Sorry for the lack of info -- SQL Server 2008.
I'm struggling to get a couple of column values from table A into a new row in table B for each row in A where a column isn't null.
Table A's structure is as:
UserID | ClientUserID | ClientSessionID | [and a load of other irrelevant columns)
Table B:
UserID | Name | Value
I want to create rows in table B for each non-null ClientUserID or ClientSessionID in A - using the column name as B's "Name", and column value as "B's Value".
I'm struggling to write my "unpivot" statement - just getting the syntax correct! I'm trying to follow along with some samples but can't
Here's my SQL query so far - any further help would be appreciated (just getting this SELECT is frustrating me, let alone doing the insert!)
SELECT UserID, ClientUserID, ClientSessionID FROM websiteuser WHERE ClientSessionID IS NOT null
This gives me the rows that I need to perform actions upon -- but I just can't get the syntax correct for UNPIVOTing this data and turning it into my insert.
You can unpivot records in this fashion by using UNION to get each new row:
INSERT INTO TableB (UserID, Name, Value)
SELECT UserID, 'ClientUserID' AS Name, ClientUserID AS Value
FROM TableA
WHERE ClientUserID IS NOT NULL
UNION ALL
SELECT UserID, 'ClientSessionID' AS Name, ClientSessionID AS Value
FROM TableA
WHERE ClientSessionID IS NOT NULL
I am using UNION ALL in this case as UNION implies a DISTINCT operation across the entire set, which should normally be unnecessary when pivoting unique records.
If your ClientUserID and ClientSessionID columns are not the same datatype, you may have to cast one or both to the same.
Related
Let's assume I run the following in SQLite:
CREATE TABLE my_table
(
id INTEGER PRIMARY KEY,
NAME VARCHAR(20),
date DATE,
num INTEGER,
important VARCHAR(20)
);
INSERT INTO my_table (NAME, date, num, important)
VALUES ('A', '2000-01-01', 10, 'Important 1');
INSERT INTO my_table (NAME, date, num, important)
VALUES ('A', '2000-02-01', 20, 'Important 2');
INSERT INTO my_table (NAME, date, num, important)
VALUES ('A', '1999-12-01', 30, 'Important 3');
The table looks like this:
id
NAME
date
num
important
1
A
2000-01-01
10
Important 1
2
A
2000-02-01
20
Important 2
3
A
1999-12-01
30
Important 3
If I execute:
SELECT id
FROM my_table
GROUP BY NAME;
the results are:
+----+
| id |
+----+
| 1 |
+----+
If I execute:
SELECT id, MAX(date)
FROM my_table
GROUP BY NAME;
The results are:
+----+------------+
| id | max(date) |
+----+------------+
| 2 | 2000-02-01 |
+----+------------+
And if I execute:
SELECT id,
MAX(date),
MAX(num)
FROM my_table
GROUP BY NAME;
The results are:
+----+------------+----------+
| id | max(date) | max(num) |
+----+------------+----------+
| 3 | 2000-02-01 | 30 |
+----+------------+----------+
My question is, is this well defined? Specifically, am I guaranteed to always get id = 2 when doing the second query (with the single Max(date) aggregate), or is this just a side effect of how SQLite is likely ordering the table to grab the Max before grouping?
I ask this because I specifically do want id = 2. I will then execute another query that selects the important field for that row (for my actual problem the first query would return multiple ids and I'd select all important fields for all those rows at once.
Additionally, this is all happening in an iOS Core Data query, so I'm not able to do more complicated subqueries. If I knew that the ordering of a GROUP BY is defined by an aggregate then I'd feel pretty confident my queries wouldn't break (until Apple moves away from SQLite for Core Data).
Thanks!
