I've been beating my head on the desk trying to figure this one out. I have a table that stores job information, and reasons for a job not being completed. The reasons are numeric,01,02,03,etc. You can have two reasons for a pending job. If you select two reasons, they are stored in the same column, separated by a comma. This is an example from the JOBID table:
Job_Number User_Assigned PendingInfo
1 user1 01,02
There is another table named Pending, that stores what those values actually represent. 01=Not enough info, 02=Not enough time, 03=Waiting Review. Example:
Pending_Num PendingWord
01 Not Enough Info
02 Not Enough Time
What I'm trying to do is query the database to give me all the job numbers, users, pendinginfo, and pending reason. I can break out the first value, but can't figure out how to do the second. What my limited skills have so far:
select Job_number,user_assigned,SUBSTRING(pendinginfo,0,3),pendingword
from jobid,pending
where
SUBSTRING(pendinginfo,0,3)=pending.pending_num and
pendinginfo!='00,00' and
pendinginfo!='NULL'
What I would like to see for this example would be:
Job_Number User_Assigned PendingInfo PendingWord PendingInfo PendingWord
1 User1 01 Not Enough Info 02 Not Enough Time
Thanks in advance
You really shouldn't store multiple items in one column if your SQL is ever going to want to process them individually. The "SQL gymnastics" you have to perform in those cases are both ugly hacks and performance degraders.
The ideal solution is to split the individual items into separate columns and, for 3NF, move those columns to a separate table as rows if you really want to do it properly (but baby steps are probably okay if you're sure there will never be more than two reasons in the short-medium term).
Then your queries will be both simpler and faster.
However, if that's not an option, you can use the afore-mentioned SQL gymnastics to do something like:
where find ( ',' |fld| ',', ',02,' ) > 0
assuming your SQL dialect has a string search function (find in this case, but I think charindex for SQLServer).
This will ensure all sub-columns begin and start with a comma (comma plus field plus comma) and look for a specific desired value (with the commas on either side to ensure it's a full sub-column match).
If you can't control what the application puts in that column, I would opt for the DBA solution - DBA solutions are defined as those a DBA has to do to work around the inadequacies of their users :-).
Create two new columns in that table and make an insert/update trigger which will populate them with the two reasons that a user puts into the original column.
Then query those two new columns for specific values rather than trying to split apart the old column.
This means that the cost of splitting is only on row insert/update, not on _every single select`, amortising that cost efficiently.
Still, my answer is to re-do the schema. That will be the best way in the long term in terms of speed, readable queries and maintainability.
I hope you are just maintaining the code and it's not a brand new implementation.
Please consider to use a different approach using a support table like this:
JOBS TABLE
jobID | userID
--------------
1 | user13
2 | user32
3 | user44
--------------
PENDING TABLE
pendingID | pendingText
---------------------------
01 | Not Enough Info
02 | Not Enough Time
---------------------------
JOB_PENDING TABLE
jobID | pendingID
-----------------
1 | 01
1 | 02
2 | 01
3 | 03
3 | 01
-----------------
You can easily query this tables using JOIN or subqueries.
If you need retro-compatibility on your software you can add a view to reach this goal.
I have a tables like:
Events
---------
eventId int
eventTypeIds nvarchar(50)
...
EventTypes
--------------
eventTypeId
Description
...
Each Event can have multiple eventtypes specified.
All I do is write 2 procedures in my site code, not SQL code
One procedure converts the table field (eventTypeIds) value like "3,4,15,6" into a ViewState array, so I can use it any where in code.
This procedure does the opposite it collects any options your checked and converts it in
If changing the schema is an option (which it probably should be) shouldn't you implement a many-to-many relationship here so that you have a bridging table between the two items? That way, you would store the number and its wording in one table, jobs in another, and "failure reasons for jobs" in the bridging table...
