Postgresql, select a "fake" row - postgresql

In Postgres 8.4 or higher, what is the most efficient way to get a row of data populated by defaults without actually creating the row. Eg, as a transaction (pseudocode):
create table "mytable"
(
id serial PRIMARY KEY NOT NULL,
parent_id integer NOT NULL DEFAULT 1,
random_id integer NOT NULL DEFAULT random(),
)
begin transaction
fake_row = insert into mytable (id) values (0) returning *;
delete from mytable where id=0;
return fake_row;
end transaction
Basically I'd expect a query with a single row where parent_id is 1 and random_id is a random number (or other function return value) but I don't want this record to persist in the table or impact on the primary key sequence serial_id_seq.
My options seem to be using a transaction like above or creating views which are copies of the table with the fake row added but I don't know all the pros and cons of each or whether a better way exists.
I'm looking for an answer that assumes no prior knowledge of the datatypes or default values of any column except id or the number or ordering of the columns. Only the table name will be known and that a record with id 0 should not exist in the table.
In the past I created the fake record 0 as a permanent record but I've come to consider this record a type of pollution (since I typically have to filter it out of future queries).

You can copy the table definition and defaults to the temp table with:
CREATE TEMP TABLE table_name_rt (LIKE table_name INCLUDING DEFAULTS);
And use this temp table to generate dummy rows. Such table will be dropped at the end of the session (or transaction) and will only be visible to current session.

You can query the catalog and build a dynamic query
Say we have this table:
create table test10(
id serial primary key,
first_name varchar( 100 ),
last_name varchar( 100 ) default 'Tom',
age int not null default 38,
salary float default 100.22
);
When you run following query:
SELECT string_agg( txt, ' ' order by id )
FROM (
select 1 id, 'SELECT ' txt
union all
select 2, -9999 || ' as id '
union all
select 3, ', '
|| coalesce( column_default, 'null'||'::'||c.data_type )
|| ' as ' || c.column_name
from information_schema.columns c
where table_schema = 'public'
and table_name = 'test10'
and ordinal_position > 1
) xx
;
you will get this sting as a result:
"SELECT -9999 as id , null::character varying as first_name ,
'Tom'::character varying as last_name , 38 as age , 100.22 as salary"
then execute this query and you will get the "phantom row".
We can build a function that build and excecutes the query and return our row as a result:
CREATE OR REPLACE FUNCTION get_phantom_rec (p_i test10.id%type )
returns test10 as $$
DECLARE
v_sql text;
myrow test10%rowtype;
begin
SELECT string_agg( txt, ' ' order by id )
INTO v_sql
FROM (
select 1 id, 'SELECT ' txt
union all
select 2, p_i || ' as id '
union all
select 3, ', '
|| coalesce( column_default, 'null'||'::'||c.data_type )
|| ' as ' || c.column_name
from information_schema.columns c
where table_schema = 'public'
and table_name = 'test10'
and ordinal_position > 1
) xx
;
EXECUTE v_sql INTO myrow;
RETURN myrow;
END$$ LANGUAGE plpgsql ;
and then this simple query gives you what you want:
select * from get_phantom_rec ( -9999 );
id | first_name | last_name | age | salary
-------+------------+-----------+-----+--------
-9999 | | Tom | 38 | 100.22

I would just select the fake values as literals:
select 1 id, 1 parent_id, 1 user_id
The returned row will be (virtually) indistinguishable from a real row.
To get the values from the catalog:
select
0 as id, -- special case for serial type, just return 0
(select column_default::int -- Cast to int, because we know the column is int
from INFORMATION_SCHEMA.COLUMNS
where table_name = 'mytable'
and column_name = 'parent_id') as parent_id,
(select column_default::int -- Cast to int, because we know the column is int
from INFORMATION_SCHEMA.COLUMNS
where table_name = 'mytable'
and column_name = 'user_id') as user_id;
Note that you must know what the columns are and their type, but this is reasonable. If you change the table schema (except default value), you would need to tweak the query.
See the above as a SQLFiddle.

