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What are differences between SQL queries?
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Closed 4 years ago.
This syntax is valid for PostgreSQL:
select T from table_name as T
T seems to become a CSV list of values from all columns in table_name. select T from table_name as T works, and, for that matter, select table_name from table_name. Where is this syntax documented, and what is the datatype of T?
This syntax is not in SQL Server, and (AFAIK) does not exist in any other SQL variant.
If you create a table, Postgres creates a type with the same name in the background. The table is then essentially a "list of that type".
Postgres also allows to reference a complete row as a single "record" - a value built from multiple columns. Those records can be created dynamically through a row constructor.
Each row in a the result of a SELECT statement is implicitly assigned a TYPE - if the row comes from a single table, it's the table's type. Otherwise it's an anonymous type.
When you use the table name in a place where a column would be allowed it references the full row as a single record. If the table is aliased in the select, the type of that record is still the table's type.
So the statement:
select T
from table_name as T;
returns a result with a single column which is a record (of the table's type) containing each column of the table as a field. The default output format of a record is a comma separated list of the values enclosed in parentheses.
Assuming table_name has three columns c1, c2 and c3 the following would essentially do the same thing:
select row(c1, c2, c3)
from table_name;
Note that a record reference can also be used in comparisons, e.g. finding rows that are different between two tables can be done in the following manner
select *
from table_one t1
full outer join table_two t2 on t1.id = t2.id
where t1 <> t2;
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sql server 2008 management studio not checking the syntax of my query
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Closed 1 year ago.
I have the following select:
SELECT DISTINCT pl
FROM [dbo].[VendorPriceList] h
WHERE PartNumber IN (SELECT DISTINCT PartNumber
FROM [dbo].InvoiceData
WHERE amount > 10
AND invoiceDate > DATEADD(yyyy, -1, CURRENT_TIMESTAMP)
UNION
SELECT DISTINCT PartNumber
FROM [dbo].VendorDeals)
The issue here is that the table [dbo].VendorDeals has NO column PartNumber, however no error is detected and the query works with the first part of the union.
Even more, IntelliSense also allows and recognize PartNumber. This fails only when inside a complex statement.
It is pretty obvious that if you qualify column names, the mistake will be evident.
This isn't a bug in SQL Server/the T-SQL dialect parsing, no, this is working exactly as intended. The problem, or bug, is in your T-SQL; specifically because you haven't qualified your columns. As I don't have the definition of your table, I'm going to provide sample DDL first:
CREATE TABLE dbo.Table1 (MyColumn varchar(10), OtherColumn int);
CREATE TABLE dbo.Table2 (YourColumn varchar(10) OtherColumn int);
And then an example that is similar to your query:
SELECT MyColumn
FROM dbo.Table1
WHERE MyColumn IN (SELECT MyColumn FROM dbo.Table2);
This, firstly, will parse; it is a valid query. Secondly, provided that dbo.Table2 contains at least one row, then every row from table dbo.Table1 will be returned where MyColumn has a non-NULL value. Why? Well, let's qualify the column with table's name as SQL Server would parse them:
SELECT Table1.MyColumn
FROM dbo.Table1
WHERE Table1.MyColumn IN (SELECT Table1.MyColumn FROM dbo.Table2);
Notice that the column inside the IN is also referencing Table1, not Table2. By default if a column has it's alias omitted in a subquery it will be assumed to be referencing the table(s) defined in that subquery. If, however, none of the tables in the sub query have a column by that name, then it will be assumed to reference a table where that column does exist; in this case Table1.
Let's, instead, take a different example, using the other column in the tables:
SELECT OtherColumn
FROM dbo.Table1
WHERE OtherColumn IN (SELECT OtherColumn FROM dbo.Table2);
This would be parsed as the following:
SELECT Table1.OtherColumn
FROM dbo.Table1
WHERE Table1.OtherColumn IN (SELECT Table2.OtherColumn FROM dbo.Table2);
This is because OtherColumn exists in both tables. As, in the subquery, OtherColumn isn't qualified it is assumed the column wanted is the one in the table defined in the same scope, Table2.
So what is the solution? Alias and qualify your columns:
SELECT T1.MyColumn
FROM dbo.Table1 T1
WHERE T1.MyColumn IN (SELECT T2.MyColumn FROM dbo.Table2 T2);
This will, unsurprisingly, error as Table2 has no column MyColumn.
Personally, I suggest that unless you have only one table being referenced in a query, you alias and qualify all your columns. This not only ensures that the wrong column can't be referenced (such as in a subquery) but also means that other readers know exactly what columns are being referenced. It also stops failures in the future. I have honestly lost count how many times over years I have had a process fall over due to the "ambiguous column" error, due to a table's definition being changed and a query referencing the table wasn't properly qualified by the developer...