Have a look at a similar question I answered here
;WITH Numbers AS
(
SELECT ROW_NUMBER() OVER(ORDER BY (SELECT 0)) AS N
FROM JobId
),
Split AS
(
SELECT JOB_NUMBER, USER_ASSIGNED, SUBSTRING(PENDING_INFO, Numbers.N, CHARINDEX(',', PENDING_INFO + ',', Numbers.N) - Numbers.N) AS PENDING_NUM
FROM JobId
JOIN Numbers ON Numbers.N <= DATALENGTH(PENDING_INFO) + 1
AND SUBSTRING(',' + PENDING_INFO, Numbers.N, 1) = ','
)
SELECT *
FROM Split JOIN Pending ON Split.PENDING_NUM = Pending.PENDING_NUM
The basic idea is that you have to multiply each row as many times as there are PENDING_NUMs. Then, extract the appropriate part of the string
While I agree with DBA perspective not to store multiple values in a single field it is doable, as bellow, practical for application logic and some performance issues. Let say you have 10000 user groups, each having average 1000 members. You may want to have a table user_groups with columns such as groupID and membersID. Your membersID column could be populated like this:
(',10,2001,20003,333,4520,') each number being a memberID, all separated with a comma. Add also a comma at the start and end of the data. Then your select would use like '%,someID,%'.
If you can not change your data ('01,02,03') or similar, let say you want rows containing 01 you still can use " select ... LIKE '01,%' OR '%,01' OR '%,01,%' " which will insure it match if at start, end or inside, while avoiding similar number (ie:101).
Related
I have a quick question regarding writing a SQL query to obtain a complete entry from two or more entries where the data is missing in different columns.
This is the example, suppose I have this table:
Client Id | Name | Email
1234 | John | (null)
1244 | (null) | john#example.com
Would it be possible to write a query that would return the following?
Client Id | Name | Email
1234 | John | john#example.com
I am finding this particularly hard because these are 2 entires in the same table.
I apologize if this is trivial, I am still studying SQL and learning, but I wasn't able to come up with a solution for this and I although I've tried looking online I couldn't phrase the question in the proper way, I suppose and I couldn't really find the answer I was after.
Many thanks in advance for the help!
Yes, but actually no.
It is possible to write a query that works with your example data.
But just under the assumption that the first part of the mail is always equal to the name.
SELECT clients.id,clients.name,bclients.email FROM clients
JOIN clients bclients ON upper(clients.name) = upper(substring(bclients.email from 0 for position('#' in bclients.email)));
db<>fiddle
Explanation:
We join the table onto itself, to get the information into one row.
For this we first search for the position of the '#' in the email, get the substring from the start (0) of the string for the amount of characters until we hit the # (result of positon).
To avoid case-problems the name and substring are cast to uppercase for comparsion.
(lowercase would work the same)
The design is flawed
How can a client have multiple ids and different kind of information about the same user at the same time?
I think you want to split the table between clients and users, so that a user can have multiple clients.
I recommend that you read information about database normalization as this provides you with necessary knowledge for successfull database design.
How would I go about joining results from multiple SQL queries so that they are side by side (but unrelated)?
The reason I am thinking of this is so that I can run 1 query in Google Big Query and it will return 1 single table which I can import into Excel and do some charts.
e.g. Query 1 looks at dataset TableA and returns:
**Metric:** Sales
**Value:** 3,402
And then Query 2 looks at dataset TableB and returns:
**Name:** John
**DOB:** 13 March
They would both use different tables and different filters, etc.
What would I do to make it look like:
---Sales----------John----
---3,402-------13 March----
Or alternatively:
-----Sales--------3,402-----
-----John-------13 March----
Or is there a totally different way to do this?
I can see the use case for the above, I've used something similar to create a single table from multiple tables with different metrics to query in Data Studio so that filters apply to all data in the dataset for example. However in that case, the data did share some dimensions that made it worthwhile doing.