Related

pivot or reshapre sql [duplicate]

I've been tasked with coming up with a means of translating the following data:
date category amount
1/1/2012 ABC 1000.00
2/1/2012 DEF 500.00
2/1/2012 GHI 800.00
2/10/2012 DEF 700.00
3/1/2012 ABC 1100.00
into the following:
date ABC DEF GHI
1/1/2012 1000.00
2/1/2012 500.00
2/1/2012 800.00
2/10/2012 700.00
3/1/2012 1100.00
The blank spots can be NULLs or blanks, either is fine, and the categories would need to be dynamic. Another possible caveat to this is that we'll be running the query in a limited capacity, which means temp tables are out. I've tried to research and have landed on PIVOT but as I've never used that before I really don't understand it, despite my best efforts to figure it out. Can anyone point me in the right direction?
Dynamic SQL PIVOT:
create table temp
(
date datetime,
category varchar(3),
amount money
)
insert into temp values ('1/1/2012', 'ABC', 1000.00)
insert into temp values ('2/1/2012', 'DEF', 500.00)
insert into temp values ('2/1/2012', 'GHI', 800.00)
insert into temp values ('2/10/2012', 'DEF', 700.00)
insert into temp values ('3/1/2012', 'ABC', 1100.00)
DECLARE #cols AS NVARCHAR(MAX),
#query AS NVARCHAR(MAX);
SET #cols = STUFF((SELECT distinct ',' + QUOTENAME(c.category)
FROM temp c
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set #query = 'SELECT date, ' + #cols + ' from
(
select date
, amount
, category
from temp
) x
pivot
(
max(amount)
for category in (' + #cols + ')
) p '
execute(#query)
drop table temp
Results:
Date ABC DEF GHI
2012-01-01 00:00:00.000 1000.00 NULL NULL
2012-02-01 00:00:00.000 NULL 500.00 800.00
2012-02-10 00:00:00.000 NULL 700.00 NULL
2012-03-01 00:00:00.000 1100.00 NULL NULL
Dynamic SQL PIVOT
Different approach for creating columns string
create table #temp
(
date datetime,
category varchar(3),
amount money
)
insert into #temp values ('1/1/2012', 'ABC', 1000.00)
insert into #temp values ('2/1/2012', 'DEF', 500.00)
insert into #temp values ('2/1/2012', 'GHI', 800.00)
insert into #temp values ('2/10/2012', 'DEF', 700.00)
insert into #temp values ('3/1/2012', 'ABC', 1100.00)
DECLARE #cols AS NVARCHAR(MAX)='';
DECLARE #query AS NVARCHAR(MAX)='';
SELECT #cols = #cols + QUOTENAME(category) + ',' FROM (select distinct category from #temp ) as tmp
select #cols = substring(#cols, 0, len(#cols)) --trim "," at end
set #query =
'SELECT * from
(
select date, amount, category from #temp
) src
pivot
(
max(amount) for category in (' + #cols + ')
) piv'
execute(#query)
drop table #temp
Result
date ABC DEF GHI
2012-01-01 00:00:00.000 1000.00 NULL NULL
2012-02-01 00:00:00.000 NULL 500.00 800.00
2012-02-10 00:00:00.000 NULL 700.00 NULL
2012-03-01 00:00:00.000 1100.00 NULL NULL
I know this question is older but I was looking thru the answers and thought that I might be able to expand on the "dynamic" portion of the problem and possibly help someone out.
First and foremost I built this solution to solve a problem a couple of coworkers were having with inconstant and large data sets needing to be pivoted quickly.
This solution requires the creation of a stored procedure so if that is out of the question for your needs please stop reading now.
This procedure is going to take in the key variables of a pivot statement to dynamically create pivot statements for varying tables, column names and aggregates. The Static column is used as the group by / identity column for the pivot(this can be stripped out of the code if not necessary but is pretty common in pivot statements and was necessary to solve the original issue), the pivot column is where the end resultant column names will be generated from, and the value column is what the aggregate will be applied to. The Table parameter is the name of the table including the schema (schema.tablename) this portion of the code could use some love because it is not as clean as I would like it to be. It worked for me because my usage was not publicly facing and sql injection was not a concern. The Aggregate parameter will accept any standard sql aggregate 'AVG', 'SUM', 'MAX' etc. The code also defaults to MAX as an aggregate this is not necessary but the audience this was originally built for did not understand pivots and were typically using max as an aggregate.