It is often particularly handy to LEFT JOIN to a LATERAL subquery, so that source rows will appear in the result even if the LATERAL subquery produces no rows for them. For example, if get_product_names() returns the names of products made by a manufacturer, but some manufacturers in our table currently produce no products, we could find out which ones those are like this:
SELECT m.name
FROM manufacturers m LEFT JOIN LATERAL get_product_names(m.id) pname ON true
WHERE pname IS NULL;
All contents extract from PostgreSQL manual. LINK
Now I finally probably get what does LATERAL mean. In this case,
Overall I am Not sure get_product_names is a table or function. The following is my understanding.
A: get_product_names(m.id) is a function, and using m.id as a input parameter returns a table. The return table alias as pname. Overall it's a table m join a null (where condition) table.
B: get_product_names is a table, table m left join table get_product_names on m.id. pname is alias for get_product_names. Overall it's a table m join a null (where condition) table.
get_product_names is a table function (also known as set returning function or SRF in PostgreSQL slang). Such a function does not necessarily return a single result row, but arbitrarily many rows.
Since the result of such a function is a table, you typically use it in SQL statements where you would use a table, that is in the FROM clause.
A simple example is
SELECT * FROM generate_series(1, 5);
generate_series
-----------------
1
2
3
4
5
(5 rows)
You can also use normal functions in this way, they are then treated as a table function that returns exactly one row.
Is it possible to SELECT * but without n-th column, for example 2nd?
I have some view that have 4 and 5 columns (each has different column names, except for the 2nd column), but I do not want to show the second column.
SELECT * -- how to prevent 2nd column to be selected?
FROM view4
WHERE col2 = 'foo';
SELECT * -- how to prevent 2nd column to be selected?
FROM view5
WHERE col2 = 'foo';
without having to list all the columns (since they all have different column name).
The real answer is that you just can not practically (See LINK). This has been a requested feature for decades and the developers refuse to implement it. The best practice is to mention the column names instead of *. Using * in itself a source of performance penalties though.
However, in case you really need to use it, you might need to select the columns directly from the schema -> check LINK. Or as the below example using two PostgreSQL built-in functions: ARRAY and ARRAY_TO_STRING. The first one transforms a query result into an array, and the second one concatenates array components into a string. List components separator can be specified with the second parameter of the ARRAY_TO_STRING function;
SELECT 'SELECT ' ||
ARRAY_TO_STRING(ARRAY(SELECT COLUMN_NAME::VARCHAR(50)
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME='view4' AND
COLUMN_NAME NOT IN ('col2')
ORDER BY ORDINAL_POSITION
), ', ') || ' FROM view4';
where strings are concatenated with the standard operator ||. The COLUMN_NAME data type is information_schema.sql_identifier. This data type requires explicit conversion to CHAR/VARCHAR data type.
But that is not recommended as well, What if you add more columns in the long run but they are not necessarily required for that query?
You would start pulling more column than you need.
What if the select is part of an insert as in
Insert into tableA (col1, col2, col3.. coln) Select everything but 2 columns FROM tableB
The column match will be wrong and your insert will fail.
It's possible but I still recommend writing every needed column for every select written even if nearly every column is required.
Conclusion:
Since you are already using a VIEW, the simplest and most reliable way is to alter you view and mention the column names, excluding your 2nd column..
-- my table with 2 rows and 4 columns
DROP TABLE IF EXISTS t_target_table;
CREATE TEMP TABLE t_target_table as
SELECT 1 as id, 1 as v1 ,2 as v2,3 as v3,4 as v4
UNION ALL
SELECT 2 as id, 5 as v1 ,-6 as v2,7 as v3,8 as v4
;
-- my computation and stuff that i have to messure, any logic could be done here !
DROP TABLE IF EXISTS t_processing;
CREATE TEMP TABLE t_processing as
SELECT *, md5(t_target_table::text) as row_hash, case when v2 < 0 THEN true else false end as has_negative_value_in_v2
FROM t_target_table
;
-- now we want to insert that stuff into the t_target_table
-- this is standard
-- INSERT INTO t_target_table (id, v1, v2, v3, v4) SELECT id, v1, v2, v3, v4 FROM t_processing;
-- this is andvanced ;-)
INSERT INTO t_target_table
-- the following row select only the columns that are pressent in the target table, and ignore the others.