If you are going to put those together with no relationship between the tables, I'd have 4 columns with TYPE describing the data in that row to make for easier filtering.
Type | Sales | Name | DOB
Use UNION ALL to put the rows together so you have something like
"Sales" | 3402 | null | null
"Customer Details" | null | John | 13 March
However, like the others said, make sure you have a good reason to do that otherwise you're just creating a bigger table to query for no reason.
My client has a set of numeric data stored in a string field in a database. So of course it doesn't sort correctly. These rows sort like this:
105
3
44
When they should sort like this:
3
44
105
This is very much a legacy database and I can't change it at all. I also can't change the software that uses the database. The client doesn't own it or have the source code. It has never worked the way they want. However, there is an unused string field that I could use to sort on (only a small number of fields can be sorted on.)
What I would like to do is take the input data, derive a string from it, and store the new string in the unused field, such that when the data is sorted on this new data, the original data sorts correctly, i.e., numerically.
So, for an overly simplistic example, if the algorithm produced the following new data:
105 -> c
3 -> a
44 -> b
Then when the second column was sorted, the first column would look 'correct'.
The tricky bit is that when new rows are added to the database, they must also sort correctly, without having to regenerate the sort data for all rows. This is the part of the problem that has my brain in a twist. I'm not sure it's actually possible.
You can assume that the number will never be more than 5 'digits'.
I realize this is a total kludge, but since I can't change the system, I have to find a work around, rather than a quality solution. Welcome to the real world.
~~~~~~~~~~~~~~~~~~~~~~ S O L U T I O N ~~~~~~~~~~~~~~~~~~
I don't think this is an uncommon problem, so here are the results of Gordon's solution:
mysql> select * from t order by new;
+------+------------+
| orig | new |
+------+------------+
| 3 | 0000000003 |
| 44 | 0000000044 |
| 105 | 0000000105 |
+------+------------+
In most databases, you can just do:
order by cast(col as int)
This will convert the string representation to a number and use that for ordering. There is no need for an additional column. If you add one, I would recommend adding a numeric column to contain the actual value.
If you really want to store something in the unused field, then you can left pad the number. How to do this depends on the database, but here is one typical method:
update t
set unused = right(concat('0000000000', col), 10);
Not all databases support these two specific functions, but all offer this basic functionality in some method.
Try something like
SELECT column1 FROM table1 ORDER BY LENGTH(column1) ASC, column1 ASC
(Adjust the column and table name for your environment.)
This is a bit of a hack but works as long as the "numbers" in your string column are natural, non-negative numbers only.
If you are looking for a more sophisticated approach or algorithm, try searching for natural sort together with your DBMS.
I have a table in MS Access of data containing results from a survey, and I have a look up table of Risk Ids and descriptions of the sort of risk based on the survey results.
What I've tried so far is selecting distinct entries from my survey table, and inputing a new field into my query for the Risk Code whose number will depend on criteria that I determine, which I will then use to look up the risk.
My table for the survey looks like so:
Name | Location | Days spent eating IceCream | Icecream eating location
John Smith | London | 30 | Hull
My Risk ID table looks like so:
RiskID | RiskBool | Description
1 | Yes | At risk - This person eats too much icecream
2 | Yes | Risk - This person does not eat enough icecream
3 | No | Sensible amount of icecream eaten
4 | Yes | It is illegal to eat icecream in Hull
And my query looks (something) like this in access design view
Name | Location | Risk Code | RiskID | Description
I want to write SQL to change the Risk Code to 1, 2, 3, 4 (up to 15 in my real case) and then I will tell it to only display the person and the description for when the Risk ID and Code match. I haven't written this yet.
What is the best way to achieve this?
I see two possibilities:
Set up 15 queries one for each risk ID, add the descriptions to
those and then join those 15 sets of results together. This is what
I know how to do, but could end up quite messily.
Set up some 'check' using if statements, and then some how setting
the Risk Code field for that entry.
