I need to reconcile article1 (top) and article2 tables into a View displaying differences. But before that I need to drop all zeros from column 'type'. Create new ID column equals to filenumber + type so the resulting column should be use as index. All columns share same data type
Columns needed:
ID
C0016
C0029
C00311
You can utilize below script in SQL Server to get the format you want:
Reference SO post on removing padding 0
SELECT CONCAT(filenumber,type) AS filenumber, type, cost
FROM
(
SELECT
filenumber,
SUBSTRING(type, PATINDEX('%[^0]%',type),
LEN(type)- PATINDEX('%[^0]%',type)+ 1) AS type, cost
FROM
(
VALUES
('C001','00006',40),
('C002','00009',80),
('C003','00011',120)
) as t(filenumber,type, cost)
) AS t
Resultset
+------------+------+------+
| filenumber | type | cost |
+------------+------+------+
| C0016 | 6 | 40 |
| C0029 | 9 | 80 |
| C00311 | 11 | 120 |
+------------+------+------+
You can use try_convert() :
alter table table_name
add id as concat(filenumber, try_convert(int, type)) persisted -- physical storage
If you want a view :
create view veiw_name
as
select t.*, concat(filenumber, try_convert(int, type)) as id
from table t;
try_convert() will return null whereas conversation fails.
Related
I have a table like this
| id | data |
|---------------|---------------------|
| org:abc:basic | {org,org:abc:basic} |
| org:xyz:basic | {org,basic} |
| org:efg:basic | {org} |
I need to write a query to select all the rows which doesn't have the id inside the data column.
Or at least I need to query all the records which doesn't have a text starting from org: and ending with :basic within data.
Currently for this I try to run
SELECT * FROM t_permission WHERE 'org:%:basic' NOT LIKE ANY (data)
query which returns everything even the first row.
you can use the <> operator with ALL against the array:
select *
from the_table
where id <> all(data);
I have a column with entries like:
column:
156781
234762
780417
and would like to have the following:
column:
0000156781
0000234762
0000780417
For this I use the following query:
Select isnull(replicate('0', 10 - len(column)),'') + rtrim(column) as a from table)
However, I don't know how to replace the values in the whole column.
I already tried with:
UPDATE table
SET column= (
Select isnull(replicate('0', 10 - len(column)),'') + rtrim(column) as columnfrom table)
But I get the following error.
Subquery returned more than 1 value. This is not permitted when the subquery follows =, !=, <, <= , >, >= or when the subquery is used as an expression.
The answer to your question is going to depend on the data type of your column. If it is a text column for example VARCHAR then you can modify the value in the table. If it is a number type such as INT it is the value and not the characters which is stored.
We can also express this by saying that "0" + "1" = "01" whilst 0 + 1 = 1.
In either case we can format the value in a query.
create table numberz(
val1 int,
val2 varchar(10));
insert into numberz values
(156781,'156781'),
(234762,'234762'),
(780417,'780417');
/* required format
0000156781
0000234762
0000780417
*/
select * from numberz;
GO
val1 | val2
-----: | :-----
156781 | 156781
234762 | 234762
780417 | 780417
UPDATE numberz
SET val1 = isnull(
replicate('0',
10 - len(val1)),'')
+ rtrim(val1),
val2 = isnull(
replicate('0',
10 - len(val2)),'')
+ rtrim(val2);
GO
3 rows affected
select * from numberz;
GO
val1 | val2
-----: | :---------
156781 | 0000156781
234762 | 0000234762
780417 | 0000780417
select isnull(
replicate('0',
10 - len(val1)),'')
+ rtrim(val1)
from numberz
GO
| (No column name) |
| :--------------- |
| 0000156781 |
| 0000234762 |
| 0000780417 |
db<>fiddle here
Usually, when we need to show values in specificity format these processes are performed using the CASE command or with other functions on the selection field list, mean without updating. In such cases, we can change our format to any format and anytime with changing functions. As dynamic fields.