SELECT r.* FROM (SELECT to_jsonb(t_processing) as d FROM t_processing) t JOIN LATERAL jsonb_populate_record(NULL::t_target_table, d) as r ON TRUE
;
-- WARNING : you need a object that represent the target structure, an exclusion of a single column is not possible
For columns col1, col2, col3 and col4 you will need to request
SELECT col1, col3, col4 FROM...
to omit the second column. Requesting
SELECT *
will get you all the columns
I am trying to find the number of distinct values in each column of a table. Declaratively that is:
for each column of table xyz
run_query("SELECT COUNT(DISTINCT column) FROM xyz")
Finding the column names of a table is shown here.
SELECT column_name
FROM information_schema.columns
WHERE table_name=xyz
However, I don't manage to merge the count query inside. I tried various queries, this one:
SELECT column_name, thecount
FROM information_schema.columns,
(SELECT COUNT(DISTINCT column_name) FROM myTable) AS thecount
WHERE table_name=myTable
is syntactically not allowed (reference to column_name in the nested query not allowed).
This one seems erroneous too (timeout):
SELECT column_name, count(distinct column_name)
FROM information_schema.columns, myTable
WHERE table_name=myTable
What is the right way to get the number of distinct values for each column of a table with one query?
Article SQL to find the number of distinct values in a column talks about a fixed column only.
In general, SQL expects the names of items (fields, tables, roles, indices, constraints, etc) in a statement to be constant. That many database systems let you examine the structure through something like information_schema does not mean you can plug that data into the running statement.
You can however use the information_schema to construct new SQL statements that you execute separately.
First consider your original problem.
CREATE TABLE foo (a numeric, b numeric, c numeric);
INSERT INTO foo(a,b,c)
VALUES (1,1,1), (1,1,2), (1,1,3), (1,2,1), (1,2,2);
SELECT COUNT(DISTINCT a) "distinct a",
COUNT(DISTINCT b) "distinct b",
COUNT(DISTINCT c) "distinct c"
FROM foo;
If you know the name of all of your columns when you are writing the query, that is sufficient.
If you are seeking data for an arbitrary table, you need to construct the SQL statement via SQL (I've added plenty of whitespace so you can see the different levels involved):
SELECT 'SELECT ' || STRING_AGG( 'COUNT (DISTINCT '
|| column_name
|| ') "'
|| column_name
|| '"',
',')
|| ' FROM foo;'
FROM information_schema.columns
WHERE table_name='foo';
That however is just the text of the necessary SQL statement. Depending on how you are accessing Postgresql, it might be easy for you to feed that into a new query, or if you are keeping everything inside Postgresql, then you will have to resort to one of the integrated procedural languages. An excellent (though complex,) discussion of the issues may provide guidance.
I have the following schema dataset which i want to transform into a table that can be exported to SQL. I am using HIVE. Input as follows
call_id,stat1,stat2,stat3
1,a,b,c,
2,x,y,z,
3,d,e,f,
1,j,k,l,
The output table needs to have call_id as its primary key so it needs to be unique. The output schema should be
call_id,stat2,stat3,
1,b,c, or (1,k,l)
2,y,z,
3,e,f,
The problem is that when i use the keyword DISTINCT in the HIVE query, the DISTINCT applies to the all the colums combined. I want to apply the DISTINCT operation only to the call_id. Something on the lines of
SELECT DISTINCT(call_id), stat2,stat3 from intable;
However this is not valid in HIVE(I am not well-versed in SQL either).
The only legal query seems to be
SELECT DISTINCT call_id, stat2,stat3 from intable;
But this returns multiple rows with same call_id as the other columns are different and the row on the whole is distinct.
NOTE: There is no arithmetic relation between a,b,c,x,y,z, etc. So any trick of averaging or summing is not viable.
Any ideas how i can do this?
One quick idea,not the best one, but will do the work-
hive>create table temp1(a int,b string);
hive>insert overwrite table temp1
select call_id,max(concat(stat1,'|',stat2,'|',stat3)) from intable group by call_id;
hive>insert overwrite table intable
select a,split(b,'|')[0],split(b,'|')[1],split(b,'|')[2] from temp1;
,,I want to apply the DISTINCT operation only to the call_id"
But how will then Hive know which row to eliminate?
Without knowing the amount of data / size of the stat fields you have, the following query can the job:
select distinct i1.call_id, i1.stat2, i1.stat3 from (
select call_id, MIN(concat(stat1, stat2, stat3)) as smin
from intable group by call_id
) i2 join intable i1 on i1.call_id = i2.call_id
AND concat(i1.stat1, i1.stat2, i1.stat3) = i2.smin;