How deep can we go in levels of nested tables in oracle 12c? - oracle12c

i am trying to do the folowing:
1) create or replace type transaction as object (date Date, description
varchar(30));
create or replace type T_transaction as table of transaction;
2) create or replace type account as object (id int, description varchar(30),
t_transaction T_transaction)
nested table t_transaction store as xxx1;
create or replace type T_account as table of account;
3) create or replace type user as object (id int, descr varchar(30), t_account
T_account)
nested table t_account store as xxx2;
create or replace type T_user as table of user;
4) create or replace table banks (name varchar(20), users T_user)
nested table users store as xxx3;
first 2 types were created successfully, but "create or replace type account..." is giving -> Warning: Type created with compilation errors.
is there an advice for creating such database using multiple level of nested tables ?

Edit:
I did some research on the subject (object nesting limitations) and here are my findings:
According to Database Limits,
every column of a nested table is in effect added to the columns of the host table and the maximum total number of columns in a table is 1000.
So this would be the official upper limit (in case every nested table had a single column).
However, when I did actual testing (on 11g and 12c), I weren't able to create a table with a nesting depth more than 50 because of error
ORA-00036: maximum number of recursive SQL levels (50) exceeded.
Thus I conclude that the maximum possible depth of nesting is 50.
Initial answer:
I am not aware of limits on objects nesting but I think they should be reasonably permissive.
Your code fails because you made a few mistakes:
1. Using type names as column names (date, t_account, etc.);
2. Using nested table clause in a wrong place;
The code should go like this:
create or replace type transaction_type as object (tx_date Date, description varchar2(30));
create or replace type transaction_tab as table of transaction_type;
create or replace type account_type as object (id int, description varchar(30),
transactions transaction_tab);
create or replace type account_tab as table of account_type;
create or replace type user_type as object (id int, descr varchar(30), accounts account_tab);
create or replace type user_tab as table of user_type;
CREATE table banks (name varchar(20), users user_tab)
nested table users store as xxx3 (
nested table accounts store as xxx2 (
nested table transactions store as xxx1
));
Checking
INSERT INTO banks VALUES (
'John', user_tab(
user_type(1
,'regular user'
, account_tab(
account_type(1
,'regular account'
, transaction_tab(transaction_type(
trunc(sysdate)
, 'regular transaction'))
))
)));
SQL> SELECT *FROM banks;
NAME
--------------------
USERS(ID, DESCR, ACCOUNTS(ID, DESCRIPTION, TRANSACTIONS(TX_DATE, DESCRIPTION)))
--------------------------------------------------------------------------------
John
USER_TAB(USER_TYPE(1, 'regular user', ACCOUNT_TAB(ACCOUNT_TYPE(1, 'regular accou
nt', TRANSACTION_TAB(TRANSACTION_TYPE('04-APR-18', 'regular transaction'))))))
Selecting nested table columns
SELECT b.name, u.id, u.descr, a.id, a.description
FROM banks b, table(b.users) u, table(u.accounts) a
WHERE u.descr = 'regular user' AND a.description = 'regular account'
NAME ID DESCR ID DESCRIPTION
----- --- ------------- --- ----------------
John 1 regular user 1 regular account

Related

How to work with data values formatted [{}, {}, {}]

I apologize if this is a simple question - I had some trouble even formatting the question when I was trying to Google for help!
In one of the tables I am working with, there's data value that looks like below:
Invoice ID
Status
Product List
1234
Processed
[{"product_id":463153},{"product_id":463165},{"product_id":463177},{"pid":463218}]
I want to count how many products each order has purchased. What is the proper syntax and way to count the values under "Product List" column? I'm aware that count() is wrong, and I need to maybe extract the data from the string value.
select invoice_id, count(Product_list)
from quote_table
where status = 'processed'
group by invoice_id
You can use a JSON function named: json_array_length and cast this column like a JSON data type (as long as possible), for example:
select invoice_id, json_array_length(Product_list::json) as count
from quote_table
where status = 'processed'
group by invoice_id;
invoice_id | count
------------+-------
1234 | 4
(1 row)
If you need to count a specific property of the json column, you can use the query below.
This query solves the problem by using create type, json_populate_recordset and subquery to count product_id inside json data.
drop type if exists count_product;
create type count_product as (product_id int);
select
t.invoice_id,
t.status,
(
select count(*) from json_populate_recordset(
null::count_product,
t.Product_list
)
where product_id is not null
) as count_produto_id
from (
-- symbolic data to use in query
select
1234 as invoice_id,
'processed' as status,
'[{"product_id":463153},{"product_id":463165},{"product_id":463177},{"pid":463218}]'::json as Product_list
) as t