For example:
select id, lpad(id::text, 6, '0') as format_id from test.test_table1
order by id
Result:
id format_id
-------------
1 000001
2 000002
3 000003
4 000004
5 000005
Maybe you really need an UPDATE, so I wrote a sample query for an UPDATE command too.
update test.test_table1
set
id = lpad(id::text, 6, '0');
Suppose that I have a table named agents_timesheet that having a structure like this:
ID | name | health_check_record | date | clock_in | clock_out
---------------------------------------------------------------------------------------------------------
1 | AAA | {"mental":{"stress":"no", "depression":"no"}, | 6-Dec-2021 | 08:25:07 |
| | "physical":{"other_symptoms":"headache", "flu":"no"}} | | |
---------------------------------------------------------------------------------------------------------
2 | BBB | {"mental":{"stress":"no", "depression":"no"}, | 6-Dec-2021 | 08:26:12 |
| | "physical":{"other_symptoms":"no", "flu":"yes"}} | | |
---------------------------------------------------------------------------------------------------------
3 | CCC | {"mental":{"stress":"no", "depression":"severe"}, | 6-Dec-2021 | 08:27:12 |
| | "physical":{"other_symptoms":"cancer", "flu":"yes"}} | | |
Now I need to get all agents having flu at the day. As for getting the flu from a single JSON in Oracle SQL, I can already get it by this SQL statement:
SELECT * FROM JSON_TABLE(
'{"mental":{"stress":"no", "depression":"no"}, "physical":{"fever":"no", "flu":"yes"}}', '$'
COLUMNS (fever VARCHAR(2) PATH '$.physical.flu')
);
As for getting the values from the column health_check_record, I can get it by utilizing the SELECT statement.
But How to get the values of flu in the JSON in the health_check_record of that table?
Additional question
Based on the table, how can I retrieve full list of other_symptoms, then it will get me this kind of output:
ID | name | other_symptoms
-------------------------------
1 | AAA | headache
2 | BBB | no
3 | CCC | cancer
You can use JSON_EXISTS() function.
SELECT *
FROM agents_timesheet
WHERE JSON_EXISTS(health_check_record, '$.physical.flu == "yes"');
There is also "plain old way" without JSON parsing only treting column like a standard VARCHAR one. This way will not work in 100% of cases, but if you have the data in the same way like you described it might be sufficient.
SELECT *
FROM agents_timesheet
WHERE health_check_record LIKE '%"flu":"yes"%';
How to get the values of flu in the JSON in the health_check_record of that table?
From Oracle 12, to get the values you can use JSON_TABLE with a correlated CROSS JOIN to the table:
SELECT a.id,
a.name,
j.*,
a."DATE",
a.clock_in,
a.clock_out
FROM agents_timesheet a
CROSS JOIN JSON_TABLE(
a.health_check_record,
'$'
COLUMNS (
mental_stress VARCHAR2(3) PATH '$.mental.stress',
mental_depression VARCHAR2(3) PATH '$.mental.depression',
physical_fever VARCHAR2(3) PATH '$.physical.fever',
physical_flu VARCHAR2(3) PATH '$.physical.flu'
)
) j
WHERE physical_flu = 'yes';
db<>fiddle here
You can use "dot notation" to access data from a JSON column. Like this:
select "DATE", id, name
from agents_timesheet t
where t.health_check_record.physical.flu = 'yes'
;
DATE ID NAME
----------- --- ----
06-DEC-2021 2 BBB
Note that this approach requires that you use an alias for the table name (so you can use it in accessing the JSON data).
For testing I used the data posted by MT0 on dbfiddle. I am not a big fan of double-quoted column names; use something else for "DATE", such as dt or date_.
I´ve got 2 tables.
CREATE TABLE content (
id bigserial NOT NULL,
name text
);
CREATE TABLE data (
id bigserial NOT NULL,
...
);
The tables are already filled with a lot of data.
Now I want to add a new column content_id (NOT NULL) to the data table.
It should be a foreign key to the content table.
Is it possible to automatically create an entry in the content table to set a content_id in the data table.
For example
**content**
| id | name |
| 1 | abc |
| 2 | cde |
data
| id |... |
| 1 |... |
| 2 |... |
| 3 |... |
Now I need an update statement that creates 3 (in this example) content entries and add the ids to the data table to get this result:
content
| id | name |
| 1 | abc |
| 2 | cde |
| 3 | ... |
| 4 | ... |
| 5 | ... |
data
| id |... | content_id |
| 1 |... | 3 |
| 2 |... | 4 |
| 3 |... | 5 |
demo:db<>fiddle
According to the answers presented here: How can I add a column that doesn't allow nulls in a Postgresql database?, there are several ways of adding a new NOT NULL column and fill this directly.