Lets start with the code to create the stored procedure. This code should work in all versions of SSMS 2005 and above but I have not tested it in 2005 or 2016 but I can not see why it would not work.
create PROCEDURE [dbo].[USP_DYNAMIC_PIVOT]
(
#STATIC_COLUMN VARCHAR(255),
#PIVOT_COLUMN VARCHAR(255),
#VALUE_COLUMN VARCHAR(255),
#TABLE VARCHAR(255),
#AGGREGATE VARCHAR(20) = null
)
AS
BEGIN
SET NOCOUNT ON;
declare #AVAIABLE_TO_PIVOT NVARCHAR(MAX),
#SQLSTRING NVARCHAR(MAX),
#PIVOT_SQL_STRING NVARCHAR(MAX),
#TEMPVARCOLUMNS NVARCHAR(MAX),
#TABLESQL NVARCHAR(MAX)
if isnull(#AGGREGATE,'') = ''
begin
SET #AGGREGATE = 'MAX'
end
SET #PIVOT_SQL_STRING = 'SELECT top 1 STUFF((SELECT distinct '', '' + CAST(''[''+CONVERT(VARCHAR,'+ #PIVOT_COLUMN+')+'']'' AS VARCHAR(50)) [text()]
FROM '+#TABLE+'
WHERE ISNULL('+#PIVOT_COLUMN+','''') <> ''''
FOR XML PATH(''''), TYPE)
.value(''.'',''NVARCHAR(MAX)''),1,2,'' '') as PIVOT_VALUES
from '+#TABLE+' ma
ORDER BY ' + #PIVOT_COLUMN + ''
declare #TAB AS TABLE(COL NVARCHAR(MAX) )
INSERT INTO #TAB EXEC SP_EXECUTESQL #PIVOT_SQL_STRING, #AVAIABLE_TO_PIVOT
SET #AVAIABLE_TO_PIVOT = (SELECT * FROM #TAB)
SET #TEMPVARCOLUMNS = (SELECT replace(#AVAIABLE_TO_PIVOT,',',' nvarchar(255) null,') + ' nvarchar(255) null')
SET #SQLSTRING = 'DECLARE #RETURN_TABLE TABLE ('+#STATIC_COLUMN+' NVARCHAR(255) NULL,'+#TEMPVARCOLUMNS+')
INSERT INTO #RETURN_TABLE('+#STATIC_COLUMN+','+#AVAIABLE_TO_PIVOT+')
select * from (
SELECT ' + #STATIC_COLUMN + ' , ' + #PIVOT_COLUMN + ', ' + #VALUE_COLUMN + ' FROM '+#TABLE+' ) a
PIVOT
(
'+#AGGREGATE+'('+#VALUE_COLUMN+')
FOR '+#PIVOT_COLUMN+' IN ('+#AVAIABLE_TO_PIVOT+')
) piv
SELECT * FROM #RETURN_TABLE'
EXEC SP_EXECUTESQL #SQLSTRING
END
Next we will get our data ready for the example. I have taken the data example from the accepted answer with the addition of a couple of data elements to use in this proof of concept to show the varied outputs of the aggregate change.
create table temp
(
date datetime,
category varchar(3),
amount money
)
insert into temp values ('1/1/2012', 'ABC', 1000.00)
insert into temp values ('1/1/2012', 'ABC', 2000.00) -- added
insert into temp values ('2/1/2012', 'DEF', 500.00)
insert into temp values ('2/1/2012', 'DEF', 1500.00) -- added
insert into temp values ('2/1/2012', 'GHI', 800.00)
insert into temp values ('2/10/2012', 'DEF', 700.00)
insert into temp values ('2/10/2012', 'DEF', 800.00) -- addded
insert into temp values ('3/1/2012', 'ABC', 1100.00)
The following examples show the varied execution statements showing the varied aggregates as a simple example. I did not opt to change the static, pivot, and value columns to keep the example simple. You should be able to just copy and paste the code to start messing with it yourself
exec [dbo].[USP_DYNAMIC_PIVOT] 'date','category','amount','dbo.temp','sum'
exec [dbo].[USP_DYNAMIC_PIVOT] 'date','category','amount','dbo.temp','max'
exec [dbo].[USP_DYNAMIC_PIVOT] 'date','category','amount','dbo.temp','avg'
exec [dbo].[USP_DYNAMIC_PIVOT] 'date','category','amount','dbo.temp','min'
This execution returns the following data sets respectively.
Updated version for SQL Server 2017 using STRING_AGG function to construct the pivot column list:
create table temp
(
date datetime,
category varchar(3),
amount money
);
insert into temp values ('20120101', 'ABC', 1000.00);
insert into temp values ('20120201', 'DEF', 500.00);
insert into temp values ('20120201', 'GHI', 800.00);
insert into temp values ('20120210', 'DEF', 700.00);
