2, schema2.table1, schema1.table6');
insert into zwork_example (username, sql_text)
Values ('user3', 'schema2.table3, schema3.table2, schema4.table1, schema2.table6');
insert into zwork_example (username, sql_text)
Values ('user4', 'schema2.table3, schema3.table2, schema4.table1, schema1.table6');
v_text := 'schema1.table1';
FOR i IN 2 .. 250 LOOP
v_text := v_text || ', schema1.table' || i;
END LOOP;
insert into zwork_example (username, sql_text) values ( 'user5', v_text );
END;
/
Outputs:
USERNAME
MATCHES
user3
user4
table6
user1
table1, table2, table1
user2
table3, table2, table6
user5
table1, table2, table3, table4, table5, table6, table7, table8, table9, table10, table11, table12, table13, table14, table15, table16, table17, table18, table19, table20, table21, table22, table23, table24, table25, table26, table27, table28, table29, table30, table31, table32, table33, table34, table35, table36, table37, table38, table39, table40, table41, table42, table43, table44, table45, table46, table47, table48, table49, table50, table51, table52, table53, table54, table55, table56, table57, table58, table59, table60, table61, table62, table63, table64, table65, table66, table67, table68, table69, table70, table71, table72, table73, table74, table75, table76, table77, table78, table79, table80, table81, table82, table83, table84, table85, table86, table87, table88, table89, table90, table91, table92, table93, table94, table95, table96, table97, table98, table99, table100, table101, table102, table103, table104, table105, table106, table107, table108, table109, table110, table111, table112, table113, table114, table115, table116, table117, table118, table119, table120, table121, table122, table123, table124, table125, table126, table127, table128, table129, table130, table131, table132, table133, table134, table135, table136, table137, table138, table139, table140, table141, table142, table143, table144, table145, table146, table147, table148, table149, table150, table151, table152, table153, table154, table155, table156, table157, table158, table159, table160, table161, table162, table163, table164, table165, table166, table167, table168, table169, table170, table171, table172, table173, table174, table175, table176, table177, table178, table179, table180, table181, table182, table183, table184, table185, table186, table187, table188, table189, table190, table191, table192, table193, table194, table195, table196, table197, table198, table199, table200, table201, table202, table203, table204, table205, table206, table207, table208, table209, table210, table211, table212, table213, table214, table215, table216, table217, table218, table219, table220, table221, table222, table223, table224, table225, table226, table227, table228, table229, table230, table231, table232, table233, table234, table235, table236, table237, table238, table239, table240, table241, table242, table243, table244, table245, table246, table247, table248, table249, table250
db<>fiddle here

How can combine the values of multiple columns to a single comma separated column in Oracle SQL?

I need to create a column that has all the values from the previous columns combined and separated using commas ', '
I can't use listagg since I'm trying to combine multiple columns instead of rows.
below is an example of how the result column should look like, thanks.

Use string concatenation:
select trim(leading ',' from
(case when column1 is not null then ',' || column1 end) ||
(case when column2 is not null then ',' || column2 end) ||
(case when column3 is not null then ',' || column3 end)
)

This is also using a string concatenation but slightly different
SELECT
SUBSTR(
REPLACE(
', ' || NVL(column1,'!!') || ', ' || NVL(column2,'!!') || ', ' || NVL(column3,'!!')
,', !!','')
,3,100)