From the Sqlite manual
2.5. Bare columns in an aggregate query
The usual case is that all column names in an aggregate query are either arguments to aggregate functions or else appear in the GROUP BY clause. A result column which contains a column name that is not within an aggregate function and that does not appear in the GROUP BY clause (if one exists) is called a "bare" column. Example:
SELECT a, b, sum(c) FROM tab1 GROUP BY a;
In the query above, the "a" column is part of the GROUP BY clause and so each row of the output contains one of the distinct values for "a". The "c" column is contained within the sum() aggregate function and so that output column is the sum of all "c" values in rows that have the same value for "a". But what is the result of the bare column "b"? The answer is that the "b" result will be the value for "b" in one of the input rows that form the aggregate. The problem is that you usually do not know which input row is used to compute "b", and so in many cases the value for "b" is undefined.
Special processing occurs when the aggregate function is either min() or max(). Example:
SELECT a, b, max(c) FROM tab1 GROUP BY a;
When the min() or max() aggregate functions are used in an aggregate query, all bare columns in the result set take values from the input row which also contains the minimum or maximum. So in the query above, the value of the "b" column in the output will be the value of the "b" column in the input row that has the largest "c" value. There is still an ambiguity if two or more of the input rows have the same minimum or maximum value or if the query contains more than one min() and/or max() aggregate function. Only the built-in min() and max() functions work this way.
If bare columns appear in an aggregate query that lacks a GROUP BY clause, and the number of input rows is zero, then the values of the bare columns are arbitrary. For example, in this query:
SELECT count(*), b FROM tab1;
If the tab1 table contains no rows (of count(*) evaluates to 0) then the bare column "b" will have an arbitrary and meaningless value.
Most other SQL database engines disallow bare columns. If you include a bare column in a query, other database engines will usually raise an error. The ability to include bare columns in a query is an SQLite-specific extension.
https://www.sqlite.org/lang_select.html
am I guaranteed to always get id = 2 when doing the second query (with
the single Max(date) aggregate), or is this just a side effect of how
SQLite is likely ordering the table to grab the Max before grouping?
Yes, the result that you get is guaranteed because it is documented in Bare columns in an aggregate query.
The value for the column id that you get is from the row that contains the max date.
I would like to see a most concise way to do what is outlined in this SO question: Sum values from multiple rows into one row
that is, combine multiple rows while summing a column.
But how to then delete the duplicates. In other words I have data like this:
Person Value
--------------
1 10
1 20
2 15
And I want to sum the values for any duplicates (on the Person col) into a single row and get rid of the other duplicates on the Person value. So my output would be:
Person Value
-------------
1 30
2 15
And I would like to do this without using a temp table. I think that I'll need to use OVER PARTITION BY but just not sure. Just trying to challenge myself in not doing it the temp table way. Working with SQL Server 2008 R2
Simply put, give me a concise stmt getting from my input to my output in the same table. So if my table name is People if I do a select * from People on it before the operation that I am asking in this question I get the first set above and then when I do a select * from People after the operation, I get the second set of data above.
Not sure why not using Temp table but here's one way to avoid it (tho imho this is an overkill):
UPDATE MyTable SET VALUE = (SELECT SUM(Value) FROM MyTable MT WHERE MT.Person = MyTable.Person);
WITH DUP_TABLE AS
(SELECT ROW_NUMBER()
OVER (PARTITION BY Person ORDER BY Person) As ROW_NO
FROM MyTable)
DELETE FROM DUP_TABLE WHERE ROW_NO > 1;
First query updates every duplicate person to the summary value. Second query removes duplicate persons.
Demo: http://sqlfiddle.com/#!3/db7aa/11
All you're asking for is a simple SUM() aggregate function and a GROUP BY
SELECT Person, SUM(Value)
FROM myTable
GROUP BY Person
The SUM() by itself would sum up the values in a column, but when you add a secondary column and GROUP BY it, SQL will show distinct values from the secondary column and perform the aggregate function by those distinct categories.
I'm trying to insert distinct values from one table into another. My target table has a primary key studentid and when I perform distinct id from source to target the load is successful. When I'm trying to load a bunch of columns from source to target including student_id, I'm getting an error unique constraint violated. There is only one constraint on target which is the primary key on studentid.
my query looks like this (just an example)
insert into target(studentid, age, schoolyear)
select distinct id, age, 2012 from source
Why does the above query returns an error where as the below query works perfectly fine
insert into target(studentid)
select distinct id from source
help me troubleshoot this.