insert into temp values ('20120301', 'ABC', 1100.00);
DECLARE #cols AS NVARCHAR(MAX),
#query AS NVARCHAR(MAX);
SET #cols = (SELECT STRING_AGG(category,',') FROM (SELECT DISTINCT category FROM temp WHERE category IS NOT NULL)t);
set #query = 'SELECT date, ' + #cols + ' from
(
select date
, amount
, category
from temp
) x
pivot
(
max(amount)
for category in (' + #cols + ')
) p ';
execute(#query);
drop table temp;
There's my solution cleaning up the unnecesary null values
DECLARE #cols AS NVARCHAR(MAX),
#maxcols AS NVARCHAR(MAX),
#query AS NVARCHAR(MAX)
select #cols = STUFF((SELECT ',' + QUOTENAME(CodigoFormaPago)
from PO_FormasPago
order by CodigoFormaPago
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
select #maxcols = STUFF((SELECT ',MAX(' + QUOTENAME(CodigoFormaPago) + ') as ' + QUOTENAME(CodigoFormaPago)
from PO_FormasPago
order by CodigoFormaPago
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set #query = 'SELECT CodigoProducto, DenominacionProducto, ' + #maxcols + '
FROM
(
SELECT
CodigoProducto, DenominacionProducto,
' + #cols + ' from
(
SELECT
p.CodigoProducto as CodigoProducto,
p.DenominacionProducto as DenominacionProducto,
fpp.CantidadCuotas as CantidadCuotas,
fpp.IdFormaPago as IdFormaPago,
fp.CodigoFormaPago as CodigoFormaPago
FROM
PR_Producto p
LEFT JOIN PR_FormasPagoProducto fpp
ON fpp.IdProducto = p.IdProducto
LEFT JOIN PO_FormasPago fp
ON fpp.IdFormaPago = fp.IdFormaPago
) xp
pivot
(
MAX(CantidadCuotas)
for CodigoFormaPago in (' + #cols + ')
) p
) xx
GROUP BY CodigoProducto, DenominacionProducto'
t #query;
execute(#query);
The below code provides the results which replaces NULL to zero in the output.
Table creation and data insertion:
create table test_table
(
date nvarchar(10),
category char(3),
amount money
)
insert into test_table values ('1/1/2012','ABC',1000.00)
insert into test_table values ('2/1/2012','DEF',500.00)
insert into test_table values ('2/1/2012','GHI',800.00)
insert into test_table values ('2/10/2012','DEF',700.00)
insert into test_table values ('3/1/2012','ABC',1100.00)
Query to generate the exact results which also replaces NULL with zeros:
DECLARE #DynamicPivotQuery AS NVARCHAR(MAX),
#PivotColumnNames AS NVARCHAR(MAX),
#PivotSelectColumnNames AS NVARCHAR(MAX)
--Get distinct values of the PIVOT Column
SELECT #PivotColumnNames= ISNULL(#PivotColumnNames + ',','')
+ QUOTENAME(category)
FROM (SELECT DISTINCT category FROM test_table) AS cat
--Get distinct values of the PIVOT Column with isnull
SELECT #PivotSelectColumnNames
= ISNULL(#PivotSelectColumnNames + ',','')
+ 'ISNULL(' + QUOTENAME(category) + ', 0) AS '
+ QUOTENAME(category)
FROM (SELECT DISTINCT category FROM test_table) AS cat
--Prepare the PIVOT query using the dynamic
SET #DynamicPivotQuery =
N'SELECT date, ' + #PivotSelectColumnNames + '
FROM test_table
pivot(sum(amount) for category in (' + #PivotColumnNames + ')) as pvt';
--Execute the Dynamic Pivot Query
EXEC sp_executesql #DynamicPivotQuery
OUTPUT :
A version of Taryn's answer with performance improvements:
Data
CREATE TABLE dbo.Temp
(
[date] datetime NOT NULL,
category nchar(3) NOT NULL,
amount money NOT NULL,
INDEX [CX dbo.Temp date] CLUSTERED ([date]),
INDEX [IX dbo.Temp category] NONCLUSTERED (category)
);
INSERT dbo.Temp
([date], category, amount)
VALUES
({D '2012-01-01'}, N'ABC', $1000.00),
({D '2012-01-02'}, N'DEF', $500.00),
({D '2012-01-02'}, N'GHI', $800.00),
({D '2012-02-10'}, N'DEF', $700.00),
({D '2012-03-01'}, N'ABC', $1100.00);
Dynamic pivot
DECLARE
#Delimiter nvarchar(4000) = N',',
#DelimiterLength bigint,
#Columns nvarchar(max),
#Query nvarchar(max);
SET #DelimiterLength = LEN(REPLACE(#Delimiter, SPACE(1), N'#'));
-- Before SQL Server 2017
SET #Columns =
STUFF
(
(
SELECT
[text()] = #Delimiter,
[text()] = QUOTENAME(T.category)
FROM dbo.Temp AS T
WHERE T.category IS NOT NULL
GROUP BY T.category
ORDER BY T.category