Convert SQL query to pivot

I can't seem able to get the logic to convert the following query to a pivot SQL. My table has 20 columns with roles on them, I'd like to convert those columns into rows so, when exported to Excel, I can filter on a single column since the values can be the same on the 20 columns. So far what I've done is convert the 20 columns into a single one and then split that single one into rows:
select distinct TASKID,
regexp_substr(t.roles,'[^|]+', 1, lines.column_value) as role
from (
select TASKID,
TRIM(ROLE1) || '|' ||
TRIM(ROLE2) || '|' ||
TRIM(ROLE3) || '|' ||
TRIM(ROLE4) || '|' ||
TRIM(ROLE5) || '|' ||
TRIM(ROLE6) || '|' ||
TRIM(ROLE7) || '|' ||
TRIM(ROLE8) || '|' ||
TRIM(ROLE9) || '|' ||
TRIM(ROLE10) || '|' ||
TRIM(ROLE11) || '|' ||
TRIM(ROLE12) || '|' ||
TRIM(ROLE13) || '|' ||
TRIM(ROLE14) || '|' ||
TRIM(ROLE15) || '|' ||
TRIM(ROLE16) || '|' ||
TRIM(ROLE17) || '|' ||
TRIM(ROLE18) || '|' ||
TRIM(ROLE19) || '|' ||
TRIM(ROLE20) as roles
from menu_roles
where RLTYPE='58'
) t,
TABLE(CAST(MULTISET(select LEVEL from dual connect by instr(t.roles, '|', 1, LEVEL - 1) > 0) as sys.odciNumberList)) lines
where regexp_substr(t.roles,'[^|]+', 1, lines.column_value) is not null
order by regexp_substr(t.roles,'[^|]+', 1, lines.column_value)
I'd understand that using PIVOT would be more efficient vs concatenating and splitting a string.
Thank you!

You appear to want UNPIVOT:
SELECT task_id,
role
FROM menu_roles
UNPIVOT ( role FOR role_number IN ( ROLE1, ROLE2, ROLE3, ROLE4 /*, ... */ ) );
Or, using UNION ALL:
SELECT task_id, role1 AS role FROM menu_roles
UNION ALL SELECT task_id, role2 AS role FROM menu_roles
UNION ALL SELECT task_id, role3 AS role FROM menu_roles
UNION ALL SELECT task_id, role4 AS role FROM menu_roles
-- ...

SQL optimization with indexes

I have been trying hard to optimize below query using indexes in place of where clause. can any one help on the same. Data volume is very high so I want to optimize it using indexing or anyother way?
Query goes like this:
SELECT *
FROM
(SELECT
a.*,
rownum as row_num
FROM
(SELECT DISTINCT
lot.lot_no AS lotNo, lot.sel as sel,
lot.C_ARRIVAL_NOTICE_NO AS arrNoticeNo,
lot.C_SHIPMENT_DIRECTION AS shipmentDirection,
lot.C_SENDERS_REFERENCE_NUM AS externalReference,
lot.booking_seq AS bookingNo,lot.shipper AS shipperCode,
nvl(lot.shipper_name ,lot.shipper_addr1) AS shipperName,
NVL2 (lot.commdesc, lot.commdesc || ' ', '') || NVL2 (lot.comdesc1,lot. comdesc1 || ' ', '') || NVL2 (lot.comdesc2, lot.comdesc2 || ' ', '') || NVL2 (lot.comdesc3, lot.comdesc3 || ' ', '') || NVL2 (lot.comdesc4, lot.comdesc4 || ' ', '') || NVL2 (lot.comdesc5, lot.comdesc5 || ' ', '') || NVL2 (lot.comdesc6,lot. comdesc6 || ' ', '') || NVL2 (lot.comdesc7,lot. comdesc7 || ' ', '') || NVL2 (lot.comdesc8, lot.comdesc8 || ' ', '') || NVL2 (lot.comdesc9, lot.comdesc9, '') AS description,
lot.lot_qty AS pieces, lot.lot_wght AS weight,
lot.lot_cube AS cube,
to_char(lot.input_date, 'dd-Mon-YYYY') AS lotDate,
lot.e_m AS e_m, lot.warehouse AS warehouse,
to_char(lot.in_date , 'dd-Mon-YYYY') AS inDate,
lot.in_time AS inTime, lot.hold AS hold,
to_char(lot.sail_date, 'dd-Mon-YYYY') AS sailDate,
to_char(lot.sail_date, 'dd-Mon-YYYY') AS etdDate,
lot.container AS container,
lot.oml_bl_no AS billOfLadingNumber,
lot.reference AS fileNumber,
lot.inland_carrier AS trucker,
lot.pro_number AS proNumber,
lot.comments AS exceptions, lot.vessel AS vessel,
lot.cstatus AS status, lot.voyage AS voyage,
(SELECT count(*) FROM tra_shipment_status
WHERE c_reference = lot.lot_no AND i_status_code = '857940') as transmitcount,
(SELECT c_finalcfs_code FROM imp_bl_top
WHERE inv_no = lot.C_Arrival_Notice_No) as cfsCode,
'STI_COUNTRY_US' AS schemaName
FROM
itemdata lot
WHERE
lot.in_date BETWEEN TO_DATE('27-FEB-2017 00:00', 'DD-MON-YYYY HH24:MI')
AND TO_DATE('29-MAR-2017 23:59', 'DD-MON-YYYY HH24:MI')
AND lot.sel IS NOT NULL
AND (lot.C_ARRIVAL_NOTICE_NO IS NOT NULL OR
lot.C_SHIPMENT_DIRECTION ='IO')
AND lot.I_STATUS > 0 AND Lot.Cstatus = 'D'
ORDER BY
lot.lot_no desc, lot.in_date desc) a
WHERE
rownum <= 60)
WHERE
row_num >= 1

