I have a table in which several indentifiers of a person may be stored. In this table I would like to create a single calculated identifier column that stores the best identifier for that record depending on what identifiers are available.
For example (some fictional sample data) ....
Table = "Citizens"
Id | LastName | DL-No | SS-No | State-Id-No | Calculated
------------------------------------------------------------------------
1 | Smith | NULL | 374-784-8888 | 7383204848 | ?
2 | Jones | JG892435262 | NULL | NULL | ?
3 | Trask | TSK73948379 | NULL | 9276542119 | ?
4 | Clinton | CL231429888 | 543-123-5555 | 1840430324 | ?
I know the order in which I would like choose identifiers ...
Drivers-License-No
Social-Security-No
State-Id-No
So I would like the calculated identifier column to be part of the table schema. The desired results would be ...
Id | LastName | DL-No | SS-No | State-Id-No | Calculated
------------------------------------------------------------------------
1 | Smith | NULL | 374-784-8888 | 7383204848 | 374-784-8888
2 | Jones | JG892435262 | NULL | 4537409273 | JG892435262
3 | Trask | NULL | NULL | 9276542119 | 9276542119
4 | Clinton | CL231429888 | 543-123-5555 | 1840430324 | CL231429888
IS this possible? If so what SQL would I use to calculate what goes in the "Calculated" column?
I was thinking of something like ..
SELECT
CASE
WHEN ([DL-No] is NOT NULL) THEN [DL-No]
WHEN ([SS-No] is NOT NULL) THEN [SS-No]
WHEN ([State-Id-No] is NOT NULL) THEN [State-Id-No]
AS "Calculated"
END
FROM Citizens
The easiest solution is to use coalesce():
select c.*,
coalesce([DL-No], [SS-No], [State-ID-No]) as calculated
from citizens c
However, I think your case statement will also work, if you fix the syntax to use when rather than where.
Related
I have table which consist of 35,000 records in which half of the rows have name as null value
If the field has null value, i want to update the field with the value of username.
Can anyone help me with this ?
This is sample table
name | username | idnumber | type
----------------------------------------------
-- | jack | 1 | A
Mark | Mark | 2 | B
-- | dev | 3 | A
After update i want it to look like this
name | username | idnumber | type
----------------------------------------------
jack | jack | 1 | A
Mark | Mark | 2 | B
dev | dev | 3 | A
You seem to want:
update t
set name = username
where name is null;
Note that -- is not a typical representation of NULL values. You might consider <null> for instance.
I am learning indexing of database.
here are indexings of a table. And this table has 330k records.
mysql> show index from employee;
+----------+------------+-------------+--------------+---------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression |
+----------+------------+-------------+--------------+---------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+
| employee | 0 | PRIMARY | 1 | id | A | 297383 | NULL | NULL | | BTREE | | | YES | NULL |
| employee | 0 | ak_employee | 1 | personal_code | A | 297383 | NULL | NULL | | BTREE | | | YES | NULL |
| employee | 1 | idx_email | 1 | email | A | 297383 | NULL | NULL | | BTREE | | | YES | NULL |
+----------+------------+-------------+--------------+---------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+
as you can see, there are only three indexing on this table.
Now I want to query with where on birth_date column, I think it will be very slow because there is no indexing on birth-date column, I when I try query, I found it is very fast.
mysql> select sql_no_cache *
-> from employee
-> where birth_date > '1955-11-11'
-> limit 100
-> ;
100 rows in set, 1 warning (0.04 sec)
So I am confused:
why it is still so fast without indexing?
due to its still fast, why do we still need indexing?
This is your query:
select sql_no_cache *
from employee
where birth_date > '1955-11-11'
limit 100
There are no indexes so the query starts reading the data from the data pages. On each record, it compares the birthdate and returns the row. When it finds 100 (due to the limit) it stops.
Presumably, it finds 100 rows quite quickly. After all, the median age of the United States is about 38 -- which is (as I write this) a birth year of 1981. By far, most people were born after 1955.
The query would be much slower if you had an order by or group by. That would require reading all the data before returning anything.
I am new to working with databases and I want to make sure I understand the best way to add or remove data from a database without making a mess of any related data.