FOR XML PATH (''), TYPE
)
.value(N'text()[1]', N'nvarchar(max)'),
1, #DelimiterLength, SPACE(0)
);
-- Alternative for SQL Server 2017+ and database compatibility level 110+
SELECT #Columns =
STRING_AGG(CONVERT(nvarchar(max), QUOTENAME(T.category)), N',')
WITHIN GROUP (ORDER BY T.category)
FROM
(
SELECT T2.category
FROM dbo.Temp AS T2
WHERE T2.category IS NOT NULL
GROUP BY T2.category
) AS T;
IF #Columns IS NOT NULL
BEGIN
SET #Query =
N'SELECT [date], ' +
#Columns +
N'
FROM
(
SELECT [date], amount, category
FROM dbo.Temp
) AS S
PIVOT
(
MAX(amount)
FOR category IN (' +
#Columns +
N')
) AS P;';
EXECUTE sys.sp_executesql #Query;
END;
Execution plans
Results
date
ABC
DEF
GHI
2012-01-01 00:00:00.000
1000.00
NULL
NULL
2012-01-02 00:00:00.000
NULL
500.00
800.00
2012-02-10 00:00:00.000
NULL
700.00
NULL
2012-03-01 00:00:00.000
1100.00
NULL
NULL
CREATE TABLE #PivotExample(
[ID] [nvarchar](50) NULL,
[Description] [nvarchar](50) NULL,
[ClientId] [smallint] NOT NULL,
)
GO
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI1','ACI1Desc1',1008)
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI1','ACI1Desc2',2000)
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI1','ACI1Desc3',3000)
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI1','ACI1Desc4',4000)
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI2','ACI2Desc1',5000)
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI2','ACI2Desc2',6000)
INSERT #PivotExample ([ID],[Description], [ClientId]) VALUES ('ACI2','ACI2Desc3', 7000)
SELECT * FROM #PivotExample
--Declare necessary variables
DECLARE #SQLQuery AS NVARCHAR(MAX)
DECLARE #PivotColumns AS NVARCHAR(MAX)
--Get unique values of pivot column
SELECT #PivotColumns= COALESCE(#PivotColumns + ',','') + QUOTENAME([Description])
FROM (SELECT DISTINCT [Description] FROM [dbo].#PivotExample) AS PivotExample
--SELECT #PivotColumns
--Create the dynamic query with all the values for
--pivot column at runtime
SET #SQLQuery =
N' -- Your pivoted result comes here
SELECT ID, ' + #PivotColumns + '
FROM
(
-- Source table should in a inner query
SELECT ID,[Description],[ClientId]
FROM #PivotExample
)AS P
PIVOT
(
-- Select the values from derived table P
SUM(ClientId)
FOR [Description] IN (' + #PivotColumns + ')
)AS PVTTable'
--SELECT #SQLQuery
--Execute dynamic query
EXEC sp_executesql #SQLQuery
Drop table #PivotExample
Fully generic way that will work in non-traditional MS SQL environments (e.g. Azure Synapse Analytics Serverless SQL Pools) - it's in a SPROC but no need to use as such...
-- DROP PROCEDURE IF EXISTS
if object_id('dbo.usp_generic_pivot') is not null
DROP PROCEDURE dbo.usp_generic_pivot
GO;
CREATE PROCEDURE dbo.usp_generic_pivot (
#source NVARCHAR (100), -- table or view object name
#pivotCol NVARCHAR (100), -- the column to pivot
#pivotAggCol NVARCHAR (100), -- the column with the values for the pivot
#pivotAggFunc NVARCHAR (20), -- the aggregate function to apply to those values
#leadCols NVARCHAR (100) -- comma seprated list of other columns to keep and order by
)
AS
BEGIN
DECLARE #pivotedColumns NVARCHAR(MAX)
DECLARE #tsql NVARCHAR(MAX)
SET #tsql = CONCAT('SELECT #pivotedColumns = STRING_AGG(qname, '','') FROM (SELECT DISTINCT QUOTENAME(', #pivotCol,') AS qname FROM ',#source, ') AS qnames')
EXEC sp_executesql #tsql, N'#pivotedColumns nvarchar(max) out', #pivotedColumns out
SET #tsql = CONCAT ( 'SELECT ', #leadCols, ',', #pivotedColumns,' FROM ',' ( SELECT ',#leadCols,',',
#pivotAggCol,',', #pivotCol, ' FROM ', #source, ') as t ',
' PIVOT (', #pivotAggFunc, '(', #pivotAggCol, ')',' FOR ', #pivotCol,
' IN (', #pivotedColumns,')) as pvt ',' ORDER BY ', #leadCols)
EXEC (#tsql)
END
GO;
-- TEST EXAMPLE
EXEC dbo.usp_generic_pivot
#source = '[your_db].[dbo].[form_answers]',
#pivotCol = 'question',
#pivotAggCol = 'answer',
#pivotAggFunc = 'MAX',
#leadCols = 'candidate_id, candidate_name'
GO;