Comparing column by column between two rows in Oracle DB

I need to write a query to compare column by column (ie: find differences) between two rows in the database. For example:
row1: 10 40 sometext 24
row2: 10 25 sometext 24
After the query executed, it should shows only the fields that have difference (ie: the second field)
Here's what I have done so far:
select table1.column1, table1.column2, table1.column3, table1.column4
from table1
where somefield in (field1, field2);
The above query will show me two rows one above another like this:
10 40 sometext 24
10 25 sometext 24
Then I have to manually do the comparison and it takes a lot of time b/c the row contains a lot of column.
So again my question is: How can I write a query that will show me only the columns that have differences??
Thanks

Use UNPIVOT clause (see http://www.oracle-developer.net/display.php?id=506) to turn columns into rows, then filter out the same rows (using GROUP BY HAVING COUNT and finally use PIVOT to get rows with different columns only.

To do this easily you need to query the metadata for the table to get each row. You can use the following code as a script.
Replace the define table_name with your table name and define yes_drop_it = NO. Put your raw WHERE syntax into the where_clause. The comparison logic always compares the first two rows returned for the where clause.
whenever sqlerror exit failure rollback;
set linesize 150
define test_tab_name = tst_cf_cols
define yes_drop_it = YES
define order_by = 1, 2
define where_clause = 1 = 1
define tab_owner = user
<<clearfirst>> begin
for clearout in (
select 'drop table ' || table_name as cmd
from all_tables
where owner = &&tab_owner and table_name = upper('&&test_tab_name')
and '&&yes_drop_it' = 'YES'
) loop
execute immediate clearout.cmd;
execute immediate '
create table &&test_tab_name as
select 10 as column1, 40 as column2, ''sometext'' as column3, 24 as column4 from dual
union all
select 10 as column1, 25 as column2, ''sometext'' as column3, 24 as column4 from dual
';
end loop;
end;
/
column cfsynt format a4000 word_wrap new_value comparison_syntax
with parms as (select 'parmquery' as cte_name, 'row_a' as corr_name_1, 'row_b' as corr_name_2 from dual)
select
'select * from (select ' || LISTAGG(cfcol || ' AS cf_' || trim (to_char (column_id, '000')) || '_' || column_name
, chr(13) || ', ') WITHIN GROUP (order by column_id)
|| chr(13) || ' from (select * from parmquery where row_number = 1) ' || corr_name_1
|| chr(13) || ', (select * from parmquery where row_number = 2) ' || corr_name_2
|| chr(13) || ') where ''DIFFERENT'' IN (' || LISTAGG ('cf_' || trim (to_char (column_id, '000')) || '_' || column_name, chr(13) || ', ') within group (order by column_id) || ')'
as cfsynt
from parms, (
select
'decode (' || corr_name_1 || '.' || column_name || ', ' || corr_name_2
|| '.' || column_name || ', ''SAME'', ''DIFFERENT'')'
as cfcol,
column_name,
column_id
from
parms,
all_tab_columns
where
owner = &&tab_owner and table_name = upper ('&&test_tab_name')
);
with parmquery as (select rownum as row_number, vals.* from (
select * from &&test_tab_name
where &&where_clause
order by &&order_by
) vals
) &&comparison_syntax
;