Here is a scenario I am working with:
I have a Tags table, with an Identity ID column. The Tags can be selected via the web application to categorize stories that are submitted by a user. When the database was first seeded; like tags were seeded in order together. As you can see all the Campuses (cities) were 1-4, the Colleges (subjects) are 5-7, and Populations are 8-11.
If this database is live in production and the client wants to add a new Campus (City) tag, what is the best way to do this?
All the other city tags are sort of organized at the top, it seems like the only option is to insert any new tags at to bottom of the table, where they will end up taking whatever the next ID available is. I suppose this is fine because the Display category column will allow us to know which categories these new tags actually belong to.
Is this typical? Is there better ways to set up the database or handle this situation such that everything remains more organized?
Thank you
+----+------------------+---------------+-----------------+--------------+--------+----------+
| ID | DisplayName | DisplayDetail | DisplayCategory | DisplayOrder | Active | ParentID |
+----+------------------+---------------+-----------------+--------------+--------+----------+
| 1 | Albany | NULL | 1 | 0 | 1 | NULL |
| 2 | Buffalo | NULL | 1 | 1 | 1 | NULL |
| 3 | New York City | NULL | 1 | 2 | 1 | NULL |
| 4 | Syracuse | NULL | 1 | 3 | 1 | NULL |
| 5 | Business | NULL | 2 | 0 | 1 | NULL |
| 6 | Dentistry | NULL | 2 | 1 | 1 | NULL |
| 7 | Law | NULL | 2 | 2 | 1 | NULL |
| 8 | Student-Athletes | NULL | 3 | 0 | 1 | NULL |
| 9 | Alumni | NULL | 3 | 1 | 1 | NULL |
| 10 | Faculty | NULL | 3 | 2 | 1 | NULL |
| 11 | Staff | NULL | 3 | 3 | 1 | NULL |
+----+------------------+---------------+-----------------+--------------+--------+----------+
The terms "top" and "bottom" which you use aren't really applicable. "Albany" isn't at the "Top" of the table - it's merely at the top of the specific view you see when you query the table without specifying a meaningful sort order. It defaults to a sort order based on the Id or an internal ROWID parameter, which isn't the logical way to show this data.
Data in the table isn't inherently ordered. If you want to view your tags organized by their category, simply order your query by DisplayCategory (and probably by DisplayOrder afterwards), and you'll see your data properly organized. You can even create a persistent View that sorts it that way for your convenience.
I have these two tables that i need to join
fields_data fields
+------------+-----------+------+ +------+-------------+----------+
| relationid | fieldname | data | | name | displayname | position |
+------------+-----------+------+ +------+-------------+----------+
| 2 | ftp | test | | user | Username | top |
| 2 | other | 1234 | | pass | Password | top |
+------------+-----------+------+ | ftp | FTP | top |
| log | Log | top |
| txt | Text | mid |
+------+-------------+----------+
I want to get all the rows from the "fields" table if they have the position "top" AND if a row has a match on name = fieldname from fields_data it should also show the data. This is my join
SELECT
fd.`data`,
fd.`relationid`,
fd.`fieldname`,
f.`name`,
f.`displayname`
FROM `fields` AS f
LEFT OUTER JOIN `fields_data` AS fd
ON fd.`fieldname` = f.`name`
WHERE f.`position`='top' AND (fd.`relationid`='3' OR fd.`relationid` IS NULL)
My problem is that the above query only gives me this result:
+------+------------+-----------+------+-------------+
| data | relationid | fieldname | name | displayname |
+------+------------+-----------+------+-------------+
| NULL | NULL | NULL | user | Username |
| NULL | NULL | NULL | pass | Password |
| NULL | NULL | NULL | log | Log |
+------+------------+-----------+------+-------------+
The field called "ftp" is missing due to it having a relation to "2".. However i still want to display it as result but like the others with NULL in it. And if the SQL query had "fd.relationid='2'" instead of 3 it would give same result, but with the row containing ftp in name, holding data in the three fields.