Selecting all records in all tables of the Public Schema in PostgreSQL

I have several tables in my PostgreSQL database's Public Schema. The tables are named "projects_2019", "projects_2020", "projects_2021", etc. and have the same columns. The idea is that a new table will be added every year.
I would like to select all records in all of the tables whose name includes "projects_", how could I do this without naming each and every table name (since I don't know how many there will be in the future)?
Here's what I have so far:
WITH t as
(SELECT * FROM information_schema.tables WHERE table_schema = 'public' and table_name ~ 'projects_')
SELECT * FROM t
You can do it using dynamic SQL and information_schema. For Example:
-- Sample Data
CREATE TABLE table1 (
id int4 NULL,
caption text NULL
);
CREATE TABLE table2 (
id int4 NULL,
caption text NULL
);
CREATE TABLE table3 (
id int4 NULL,
caption text NULL
);
CREATE TABLE table4 (
id int4 NULL,
caption text NULL
);
INSERT INTO table1 (id, caption) VALUES (1, 'text1');
INSERT INTO table2 (id, caption) VALUES (2, 'text2');
INSERT INTO table3 (id, caption) VALUES (3, 'text3');
INSERT INTO table4 (id, caption) VALUES (4, 'text4');
-- create function sample:
CREATE OR REPLACE FUNCTION select_tables()
RETURNS table(id integer, caption text)
LANGUAGE plpgsql
AS $function$
declare
v_sql text;
v_union text;
begin
SELECT string_agg('select * from ' || table_schema || '.' || table_name, ' union all ')
into v_sql
FROM information_schema.tables WHERE table_schema = 'public' and table_name ~ 'table';
return query
execute v_sql;
end ;
$function$
;
-- selecting data:
select * from select_tables()
-- Result:
id caption
1 text1
2 text2
3 text3
4 text4
You can try like this:
FOR i IN SELECT table_name
FROM information_schema.tables
WHERE table_schema = 'public'
and table_name ~ 'projects_'
LOOP
sqlstr := sqlstr || format($$
UNION
SELECT name FROM %I
$$,
i.table_name);
END LOOP;
EXECUTE sqlstr;

t-sql select column names from all tables where there is at least 1 null value

Context: I am exploring a new database (in MS SQL server), and I want to know for each table, all columns that have null values.
I.e. result would look something like this:
table column nulls
Tbl1 Col1 8
I have found this code here on stackoverflow, that makes a table of table-columnnames - without the WHERE statement which is my addition.
I tried to filter for nulls in WHERE statement, but then the table ends up empty, and I see why - i am checking if the col name is actually null, and not its contents. But can't figure out how to proceed.
select schema_name(tab.schema_id) as schema_name,
tab.name as table_name,
col.name as column_name
from sys.tables as tab
inner join sys.columns as col
on tab.object_id = col.object_id
left join sys.types as t
on col.user_type_id = t.user_type_id
-- in this where statement, I am trying to filter for nulls, but i get an empty result. and i know there are nulls
where col.name is null
order by schema_name, table_name, column_id
I also tried this (see 4th line):
select schema_name(tab.schema_id) as schema_name,
tab.name as table_name,
col.name as column_name
,(select count(*) from tab.name where col.name is null) as countnulls
from sys.tables as tab
inner join sys.columns as col
on tab.object_id = col.object_id
left join sys.types as t
on col.user_type_id = t.user_type_id
order by schema_name, table_name, column_id
the last one returns an error "Invalid object name 'tab.name'."
column name can't be null but if you mean nullable column (column that accept null value) that has null value at least so you can use following statement:
declare #schema varchar(255), #table varchar(255), #col varchar(255), #cmd varchar(max)
DECLARE getinfo cursor for
SELECT schema_name(tab.schema_id) as schema_name,tab.name , col.name from sys.tables as tab
inner join sys.columns as col on tab.object_id = col.object_id
where col.is_nullable =1
order by schema_name(tab.schema_id),tab.name,col.name
OPEN getinfo
FETCH NEXT FROM getinfo into #schema,#table,#col
WHILE ##FETCH_STATUS = 0
BEGIN
set #schema = QUOTENAME(#schema)
set #table = QUOTENAME(#table)
set #col = QUOTENAME(#col)
SELECT #cmd = 'IF EXISTS (SELECT 1 FROM '+ #schema +'.'+ #table +' WHERE ' + #col + ' IS NULL) BEGIN SELECT '''+#schema+''' as schemaName, '''+#table+''' as tablename, '''+#col+''' as columnName, * FROM '+ #schema +'.'+ #table +' WHERE ' + #col + ' IS NULL end'
EXEC(#cmd)
FETCH NEXT FROM getinfo into #schema,#table,#col
END
CLOSE getinfo
DEALLOCATE getinfo
that use cursor on all nullable columns in every table in the Database then check if this column has at least one null value if yes will select schema Name, table name, column name and all records that has null value in this column
but if you want to get only count of nulls you can use the following statement:
declare #schema varchar(255), #table varchar(255), #col varchar(255), #cmd varchar(max)
DECLARE getinfo cursor for
SELECT schema_name(tab.schema_id) as schema_name,tab.name , col.name from sys.tables as tab
inner join sys.columns as col on tab.object_id = col.object_id
where col.is_nullable =1
order by schema_name(tab.schema_id),tab.name,col.name
OPEN getinfo
FETCH NEXT FROM getinfo into #schema,#table,#col
WHILE ##FETCH_STATUS = 0
BEGIN
set #schema = QUOTENAME(#schema)
set #table = QUOTENAME(#table)
set #col = QUOTENAME(#col)
SELECT #cmd = 'IF EXISTS (SELECT 1 FROM '+ #schema +'.'+ #table +' WHERE ' + #col + ' IS NULL) BEGIN SELECT '''+#schema+''' as schemaName, '''+#table+''' as tablename, '''+#col+''' as columnName, count(*) as nulls FROM '+ #schema +'.'+ #table +' WHERE ' + #col + ' IS NULL end'
EXEC(#cmd)
FETCH NEXT FROM getinfo into #schema,#table,#col
END
that use cursor on all nullable columns in every table in the Database then check if this column has at least one null value if yes will select schema Name, table name, column name and count all records that has null value in this column