PGSQL - How to efficiently flatten key/value table [duplicate]

Does any one know how to create crosstab queries in PostgreSQL?
For example I have the following table:
Section Status Count
A Active 1
A Inactive 2
B Active 4
B Inactive 5
I would like the query to return the following crosstab:
Section Active Inactive
A 1 2
B 4 5
Is this possible?
Install the additional module tablefunc once per database, which provides the function crosstab(). Since Postgres 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION IF NOT EXISTS tablefunc;
Improved test case
CREATE TABLE tbl (
section text
, status text
, ct integer -- "count" is a reserved word in standard SQL
);
INSERT INTO tbl VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7); -- ('C', 'Active') is missing
Simple form - not fit for missing attributes
crosstab(text) with 1 input parameter:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- needs to be "ORDER BY 1,2" here
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | 7 | -- !!
No need for casting and renaming.
Note the incorrect result for C: the value 7 is filled in for the first column. Sometimes, this behavior is desirable, but not for this use case.
The simple form is also limited to exactly three columns in the provided input query: row_name, category, value. There is no room for extra columns like in the 2-parameter alternative below.
Safe form
crosstab(text, text) with 2 input parameters:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- could also just be "ORDER BY 1" here
, $$VALUES ('Active'::text), ('Inactive')$$
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | | 7 -- !!
Note the correct result for C.
The second parameter can be any query that returns one row per attribute matching the order of the column definition at the end. Often you will want to query distinct attributes from the underlying table like this:
'SELECT DISTINCT attribute FROM tbl ORDER BY 1'
That's in the manual.
Since you have to spell out all columns in a column definition list anyway (except for pre-defined crosstabN() variants), it is typically more efficient to provide a short list in a VALUES expression like demonstrated:
$$VALUES ('Active'::text), ('Inactive')$$)
Or (not in the manual):
$$SELECT unnest('{Active,Inactive}'::text[])$$ -- short syntax for long lists
I used dollar quoting to make quoting easier.
You can even output columns with different data types with crosstab(text, text) - as long as the text representation of the value column is valid input for the target type. This way you might have attributes of different kind and output text, date, numeric etc. for respective attributes. There is a code example at the end of the chapter crosstab(text, text) in the manual.
db<>fiddle here
Effect of excess input rows
Excess input rows are handled differently - duplicate rows for the same ("row_name", "category") combination - (section, status) in the above example.
The 1-parameter form fills in available value columns from left to right. Excess values are discarded.
Earlier input rows win.
The 2-parameter form assigns each input value to its dedicated column, overwriting any previous assignment.
Later input rows win.
Typically, you don't have duplicates to begin with. But if you do, carefully adjust the sort order to your requirements - and document what's happening.
Or get fast arbitrary results if you don't care. Just be aware of the effect.
Advanced examples
Pivot on Multiple Columns using Tablefunc - also demonstrating mentioned "extra columns"
Dynamic alternative to pivot with CASE and GROUP BY
\crosstabview in psql
Postgres 9.6 added this meta-command to its default interactive terminal psql. You can run the query you would use as first crosstab() parameter and feed it to \crosstabview (immediately or in the next step). Like:
db=> SELECT section, status, ct FROM tbl \crosstabview
Similar result as above, but it's a representation feature on the client side exclusively. Input rows are treated slightly differently, hence ORDER BY is not required. Details for \crosstabview in the manual. There are more code examples at the bottom of that page.
Related answer on dba.SE by Daniel Vérité (the author of the psql feature):
How do I generate a pivoted CROSS JOIN where the resulting table definition is unknown?
SELECT section,