I hope you get what i mean.. My english is not the best.. Heres the result i want:
with above query containing fd.`relationid`='3'
+------+------------+-----------+------+-------------+
| data | relationid | fieldname | name | displayname |
+------+------------+-----------+------+-------------+
| NULL | NULL | NULL | user | Username |
| NULL | NULL | NULL | pass | Password |
| NULL | NULL | NULL | ftp | FTP |
| NULL | NULL | NULL | log | Log |
+------+------------+-----------+------+-------------+
with above query containing fd.`relationid`='2'
+------+------------+-----------+------+-------------+
| data | relationid | fieldname | name | displayname |
+------+------------+-----------+------+-------------+
| NULL | NULL | NULL | user | Username |
| NULL | NULL | NULL | pass | Password |
| test | 2 | ftp | ftp | FTP |
| NULL | NULL | NULL | log | Log |
+------+------------+-----------+------+-------------+
You want to move the condition to the on clause:
SELECT fd.`data`, fd.`relationid`, fd.`fieldname`, f.`name`, f.`displayname`
FROM `fields` f LEFT OUTER JOIN
`fields_data` fd
ON fd.`fieldname` = f.`name` AND fd.`relationid` = '3'
WHERE f.`position`='top' ;
It is interesting that the semantics of your query and this query are different -- and you found the exact situation: when there is a match on another value, the where clause form filters out the row. This will still keep everything.
As a note, the following also does what you want:
SELECT fd.`data`, fd.`relationid`, fd.`fieldname`, f.`name`, f.`displayname`
FROM `fields` f LEFT OUTER JOIN
(SELECT fd.*
FROM `fields_data` fd
WHERE fd.`relationid` = '3'
) fd
ON fd.`fieldname` = f.`name`
WHERE f.`position` = 'top' ;
I wouldn't recommend writing the query this way, particularly in MySQL (because the subquery is materialized). However, understanding why your version is different from these versions (and why these are the same) is a big step forward in mastering outer joins.
Sorry for the title, perhaps it's not very clear.
I have some SQL queries in a script that depend on each other.
The script uses a temporary table in which the data is inserted (the #temp_data table).
This is the expected output:
___________________________________
| speed1 | speed2 | distance |
| 1 | NULL | 10 |
| 3 | NULL | 40 |
| 5 | NULL | 90 |
| NULL | 1 | 10 |
| NULL | 3 | 40 |
| NULL | 5 | 90 |
Here is the query structure (I didn't include the actual query since it's too big):
-- First group
queryForSpeed1
queryToUpdateDistanceBasedOnSpeed1
-- Second group
queryForSpeed2
queryToUpdateDistanceBasedOnSpeed2
If I run the first group of queries (queryForSpeed1 and queryToUpdateDistanceBasedOnSpeed1) separately from the second group then I get the expected output: only the speed1 and distance columns contain data:
___________________________________
| speed1 | speed2 | distance |
| 1 | NULL | 10 |
| 3 | NULL | 40 |
| 5 | NULL | 90 |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
The same happens when I run the second group:
___________________________________
| speed1 | speed2 | distance |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
| NULL | NULL | NULL |
| NULL | 1 | 10 |
| NULL | 2 | 40 |
| NULL | 3 | 90 |
BUT, when I run both groups: all the distances are NULL:
___________________________________
| speed1 | speed2 | distance |
| 1 | NULL | NULL |
| 3 | NULL | NULL |
| 5 | NULL | NULL |
| NULL | 1 | NULL |
| NULL | 2 | NULL |
| NULL | 3 | NULL |
I believe this is somehow related to transaction management and temporary tables, although I wasn't able to find anything relevant to solve the problem on Google.
From what I've read, SQL Server keeps a transaction log where it stores every update, insert and whatever... when it arrives at the end of the script it actually does all those insertions and updates.
So the update I did for the distance column finds all the speeds as being NULL because the data wasn't yet inserted in the temporary table from the previous updates, but at the end of the query the speeds are inserted in the table so that's why they are visible.
I played a bit with the GO statement to execute my script in batches, but no luck so far...
What am I doing wrong? Can someone point me in the right direction, please?
EDIT
Here is the actual query.
The problem is not related to transactions, but rather to the way you conduct updates to #temp_speed_profile. The second pass through #temp_speed_profile retrieves all six records. Speed_new is null in first record of Voyage_Id, consequently #distance becomes null. As you retain the value of #distance in next turn, it remains null.
Problem goes away when using different temporary tables because second pass works on second set of data only.
A note on cursors - when defining one make sure to add local and fast_forward. Local because it is limiting cursors' scope, and fast_forward to optimize fetches.
It is almost certainly caused by the way you have written your queries.
To confirm, just rewrite your queries using #temp_data1 and #temp_data2, rather than a single table #temp_data.