Basicly there are 3 steps. Choose the best fitting (with or without transaction, setting a default value first and remove after, leave the NOT NULL contraint first and add afterwards, ...)
Step 1: Adding new column (without NOT NULL constraint, because the values of the new column values are not available at this point)
ALTER TABLE data ADD COLUMN content_id integer;
Step 2: Inserting the data into both tables in a row:
WITH inserted AS ( -- 1
INSERT INTO content
SELECT
generate_series(
(SELECT MAX(id) + 1 FROM content),
(SELECT MAX(id) FROM content) + (SELECT COUNT(*) FROM data)
),
'dummy text'
RETURNING id
), matched AS ( -- 2
SELECT
d.id AS data_id,
i.id AS content_id
FROM (
SELECT
id,
row_number() OVER ()
FROM data
) d
JOIN (
SELECT
id,
row_number() OVER ()
FROM inserted
) i ON i.row_number = d.row_number
) -- 3
UPDATE data d
SET content_id = s.content_id
FROM (
SELECT * FROM matched
) s
WHERE d.id = s.data_id;
Executing several statements one after another by using the results of the previous one can be achieved using WITH clauses (CTEs):
Insert data into content table: This generates an integer series starting at the MAX() + 1 value of the current content's id values and has as many records as the data table. Afterwards the new ids are returned
Now we need to match the current records of the data table with the new ids. So for both sides, we use row_number() window function to generate a consecutive row count for each records. Because both, the insert result and the actual data table have the same number of records, this can be used as join criterion. So we can match the id column of the data table with the new content's id values
This matched data can used in the final update of the new content_id column
Step 3: Add the NOT NULL constraint
ALTER TABLE data ALTER COLUMN content_id SET NOT NULL;
I have the following table and want to merge multiple rows based on neighboring rows.
INPUT
EXPECTED OUTPUT
The logic is that since "abc" is connected to "abcd" in the first row and "abcd" is connected to "abcde" in the second row and so on, thus "abc", "abcd", "abcde", "abcdef" are connected and put in one array. The same applied to the rest rows. The number of connected neighboring rows are arbitrary.
The question is how to do that using Hive script without any UDF. Do I have to use Spark for this type of operation? Thanks very much.
One idea I had is to tag rows first as
How to do that using Hive script only?
This is an example of a CONNECT BY query which is not supported in HIVE or SPARK, unlike DB2 or ORACLE, et al.
You can simulate such a query with Spark Scala, but it is far from handy. Putting a tag in means the question is less relevant then, imo.
Here is a work-around using Hive script to get the intermediate table.
drop table if exists step1;
create table step1 STORED as orc as
with src as
(
select split(u.tmp,",")[0] as node_1, split(u.tmp,",")[1] as node_2
from
(select stack (7,
"abc,abcd",
"abcd,abcde",
"abcde,abcdef",
"bcd,bcde",
"bcde,bcdef",
"cdef,cdefg",
"def,defg"
) as tmp
) u
)
select node_1, node_2, if(node_2 = lead(node_1, 1) over (order by node_1), 1, 0) as tag, row_number() OVER (order by node_1) as row_num
from src;
drop table if exists step2;
create table step2 STORED as orc as
SELECT tag, row_number() over (ORDER BY tag) as row_num
FROM (
SELECT cast(v.tag as int) as tag
FROM (
SELECT
split(regexp_replace(repeat(concat(cast(key as string), ","), end_idx-start_idx), ",$",""), ",") as tags --repeat the row number by the number of rows
FROM (
SELECT COALESCE(lag(row_num, 1) over(ORDER BY row_num), 0) as start_idx, row_num as end_idx, row_number() over (ORDER BY row_num) as key
FROM step1 where tag=0
) a
) b
LATERAL VIEW explode(tags) v as tag
) c ;
drop table if exists step3;
create table step3 STORED as orc as
SELECT
a.node_1, a.node_2, b.tag
FROM step1 a
JOIN step2 b
ON a.row_num=b.row_num;
The final table looks like
select * from step3;
+---------------+---------------+------------+
| step3.node_1 | step3.node_2 | step3.tag |
+---------------+---------------+------------+
| abc | abcd | 1 |
| abcd | abcde | 1 |
| abcde | abcdef | 1 |
| bcd | bcde | 2 |
| bcde | bcdef | 2 |
| cdef | cdefg | 3 |
| def | defg | 4 |
+---------------+---------------+------------+
The third column can be used to collect node pairs.