How to check content loading status on a static database?

We have a static database we constantly update with loader scripts. These loader scripts get current information from third party sources, clean it and upload it to database.
I have already made some SQL scripts to ensure schemas and tables required exists. Now I'd like to check that each table has the expected row count.
I did something like this:
select case when count(*) = <someNumber>
then 'someSchema.someTable OK'
else 'someSchema.someTable BAD row count' end
from someSchema.someTable;
But doing these kind of queries for ~300 tables is cumbersome.
Now I was thinking maybe there's a way to have a table like:
create table expected_row_count (
schema_name varchar,
table_name varchar,
row_count bigint
);
And somehow test all listed tables and only output the ones that fail the count check. But I'm kind of missing now... Should I try to write a function? Can a table like this be used to build queries and execute them?
Whole credit goes to #a-horse_with*_no_name , I'm posting a reply for completeness:
Check row count
First let's create some data to test the query:
create schema if not exists data;
create table if not exists data.test1 (nothing int);
create table if not exists data.test2 (nothing int);
insert into data.test1 (nothing)
(select random() from generate_series(1, 28));
insert into data.test2 (nothing)
(select random() from generate_series(1, 55));
create table if not exists public.expected_row_count (
table_schema varchar not null default '',
table_name varchar not null default '',
row_count bigint not null default 0
);
insert into public.expected_row_count (table_schema, table_name, row_count) values
('data', 'test1', (select count(*) from data.test1)),
('data', 'test2', (select count(*) from data.test2))
;
Now the query to check the data:
select * from (
select
table_schema,
table_name,
(xpath('/row/cnt/text()', xml_count))[1]::text::int as row_count
from (
select
table_schema,
table_name,
query_to_xml(format('select count(*) as cnt from %I.%I', table_schema, table_name), false, true, '') as xml_count
from information_schema.tables
where table_schema = 'data' --<< change here for the schema you want
) infs ) as r
inner join expected_row_count erc
on r.table_schema = erc.table_schema
and r.table_name = erc.table_name
and r.row_count != erc.row_count
;
Previous query should give an empty results if all counts are ok, and the
tables with missing data if not. To check it, update the count for some
table on expected_row_count and re-run the query. For example:
update expected_row_count set row_count = 666 where table_name = 'test1';