SUM(CASE status WHEN 'Active' THEN count ELSE 0 END) AS active, --here you pivot each status value as a separate column explicitly
SUM(CASE status WHEN 'Inactive' THEN count ELSE 0 END) AS inactive --here you pivot each status value as a separate column explicitly
FROM t
GROUP BY section
You can use the crosstab() function of the additional module tablefunc - which you have to install once per database. Since PostgreSQL 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION tablefunc;
In your case, I believe it would look something like this:
CREATE TABLE t (Section CHAR(1), Status VARCHAR(10), Count integer);
INSERT INTO t VALUES ('A', 'Active', 1);
INSERT INTO t VALUES ('A', 'Inactive', 2);
INSERT INTO t VALUES ('B', 'Active', 4);
INSERT INTO t VALUES ('B', 'Inactive', 5);
SELECT row_name AS Section,
category_1::integer AS Active,
category_2::integer AS Inactive
FROM crosstab('select section::text, status, count::text from t',2)
AS ct (row_name text, category_1 text, category_2 text);
DB Fiddle here:
Everything works: https://dbfiddle.uk/iKCW9Uhh
Without CREATE EXTENSION tablefunc; you get this error: https://dbfiddle.uk/j8W1CMvI
ERROR: function crosstab(unknown, integer) does not exist
LINE 4: FROM crosstab('select section::text, status, count::text fro...
^
HINT: No function matches the given name and argument types. You might need to add explicit type casts.
Solution with JSON aggregation:
CREATE TEMP TABLE t (
section text
, status text
, ct integer -- don't use "count" as column name.
);
INSERT INTO t VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7);
SELECT section,
(obj ->> 'Active')::int AS active,
(obj ->> 'Inactive')::int AS inactive
FROM (SELECT section, json_object_agg(status,ct) AS obj
FROM t
GROUP BY section
)X
Sorry this isn't complete because I can't test it here, but it may get you off in the right direction. I'm translating from something I use that makes a similar query:
select mt.section, mt1.count as Active, mt2.count as Inactive
from mytable mt
left join (select section, count from mytable where status='Active')mt1
on mt.section = mt1.section
left join (select section, count from mytable where status='Inactive')mt2
on mt.section = mt2.section
group by mt.section,
mt1.count,
mt2.count
order by mt.section asc;
The code I'm working from is:
select m.typeID, m1.highBid, m2.lowAsk, m1.highBid - m2.lowAsk as diff, 100*(m1.highBid - m2.lowAsk)/m2.lowAsk as diffPercent
from mktTrades m
left join (select typeID,MAX(price) as highBid from mktTrades where bid=1 group by typeID)m1
on m.typeID = m1.typeID
left join (select typeID,MIN(price) as lowAsk from mktTrades where bid=0 group by typeID)m2
on m1.typeID = m2.typeID
group by m.typeID,
m1.highBid,
m2.lowAsk
order by diffPercent desc;
which will return a typeID, the highest price bid and the lowest price asked and the difference between the two (a positive difference would mean something could be bought for less than it can be sold).
There's a different dynamic method that I've devised, one that employs a dynamic rec. type (a temp table, built via an anonymous procedure) & JSON. This may be useful for an end-user who can't install the tablefunc/crosstab extension, but can still create temp tables or run anon. proc's.
The example assumes all the xtab columns are the same type (INTEGER), but the # of columns is data-driven & variadic. That said, JSON aggregate functions do allow for mixed data types, so there's potential for innovation via the use of embedded composite (mixed) types.
The real meat of it can be reduced down to one step if you want to statically define the rec. type inside the JSON recordset function (via nested SELECTs that emit a composite type).
dbfiddle.uk
https://dbfiddle.uk/N1EzugHk
Crosstab function is available under the tablefunc extension. You'll have to create this extension one time for the database.
CREATE EXTENSION tablefunc;
You can use the below code to create pivot table using cross tab:
create table test_Crosstab( section text,
status text,
count numeric)
insert into test_Crosstab values ( 'A','Active',1)
,( 'A','Inactive',2)
,( 'B','Active',4)
,( 'B','Inactive',5)
select * from crosstab(
'select section
,status
,count
from test_crosstab'
)as ctab ("Section" text,"Active" numeric,"Inactive" numeric)

Make rows to Columns in Postgresql [duplicate]