My current SQL looks like this, but it doesn't make any checks yet, I'm worried the if statment will be very, very long.
SELECT DISTINCT
[At Risk Employee List].Employee AS Name,
[At Risk Employee List].[DaysIceCream] AS [Days spent eating Icecream],
[At Risk Employee List].[Base Location],
[RiskCode] AS [Risk Code], <----is this where the check would need to go?
RiskDescLookup.RiskBoolean,
RiskDescLookup.RiskExplanation
FROM RiskDescLookup,
[Survey Raw Data]
INNER JOIN
[At Risk Employee List]
ON
[Survey Raw Data].ResID = [At Risk Employee List].[Staff ID]
GROUP BY
[At Risk Employee List].Employee,
[At Risk Employee List].[DaysIceCream],
[At Risk Employee List].[Base Location],
RiskDescLookup.RiskID,
[RiskCode] AS [Risk Code], <----is this where the check would need to go?
RiskDescLookup.RiskBoolean,
RiskDescLookup.RiskExplanation
I imagine the check done by if statements to be Very long and look something like (in pseudocode):
if ( [At Risk Employee List].[Base Location] = Hull, then [RiskCode]=4...., else if (DaysIceCream>42) then....
Is that the best way to do this? Do I even need to have a Risk Code?
I'm a bit lost as to how to produce this 'check' in the best possible way.
I am not entirely certain of your intent, but from what you've posted and the follow up comments it would appear that the process of joining the Risk Code to Risk ID is relatively simple once you have the Risk Code identified for each survey result.
The real issue it seems is how to encapsulate the logic to identify the Risk Code for each survey result. I would suggest "calculating" the risk code value for each survey result externally to your query and then join to those results before finally joining to the Risk ID.
For example, I might add a third table to the design SurveyRisk that contains Name and Risk Code.
Use whatever criteria and logic you need to use to identify the risk for each survey response. Enter these values into the SurveyRisk table. Then, you can simply join Survey to SurveyRisk to Risk to summarize your results.
Feel free to clarify where I'm misunderstanding what you are trying to accomplish and I'll edit my post accordingly.
The best way to do this is to use a look up table that emulates the structure of your data.
Add a row for every 'case', and in MS Access link the corresponding fields together.
Here is a few of the links:
Then alter the SQL to pair up any options that need to go together. For instance each of the checks I make are duplicated for two seperate locations.
Here is an example:
FROM RiskDescLookupReg
INNER JOIN ([Survey Raw Data]
INNER JOIN [At Risk Employee List]
ON [Survey Raw Data].ResID=[At Risk Employee List].[Staff ID])
ON (RiskDescLookupReg.RegTravelChoice=[Survey Raw Data].RegTravelChoice)
And (RiskDescLookupReg.MonthChoice2=[Survey Raw Data].MonthChoice2
And RiskDescLookupReg.PercentageTimeChoice2=[Survey Raw Data].PercentageTimeChoice2
And RiskDescLookupReg.LimitedDurationChoice2=[Survey Raw Data].LimitedDurationChoice2
And RiskDescLookupReg.TemporaryPurposeChoice2=[Survey Raw Data].TemporaryPurposeChoice2)
Or (
RiskDescLookupReg.MonthChoice1=[Survey Raw Data].MonthChoice1
And RiskDescLookupReg.PercentageTimeChoice1=[Survey Raw Data].PercentageTimeChoice1
And RiskDescLookupReg.LimitedDurationChoice1=[Survey Raw Data].LimitedDurationChoice1
And RiskDescLookupReg.TemporaryPurposeChoice1=[Survey Raw Data].TemporaryPurposeChoice1)
Not how there are two blocks for each location. If I only had one location of interest, I could drop the last block.