Postgres find all rows in database tables matching criteria on a given column

I am trying to write sub-queries so that I search all tables for a column named id and since there are multiple tables with id column, I want to add the condition, so that id = 3119093.
My attempt was:
Select *
from information_schema.tables
where id = '3119093' and id IN (
Select table_name
from information_schema.columns
where column_name = 'id' );
This didn't work so I tried:
Select *
from information_schema.tables
where table_name IN (
Select table_name
from information_schema.columns
where column_name = 'id' and 'id' IN (
Select * from table_name where 'id' = 3119093));
This isn't the right way either. Any help would be appreciated. Thanks!
A harder attempt is:
CREATE OR REPLACE FUNCTION search_columns(
needle text,
haystack_tables name[] default '{}',
haystack_schema name[] default '{public}'
)
RETURNS table(schemaname text, tablename text, columnname text, rowctid text)
AS $$
begin
FOR schemaname,tablename,columnname IN
SELECT c.table_schema,c.table_name,c.column_name
FROM information_schema.columns c
JOIN information_schema.tables t ON
(t.table_name=c.table_name AND t.table_schema=c.table_schema)
WHERE (c.table_name=ANY(haystack_tables) OR haystack_tables='{}')
AND c.table_schema=ANY(haystack_schema)
AND t.table_type='BASE TABLE'
--AND c.column_name = "id"
LOOP
EXECUTE format('SELECT ctid FROM %I.%I WHERE cast(%I as text) like %L',
schemaname,
tablename,
columnname,
needle
) INTO rowctid;
IF rowctid is not null THEN
RETURN NEXT;
END IF;
END LOOP;
END;
$$ language plpgsql;
select * from search_columns('%3119093%'::varchar,'{}'::name[]) ;
The only problem is this code displays the table name and column name. I have to then manually enter
Select * from table_name where id = 3119093
where I got the table name from the code above.
I want to automatically implement returning rows from a table but I don't know how to get the table name automatically.
I took the time to make it work for you.
For starters, some information on what is going on inside the code.
Explanation
function takes two input arguments: column name and column value
it requires a created type that it will be returning a set of
first loop identifies tables that have a column name specified as the input argument
then it forms a query which aggregates all rows that match the input condition inside every table taken from step 3 with comparison based on ILIKE - as per your example
function goes into the second loop only if there is at least one row in currently visited table that matches specified condition (then the array is not null)
second loop unnests the array of rows that match the condition and for every element it puts it in the function output with RETURN NEXT rec clause
Notes
Searching with LIKE is inefficient - I suggest adding another input argument "column type" and restrict it in the lookup by adding a join to pg_catalog.pg_type table.
The second loop is there so that if more than 1 row is found for a particular table, then every row gets returned.
If you are looking for something else, like you need key-value pairs, not just the values, then you need to extend the function. You could for example build json format from rows.
Now, to the code.
Test case
CREATE TABLE tbl1 (col1 int, id int); -- does contain values
CREATE TABLE tbl2 (col1 int, col2 int); -- doesn't contain column "id"
CREATE TABLE tbl3 (id int, col5 int); -- doesn't contain values
INSERT INTO tbl1 (col1, id)
VALUES (1, 5), (1, 33), (1, 25);
Table stores data:
postgres=# select * From tbl1;
col1 | id
------+----
1 | 5
1 | 33
1 | 25
(3 rows)
Creating type
CREATE TYPE sometype AS ( schemaname text, tablename text, colname text, entirerow text );
Function code
CREATE OR REPLACE FUNCTION search_tables_for_column (
v_column_name text
, v_column_value text
)
RETURNS SETOF sometype
LANGUAGE plpgsql
STABLE
AS
$$
DECLARE
rec sometype%rowtype;
v_row_array text[];
rec2 record;
arr_el text;
BEGIN
FOR rec IN
SELECT
nam.nspname AS schemaname
, cls.relname AS tablename
, att.attname AS colname
, null::text AS entirerow
FROM
pg_attribute att
JOIN pg_class cls ON att.attrelid = cls.oid
JOIN pg_namespace nam ON cls.relnamespace = nam.oid
WHERE
cls.relkind = 'r'
AND att.attname = v_column_name
LOOP
EXECUTE format('SELECT ARRAY_AGG(row(tablename.*)::text) FROM %I.%I AS tablename WHERE %I::text ILIKE %s',
rec.schemaname, rec.tablename, rec.colname, quote_literal(concat('%',v_column_value,'%'))) INTO v_row_array;
IF v_row_array is not null THEN
FOR rec2 IN
SELECT unnest(v_row_array) AS one_row
LOOP
rec.entirerow := rec2.one_row;
RETURN NEXT rec;
END LOOP;
END IF;
END LOOP;
END
$$;
Exemplary call & output
postgres=# select * from search_tables_for_column('id','5');
schemaname | tablename | colname | entirerow
------------+-----------+---------+-----------
public | tbl1 | id | (1,5)
public | tbl1 | id | (1,25)
(2 rows)