Does any one know how to create crosstab queries in PostgreSQL?
For example I have the following table:
Section Status Count
A Active 1
A Inactive 2
B Active 4
B Inactive 5
I would like the query to return the following crosstab:
Section Active Inactive
A 1 2
B 4 5
Is this possible?
Install the additional module tablefunc once per database, which provides the function crosstab(). Since Postgres 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION IF NOT EXISTS tablefunc;
Improved test case
CREATE TABLE tbl (
section text
, status text
, ct integer -- "count" is a reserved word in standard SQL
);
INSERT INTO tbl VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7); -- ('C', 'Active') is missing
Simple form - not fit for missing attributes
crosstab(text) with 1 input parameter:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- needs to be "ORDER BY 1,2" here
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | 7 | -- !!
No need for casting and renaming.
Note the incorrect result for C: the value 7 is filled in for the first column. Sometimes, this behavior is desirable, but not for this use case.
The simple form is also limited to exactly three columns in the provided input query: row_name, category, value. There is no room for extra columns like in the 2-parameter alternative below.
Safe form
crosstab(text, text) with 2 input parameters:
SELECT *
FROM crosstab(
'SELECT section, status, ct
FROM tbl
ORDER BY 1,2' -- could also just be "ORDER BY 1" here
, $$VALUES ('Active'::text), ('Inactive')$$
) AS ct ("Section" text, "Active" int, "Inactive" int);
Returns:
Section | Active | Inactive
---------+--------+----------
A | 1 | 2
B | 4 | 5
C | | 7 -- !!
Note the correct result for C.
The second parameter can be any query that returns one row per attribute matching the order of the column definition at the end. Often you will want to query distinct attributes from the underlying table like this:
'SELECT DISTINCT attribute FROM tbl ORDER BY 1'
That's in the manual.
Since you have to spell out all columns in a column definition list anyway (except for pre-defined crosstabN() variants), it is typically more efficient to provide a short list in a VALUES expression like demonstrated:
$$VALUES ('Active'::text), ('Inactive')$$)
Or (not in the manual):
$$SELECT unnest('{Active,Inactive}'::text[])$$ -- short syntax for long lists
I used dollar quoting to make quoting easier.
You can even output columns with different data types with crosstab(text, text) - as long as the text representation of the value column is valid input for the target type. This way you might have attributes of different kind and output text, date, numeric etc. for respective attributes. There is a code example at the end of the chapter crosstab(text, text) in the manual.
db<>fiddle here
Effect of excess input rows
Excess input rows are handled differently - duplicate rows for the same ("row_name", "category") combination - (section, status) in the above example.
The 1-parameter form fills in available value columns from left to right. Excess values are discarded.
Earlier input rows win.
The 2-parameter form assigns each input value to its dedicated column, overwriting any previous assignment.
Later input rows win.
Typically, you don't have duplicates to begin with. But if you do, carefully adjust the sort order to your requirements - and document what's happening.
Or get fast arbitrary results if you don't care. Just be aware of the effect.
Advanced examples
Pivot on Multiple Columns using Tablefunc - also demonstrating mentioned "extra columns"
Dynamic alternative to pivot with CASE and GROUP BY
\crosstabview in psql
Postgres 9.6 added this meta-command to its default interactive terminal psql. You can run the query you would use as first crosstab() parameter and feed it to \crosstabview (immediately or in the next step). Like:
db=> SELECT section, status, ct FROM tbl \crosstabview
Similar result as above, but it's a representation feature on the client side exclusively. Input rows are treated slightly differently, hence ORDER BY is not required. Details for \crosstabview in the manual. There are more code examples at the bottom of that page.
Related answer on dba.SE by Daniel Vérité (the author of the psql feature):
How do I generate a pivoted CROSS JOIN where the resulting table definition is unknown?