If you get duplicates because of the way your lookup table is arranged, you need to specify that the parts from the lookup table are enclosed in a LAST, and the parts from the survey in FIRST. Here is an example:
SELECT
[At Risk Employee List].Number,
FIRST([At Risk Employee List].Employee) AS Name,
FIRST([At Risk Employee List].[Base Location]) AS BaseLocation,
LAST(RiskDescLookupReg.RiskBool) AS RiskBool,
LAST(RiskDescLookupReg.RiskDesc) AS RiskDesc,
The use of LAST ensures that if someone would come up as at risk and not at risk, only the LAST at risk case is displayed (those entries come later in the field). This is counter to the fact when duplicates are displayed the at risk ones come first.
I realize that referring to these as dimension and fact tables is not exactly appropriate. I am at a lost for better terminology, so please excuse this categorization that I use in the post.
I am building an application for employee record keeping.
The database will contain organizational information. The information is mostly defined in three tables: Locations, Divisions, and Departments. However, there are others with similar problems. First, I need to store the available values for these tables. This will allow for available values in the application when managing an employee and for management of these values when adding/deleting departments and such. For instance, the Locations table may look like,
LocationId | LocationName | LocationStatus
1 | New York | Active
2 | Denver | Inactive
3 | New Orleans | Active
I then need to store these values for each employee and keep their history. My first thought was to create LocationHistory, DivisionHistory, and DepartmentHistory tables. I cannot pinpoint why, but this struck me as poor design. My next inclination was to create a DimLocation/FactLocation, DimDivision/FactDivision, DimDepartment/FactDepartment set of tables. I do not believe this makes sense either. I have also considered naming them as a combination of Employee, i.e. EmployeeLocations, EmployeeDivisions, etc. Regardless of the naming convention for these tables, I imagine that data would look similar to a simplified version I have below:
EmployeeId | LocationId | EffectiveDate | EndDate
1 | 3 | 2008-07-01 | NULL
1 | 2 | 2007-04-01 | 2008-06-30
I realize any of the imagined solutions I described above could work, but I am really looking to create a design that will be easy for others to maintain with an intuitive, familiar structure. I would like to receive this community's help, opinions, and experience with this matter. I am open to and would welcome any suggestion to consider. For instance, should I even store the available values for these three tables in the database? Should they be maintained in the application code/business logic layer? Do I just need to get over seeing the word History repeating three times?
Thanks!
Firstly, I see no issue in describing these as Dimension and Fact tables outside of a warehouse :)
In terms of conceptualising and understanding the relationships, I personally see the use of start/end dates perfectly easy for people to understand. Allowing Agent and Location fact tables, and then time dependant mapping tables such as Agent_At_Location, etc. They do, however, have issues worthy of taking note.
If EndDate is 2008-08-30, was the employee in that location UP TO 30th August, or UP TO and INCLUDING 30th August.
Dealing with overlapping date periods in queries can give messy queries, but more importantly, slow queries.
The first one seems simply a matter of convention, but it can have certain implications when dealign with other data. For example, consider that an EndDate of 2008-08-30 means that they ARE at that location UP TO and INCLUDING 30th August. Then you join on to their Daily Agent Data for that day (Such as when they Actually arrived at work, left for breaks, etc). You need to join ON AgentDailyData.EventTimeStamp < '2008-08-30' + 1 in order to include all the events that happened during that day.
This is because the data's EventTimeStamp isn't measured in days, but probably minutes or seconds.
If you consider that the EndDate of '2008-08-30' means that the Agent was at that Location UP TO but NOT INCLDUING 30th August, the join does not need the + 1. In fact you don't need to know if the date is DAY bound, or can include a time component or not. You just need TimeStamp < EndDate.
By using EXCLUSIVE End markers, all of your queries simplify and never need + 1 day, or + 1 hour to deal with edge conditions.