Thanks for your time.
In your first query you are selecting for distinct combination of three columns ie,
select distinct id, age, 2012 from source
Not the distinct id alone. In such case there are possibility for duplicate id's.
For example, Your above query is valid for this
id age
1 23
1 24
1 25
2 23
3 23
But in your second query you are selecting only distinct id's
select distinct id from source
So this will return like,
id
1
2
3
In this case there is no way for duplicates and your insert into target will not
fail.
If you really want to do bulk insert with constrain on target then go for
any aggregate functions
select id, max(age), max(2012) group by id from source
Or if you dont want to loose any records from source to target then remove your constraint on target and insert it.
Hope this helps
Is there a way to know the last nth id field of a table, without scanning it completely? (just go to the end of table and get id value)
table
id fieldvalue
1 2323
2 4645
3 556
... ...
100000000 1232
So for example here n = 100000000 100 Million
--------------EDIT-----
So which one of the queries proposed would be more efficient?
SELECT MAX(id) FROM <tablename>
Assuming ID is the IDENTITY for the table, you could use SELECT IDENT_CURRENT('TABLE NAME').
See here for more info.
One thing to note about this approach: If you have INSERTs that fail but increment the IDENTITY counter, then you will get back a result that is higher than the result returned by SELECT MAX(id) FROM <tablename>
You can also use system tables to get all last values from all identity columns in system:
select
OBJECT_NAME(object_id) + '.' + name as col_name
, last_value
from
sys.identity_columns
order by last_value desc
In case when table1 rows are inserted first, and then rows to table2 which depend on ids from the table1, you can use SELECT:
INSERT INTO `table2` (`some_id`, `some_value`)
VALUES ((SELECT some_id
FROM `table1`
WHERE `other_key_1` = 'xxx'
AND `other_key_2` = 'yyy'),
'some value abc abc 123 123 ...');
Of course, this can work only if there are other identifiers that can uniquely identify rows from table1
First of all, you want to access the table in DESCENDING order by ID.
Then you would select the TOP N records.
At this point, you want the last record of the set which hopefully is obvious. Assuming that the id field is indexed, this would at most retrieve the last N records of the table and most likely would end up being optimized into a single record fetch.
Select Ident_Current('Your Table Name') gives the last Id of your table.
I'm trying to normalize a mysql database....
I currently have a table that contains 11 columns for "categories". The first column is a user_id and the other 10 are category_id_1 - category_id_10. Some rows may only contain a category_id up to category_id_1 and the rest might be NULL.
I then have a table that has 2 columns, user_id and category_id...
What is the best way to transfer all of the data into separate rows in table 2 without adding a row for columns that are NULL in table 1?
thanks!
You can create a single query to do all the work, it just takes a bit of copy and pasting, and adjusting the column name:
INSERT INTO table2
SELECT * FROM (
SELECT user_id, category_id_1 AS category_id FROM table1
UNION ALL
SELECT user_id, category_id_2 FROM table1
UNION ALL
SELECT user_id, category_id_3 FROM table1
) AS T
WHERE category_id IS NOT NULL;
Since you only have to do this 10 times, and you can throw the code away when you are finished, I would think that this is the easiest way.
One table for users:
users(id, name, username, etc)
One for categories:
categories(id, category_name)
One to link the two, including any extra information you might want on that join.
categories_users(user_id, category_id)
-- or with extra information --
categories_users(user_id, category_id, date_created, notes)
To transfer the data across to the link table would be a case of writing a series of SQL INSERT statements. There's probably some awesome way to do it in one go, but since there's only 11 categories, just copy-and-paste IMO:
INSERT INTO categories_users
SELECT user_id, 1
FROM old_categories
WHERE category_1 IS NOT NULL