SELECT section,
SUM(CASE status WHEN 'Active' THEN count ELSE 0 END) AS active, --here you pivot each status value as a separate column explicitly
SUM(CASE status WHEN 'Inactive' THEN count ELSE 0 END) AS inactive --here you pivot each status value as a separate column explicitly
FROM t
GROUP BY section
You can use the crosstab() function of the additional module tablefunc - which you have to install once per database. Since PostgreSQL 9.1 you can use CREATE EXTENSION for that:
CREATE EXTENSION tablefunc;
In your case, I believe it would look something like this:
CREATE TABLE t (Section CHAR(1), Status VARCHAR(10), Count integer);
INSERT INTO t VALUES ('A', 'Active', 1);
INSERT INTO t VALUES ('A', 'Inactive', 2);
INSERT INTO t VALUES ('B', 'Active', 4);
INSERT INTO t VALUES ('B', 'Inactive', 5);
SELECT row_name AS Section,
category_1::integer AS Active,
category_2::integer AS Inactive
FROM crosstab('select section::text, status, count::text from t',2)
AS ct (row_name text, category_1 text, category_2 text);
DB Fiddle here:
Everything works: https://dbfiddle.uk/iKCW9Uhh
Without CREATE EXTENSION tablefunc; you get this error: https://dbfiddle.uk/j8W1CMvI
ERROR: function crosstab(unknown, integer) does not exist
LINE 4: FROM crosstab('select section::text, status, count::text fro...
^
HINT: No function matches the given name and argument types. You might need to add explicit type casts.
Solution with JSON aggregation:
CREATE TEMP TABLE t (
section text
, status text
, ct integer -- don't use "count" as column name.
);
INSERT INTO t VALUES
('A', 'Active', 1), ('A', 'Inactive', 2)
, ('B', 'Active', 4), ('B', 'Inactive', 5)
, ('C', 'Inactive', 7);
SELECT section,
(obj ->> 'Active')::int AS active,
(obj ->> 'Inactive')::int AS inactive
FROM (SELECT section, json_object_agg(status,ct) AS obj
FROM t
GROUP BY section
)X
Sorry this isn't complete because I can't test it here, but it may get you off in the right direction. I'm translating from something I use that makes a similar query:
select mt.section, mt1.count as Active, mt2.count as Inactive
from mytable mt
left join (select section, count from mytable where status='Active')mt1
on mt.section = mt1.section
left join (select section, count from mytable where status='Inactive')mt2
on mt.section = mt2.section
group by mt.section,
mt1.count,
mt2.count
order by mt.section asc;
The code I'm working from is:
select m.typeID, m1.highBid, m2.lowAsk, m1.highBid - m2.lowAsk as diff, 100*(m1.highBid - m2.lowAsk)/m2.lowAsk as diffPercent
from mktTrades m
left join (select typeID,MAX(price) as highBid from mktTrades where bid=1 group by typeID)m1
on m.typeID = m1.typeID
left join (select typeID,MIN(price) as lowAsk from mktTrades where bid=0 group by typeID)m2
on m1.typeID = m2.typeID
group by m.typeID,
m1.highBid,
m2.lowAsk
order by diffPercent desc;
which will return a typeID, the highest price bid and the lowest price asked and the difference between the two (a positive difference would mean something could be bought for less than it can be sold).
There's a different dynamic method that I've devised, one that employs a dynamic rec. type (a temp table, built via an anonymous procedure) & JSON. This may be useful for an end-user who can't install the tablefunc/crosstab extension, but can still create temp tables or run anon. proc's.
The example assumes all the xtab columns are the same type (INTEGER), but the # of columns is data-driven & variadic. That said, JSON aggregate functions do allow for mixed data types, so there's potential for innovation via the use of embedded composite (mixed) types.
The real meat of it can be reduced down to one step if you want to statically define the rec. type inside the JSON recordset function (via nested SELECTs that emit a composite type).
dbfiddle.uk
https://dbfiddle.uk/N1EzugHk
Crosstab function is available under the tablefunc extension. You'll have to create this extension one time for the database.
CREATE EXTENSION tablefunc;
You can use the below code to create pivot table using cross tab:
create table test_Crosstab( section text,
status text,
count numeric)
insert into test_Crosstab values ( 'A','Active',1)
,( 'A','Inactive',2)
,( 'B','Active',4)
,( 'B','Inactive',5)
select * from crosstab(
'select section
,status
,count
from test_crosstab'
)as ctab ("Section" text,"Active" numeric,"Inactive" numeric)