The second one is much harder to resolve. The simplest way of resolving an overlapping period is as follows:
SELECT
CASE WHEN TableA.InclusiveFrom > TableB.InclusiveFrom THEN TableA.InclusiveFrom ELSE TableB.InclusiveFrom END AS [NetInclusiveFrom],
CASE WHEN TableA.ExclusiveFrom < TableB.ExclusiveFrom THEN TableA.ExclusiveFrom ELSE TableB.ExclusiveFrom END AS [NetExclusiveFrom],
FROM
TableA
INNER JOIN
TableB
ON TableA.InclusiveFrom < TableB.ExclusiveFrom
AND TableA.ExclusiveFrom > TableB.InclusiveFrom
-- Where InclusiveFrom is the StartDate
-- And ExclusiveFrom is the EndDate, up to but NOT including that date
The problem with that query is one of indexing. The first condition TableA.InclusiveFrom < TableB.ExclusiveFrom could be be resolved using an index. But it could give a Massive range of dates. And then, for each of those records, the ExclusiveDates could all be just about anything, and certainly not in an order that could help quickly resolve TableA.ExclusiveFrom > TableB.InclusiveFrom
The solution I have previously used for that is to have a maximum allowed gap between InclusiveFrom and ExclusiveFrom. This allows something like...
ON TableA.InclusiveFrom < TableB.ExclusiveFrom
AND TableA.InclusiveFrom >= TableB.InclusiveFrom - 30
AND TableA.ExclusiveFrom > TableB.InclusiveFrom
The condition TableA.ExclusiveFrom > TableB.InclusiveFrom STILL can't benefit from indexes. But instead we've limitted the number of rows that can be returned by searching TableA.InclusiveFrom. It's at most only ever 30 days of data, because we know that we restricted the duration to a maximum of 30 days.
An example of this is to break up the associations by calendar month (max duration of 31 days).
EmployeeId | LocationId | EffectiveDate | EndDate
1 | 2 | 2007-04-01 | 2008-05-01
1 | 2 | 2007-05-01 | 2008-06-01
1 | 2 | 2007-06-01 | 2008-06-25
(Representing Employee 1 being in Location 2 from 1st April to (but not including) 25th June.)
It's effectively a trade off; using Disk Space to gain performance.
I've even seen this pushed to the extreme of not actually storing date Ranges, but storing the actual mapping for each and every day. Essentially, it's like restricting the maximum duration to 1 day...
EmployeeId | LocationId | EffectiveDate
1 | 2 | 2007-06-23
1 | 2 | 2007-06-24
1 | 3 | 2007-06-25
1 | 3 | 2007-06-26
Instinctively I initially rebelled against this. But in subsequent ETL, Warehousing, Reporting, etc, I actually found it Very powerful, adaptable, and maintainable. I actually saw people making fewer coding mistakes, writing code in less time, the code ending up running faster, and being much more able to adapt to clients' changing needs.
The only two down sides were:
1. More disk space taken (But trival compared to the size of fact tables)
2. Inserts and Updates to this mapping was slower
The actual slow down for Inserts and Updates only actually matter Once, where this model was being used to represent a constantly changing process net; where the app wanted to change the mapping about 30 times a second. Even then it worked, it just chomped up more CPU time than was ideal.
If you want to be efficient and keep a history, do these things. There are multiple solutions to this problem, but this is the one that I keep going back to:
Remember that each row represents a single entity, if you make corrections that entity, that's fine, but don't re-use and ID for a new Location. Set it up so that instead of deleting a Location, you mark it as deleted with a bit and hide it from the interface, that way when it's referenced historically, it's still there.
Create a history table that includes the current value, or no records if a value isn't currently set. Have the foreign key tie back to the employee and tie to the location.
Create a column in the employee table that points to the current active location in the history. When you need to get the employees location, you join in the history table based on this ID. When you need to get all of the history for an employee you join from the history table.
This structure keeps it all normalized, and gives you an easy way to find the current value without having to do any date comparisons.
As far as using the word history, think of it in different terms: since it contains the current item as well as historical items, it's really just a junction table that keeps around the old item. As such you can name it something like EmployeeLocations.