I have two tables:
table_a with fields item_id,rank, and 50 other fields.
table_b with fields item_id, and the same 50 fields as table_a
I need to write a SELECT query that adds the rows of table_b to table_a but with rank set to a specific value, let's say 4.
Currently I have:
SELECT * FROM table_a
UNION
SELECT item_id, 4 rank, field_1, field_2, ...
How can I join the two tables together without writing out all of the fields and without using an INSERT query?
EDIT:
My idea is to join table_b to table_a somehow with the rank field remaining empty, then simply replace the null rank fields. The rank field is never null, but item_id can be duplicated and table_a may have item_id values that are not in table_b, and vice-versa.
I am not sure I understand why you need this, but you can use jsonb functions:
select (jsonb_populate_record(null::table_a, row)).*
from (
select to_jsonb(a) as row
from table_a a
union
select to_jsonb(b) || '{"rank": 4}'
from table_b b
) s
order by item_id;
Working example in rextester.
I'm pretty sure I've got it. The predefined rank column can be inserted into table_b by joining to the subset of itself with only the columns left of the column behind which you want to insert.
WITH
_leftcols AS ( SELECT item_id, 4 rank FROM table_b ),
_combined AS ( SELECT * FROM table_b JOIN _leftcols USING (item_id) )
SELECT * FROM _combined
UNION
SELECT * FROM table_a
Related
I’m building an insert statement dynamically to add multiple rows of data to a table in a batch, as I believe it is more efficient than inserting one at a time. However, I need the last couple of columns in each inserted row to be set with the results of querying another table using a value from the new row. This is my imaginary pseudocode version:
INSERT INTO TableA (column1, column2, column3, column4, column5)
VALUES (SELECT {value1a}, {value1b}, {value1c}, b.column1, b.column2 FROM TableB b WHERE b.column3 = {value1c}),
(SELECT {value2a}, {value2b}, {value2c}, b.column1, b.column2 FROM TableB b WHERE b.column3 = {value2c}),
…
Now here is another wrinkle: I have a unique index on TableA with an ignore clause, and there is a lot of redundant data to process, so only about 15% of the rows in any given batch insert will actually be added to the database. Does this mean it would be more efficient to insert the rows with values for columns 1 – 3, then query for the rows that were inserted, and update column 4 and 5? If so, would the following be the most efficient way to do that for all the inserted rows?
UPDATE a SET a.column4 = b.column1, a.column5 = b.column2
FROM TableA a INNER JOIN TableB b ON b.column3 = a.column3
WHERE a.CreatedAt >= {BatchInsertTime}
(assuming no other processes are adding rows to the table)
For better efficiency and a simpler way to join TableB, send all the TableA rows in a JSON doc, eg
insert into TableA (column1, column2, column3, column4, column5) …
select d.*, b.column1 column4, b.column2 column5
from openjson(#json)
with
(
column1 varchar(20),
column2 int,
column3 varchar(20)
) as d
left join TableB b
on b.column3 = d.column2
where #json is an NVARCHAR(MAX) parameter that looks like
[
{"column1":"foo", "column2":3,"column3":"bar" },
{"column1":"foo2", "column2":4,"column3":"bar2" },
. . .
]
I have two tables in postgresql
One table is of the form
Create table table1(
ID serial PRIMARY KEY,
Type []Text
)
Create table table2(
type text,
sellerID int
)
Now i want to get all the rows from table1 which are having type same that in table2 but the problem is that in table1 the type is an array.
In case the type in the table has an identifiable delimiter like ',' ,';' etc. you can rewrite the query as regexp_split_to_table(type,',') or versions later than 9.5 unnest function can be use too.
For eg.,
select * from
( select id ,regexp_split_to_table(type,',') from table1)table1
inner join
select * from table2
on trim(table1.type) = trim(table2.type)
Another good example can be found - https://www.dbrnd.com/2017/03/postgresql-regexp_split_to_array-to-split-string-using-different-delimiters/
SELECT
a[1] AS DiskInfo
,a[2] AS DiskNumber
,a[3] AS MessageKeyword
FROM (
SELECT regexp_split_to_array('Postgres Disk information , disk 2 , failed', ',')
) AS dt(a)
You can use the ANY operator in the JOIN condition:
select *
from table1 t1
join table2 t2 on t2.type = any (t1.type);
Note that if the types in the table1 match multiple rows in table2, you would get duplicates (from table1) because that's how a join works. Maybe you want an EXISTS condition instead:
select *
from table1 t1
where exists (select *
from table2 t2
where t2.type = any(t1.type));
I am creating a Materialized View from two tables, using the array_agg function to join strings from table_b to table_a. Essentially, column_c on table_a is a nullable array of numbers corresponding to the id column of table_b (which has only two columns, id and description). However, the Materialized View fails to include a row for any row on table_a that is null / empty on column_c.
Is it possible to make the Materialized either (1) enter an empty array; or (2) a null value, when table_a column_c value is null?
CREATE MATERIALIZED VIEW my_materialized_view
AS
SELECT
id,
column_a,
column_b,
array_agg(description) as column_c
FROM table_a
JOIN table_b on table_b.id = any(column_c)
GROUP BY table_a.id
ORDER BY table_a.id ASC
WITH DATA;
Use LEFT JOIN:
CREATE MATERIALIZED VIEW my_materialized_view
AS
SELECT
id,
column_a,
column_b,
array_agg(description) as column_c
-- or
-- coalesce(array_agg(description), '{}') as column_c
FROM table_a
LEFT JOIN table_b on table_b.id = any(column_c)
GROUP BY table_a.id
ORDER BY table_a.id ASC
WITH DATA;
Table 1
Table 2
select col1, col2, etc
from table 1
left join table 2
on table1.col1 = table2.col1
If table2.col1 has null values, will this somehow screw up my join results?
No, table2 null values do not matter in this case. Left join will match all rows from table1 to table2. If a row from table2 does not have a match in table1 it will not appear in the result set.
I am using Postgresql and need to query two tables like this:
Table1
ID Bill
A 1
B 2
B 3
C 4
Table2
ID
A
B
I want a table with all the columns in Table1 but keeping only the records with IDs that are available in Table2 (A and B in this case). Also, Table2's ID is unique.
ID Bill
A 1
B 2
B 3
Which join I should use or if I can use WHERE statement?
Thanks!
SELECT Table1.*
FROM Table1
INNER JOIN Table2 USING (ID);
or
SELECT *
FROM Table1
WHERE ID IN (SELECT ID FROM Table2);
but the first one is better for performance reason.
SELECT *
FROM Table1
WHERE EXISTS (
SELECT 1 FROM Table2 WHERE Table2.ID = Table1.ID LIMIT 1
)