Can the categories in the postgres tablefunc crosstab() function be integers?

It's all in the title. Documentation has something like this:
SELECT *
FROM crosstab('...') AS ct(row_name text, category_1 text, category_2 text);
I have two tables, lab_tests and lab_tests_results. All of the lab_tests_results rows are tied to the primary key id integer in the lab_tests table. I'm trying to make a pivot table where the lab tests (identified by an integer) are row headers and the respective results are in the table. I can't get around a syntax error at or around the integer.
Is this possible with the current set up? Am I missing something in the documentation? Or do I need to perform an inner join of sorts to make the categories strings? Or modify the lab_tests_results table to use a text identifier for the lab tests?
Thanks for the help, all. Much appreciated.
Edit: Got it figured out with the help of Dmitry. He had the data layout figured out, but I was unclear on what kind of output I needed. I was trying to get the pivot table to be based on batch_id numbers in the lab_tests_results table. Had to hammer out the base query and casting data types.
SELECT *
FROM crosstab('SELECT lab_tests_results.batch_id, lab_tests.test_name, lab_tests_results.test_result::FLOAT
FROM lab_tests_results, lab_tests
WHERE lab_tests.id=lab_tests_results.lab_test AND (lab_tests.test_name LIKE ''Test Name 1'' OR lab_tests.test_name LIKE ''Test Name 2'')
ORDER BY 1,2'
) AS final_result(batch_id VARCHAR, test_name_1 FLOAT, test_name_2 FLOAT);
This provides a pivot table from the lab_tests_results table like below:
batch_id |test_name_1 |test_name_2
---------------------------------------
batch1 | result1 | <null>
batch2 | result2 | result3
If I understand correctly your tables look something like this:
CREATE TABLE lab_tests (
id INTEGER PRIMARY KEY,
name VARCHAR(500)
);
CREATE TABLE lab_tests_results (
id INTEGER PRIMARY KEY,
lab_tests_id INTEGER REFERENCES lab_tests (id),
result TEXT
);
And your data looks something like this:
INSERT INTO lab_tests (id, name)
VALUES (1, 'test1'),
(2, 'test2');
INSERT INTO lab_tests_results (id, lab_tests_id, result)
VALUES (1,1,'result1'),
(2,1,'result2'),
(3,2,'result3'),
(4,2,'result4'),
(5,2,'result5');
First of all crosstab is part of tablefunc, you need to enable it:
CREATE EXTENSION tablefunc;
You need to run it one per database as per this answer.
The final query will look like this:
SELECT *
FROM crosstab(
'SELECT lt.name::TEXT, lt.id, ltr.result
FROM lab_tests AS lt
JOIN lab_tests_results ltr ON ltr.lab_tests_id = lt.id'
) AS ct(test_name text, result_1 text, result_2 text, result_3 text);
Explanation:
The crosstab() function takes a text of a query which should return 3 columns; (1) a column for name of a group, (2) a column for grouping, (3) the value. The wrapping query just selects all the values those crosstab() returns and defines the list of columns after (the part after AS). First is the category name (test_name) and then the values (result_1, result_2). In my query I'll get up to 3 results. If I have more then 3 results then I won't see them, If I have less then 3 results I'll get nulls.
The result for this query is:
test_name |result_1 |result_2 |result_3
---------------------------------------
test1 |result1 |result2 |<null>
test2 |result3 |result4 |result5

Dynamically Buld the Statement

I want dynamically search condition.
This is my table(This is generated dynamically ) this is not a physical table.
id Tablename columnname Value |
1 Company Company_name Microsoft |
2 Address Pcity CA |
3 Phone Pnumber 100-4582 |
I want search the Value in the particular table , In this tables are already in the database(Company,Address,Phone). dynamically pass the tablename and columnname and search the Value.
Ex
Select c.Company_name from Company c join Address a on
a.companyid=c.companyid join phone p on p.companyid=c.companyid
where 1=1 and c.company_name like '%Microsoft%' and a.Pcity Like
'%CA%' and p.Pnumber like '%100-4582%'
I want dynamically buld the query and search the condition in the Value column.
How can I do this ..
Thanks.
what i understood is basically you want to make dynamic query, so i am providing a sample for you
create proc dummy_proc
#arg1 varchar(50),
#arg2 int
as
Declare #S varchar(max)
Set #S='select * from tablename where 1=1'
if #arg1<>'' then
set #s=#s+ 'and column1 like''%'+#arg1+%'''
Execute(#S)
hope it helps