I have a strange issue. I have a report CR. In the Selection Formula I do a test on two fields. The test is simple like that : {field_City} = 'Paris' OR {field_Country} = 'France'.
This is a sample of the data in my table:
|---------------|---------------|---------------|
| ID_Record | Country | City |
|---------------|---------------|---------------|
| 1 | null | Paris |
|---------------|---------------|---------------|
| 2 | France | null |
|---------------|---------------|---------------|
| 3 | France | Paris |
|---------------|---------------|---------------|
The result of the Selection should be the 3 records, however it's excluding the 2 first rows where there is a null value in one of the columns. Then I changed the Selection Formula like this to consider null values too : ({field_City} = 'Paris' AND (isnull({field_Country}) OR not(isnull({field_Country})))) OR ({field_Country} = 'France' AND (isnull({field_City}) OR not(isnull({field_City})))) but I am still getting only the last record ! To ensure myself that my code is correct, I generated the sql query via the option in CR 'Show sql query', then i've added a WHERE clause in which I wrote the same condition that i've put in the Selection Formula, and...... it gave me the 3 records ! Unfortunately I can't work with the sql query, I have to find out why the formula is excluding the records that have a null value in one of the columns :( I hope that you can help me. Thanks a lot !
This is the solution: ((isnull({field_Country}) AND {field_City} = 'Paris') OR (isnull({field_City}) AND {field_Country} = 'France') OR (not(isnull({field_Country})) AND {field_City} = 'Paris') OR (not(isnull({field_City})) AND {field_Country} = 'France')) , Thank you so much Craig!
You need to test for null values first:
( Not(Isnull({field_Country})) AND {field_Country}='France' )
OR
( Isnull({field_Country}) AND {field_City}='Paris' )
Related
I have a source table, which lists like below:
public.source
Id | part_no | category
1 | 01270-4 | Landscape
2 | 01102-3 | Sports
Then, I have target table with jsonb column (combinations) , which list like below;
public.target
Id | part_no | combinations
7 | 01270-4 | {"subject":""}
8 | 01102-3 | {"subject":""}
My problem is - how I can update the target table with jsonb column (combinations) with the values coming from source table using the part_no column?
Output like:
Id | part_no | combinations
7 | 01270-4 | {"subject":"Landscape"}
8 | 01102-3 | {"subject":"Sports"}
I tried below but giving error:
UPDATE public.target t
SET combinations = jsonb_set(combinations,'{subject}','s.category',false)
FROM public.source s
WHERE s.part_no = t.part_no;
ERROR: invalid input syntax for type json
LINE 2: SET combinations = jsonb_set(combinations,'{subject}', 's.categor...
^
DETAIL: Token "s" is invalid.
CONTEXT: JSON data, line 1: s...
SQL state: 22P02
Character: 77
You should use to_jsonb function to convert s.category to JSON
Demo
UPDATE public.target t
SET combinations = jsonb_set(combinations,'{subject}',to_jsonb(s.category),false)
FROM public.source s
WHERE s.part_no = t.part_no
Or you can use sample structure for join and update two JSON field:
Demo
UPDATE public.target t
SET combinations = combinations || jsonb_build_object('subject', s.category)
FROM public.source s
WHERE s.part_no = t.part_no
I have formed this query to get the desired output mentioned below:
select tbl.id, tbl.label, tbl.input_type, tbl.table_name
case when tbl.input_type = 'dropdown' or tbl.input_type = 'searchable-dropdown'
then (select json_agg(opt) from tbl.table_name) as opt) end as options
from mst_config as tbl;
I want output like below:
id | label | input_type | table_name | options
----+----------------------------------------------------+---------------------+-------------------------+-----------------------------------------------------------
1 | Gender | dropdown | mst_gender | [{"id":1,"label":"MALE"},
| | | | {"id":2,"label":"FEMALE"}]
2 | SS | dropdown | mst_ss | [{"id":1,"label":"something"},
| | | | {"id":2,"label_en":"something"}]
But, I'm facing a problem while using,
select json_agg(opt) from tbl.table_name) as opt
In the above part "tbl.table_name", I wanted to use it as dynamic table name but it's not working.
Then, I have searched a lot and found something like Execute format('select * from %s', table_name), where tablename is the dynamic table name. I have even tried the same with postgres function.
But I faced an issue again while using the format method. The reason is I want to use the variable for which the value needs to come from its own main query value instead of already having it in a variable. so this one was also not working.
I would really appreciate if anyone can help me out on this. Also if there are any other possibilities available to achieve this output, help me on that as well.
I used to write my EXISTS checks like this:
IF EXISTS (SELECT * FROM TABLE WHERE Columns=#Filters)
BEGIN
UPDATE TABLE SET ColumnsX=ValuesX WHERE Where Columns=#Filters
END
One of the DBA's in a previous life told me that when I do an EXISTS clause, use SELECT 1 instead of SELECT *
IF EXISTS (SELECT 1 FROM TABLE WHERE Columns=#Filters)
BEGIN
UPDATE TABLE SET ColumnsX=ValuesX WHERE Columns=#Filters
END
Does this really make a difference?
No, SQL Server is smart and knows it is being used for an EXISTS, and returns NO DATA to the system.
Quoth Microsoft:
http://technet.microsoft.com/en-us/library/ms189259.aspx?ppud=4
The select list of a subquery
introduced by EXISTS almost always
consists of an asterisk (*). There is
no reason to list column names because
you are just testing whether rows that
meet the conditions specified in the
subquery exist.
To check yourself, try running the following:
SELECT whatever
FROM yourtable
WHERE EXISTS( SELECT 1/0
FROM someothertable
WHERE a_valid_clause )
If it was actually doing something with the SELECT list, it would throw a div by zero error. It doesn't.
EDIT: Note, the SQL Standard actually talks about this.
ANSI SQL 1992 Standard, pg 191 http://www.contrib.andrew.cmu.edu/~shadow/sql/sql1992.txt
3) Case:
a) If the <select list> "*" is simply contained in a <subquery> that
is immediately contained in an <exists predicate>, then the <select list> is
equivalent to a <value expression>
that is an arbitrary <literal>.
The reason for this misconception is presumably because of the belief that it will end up reading all columns. It is easy to see that this is not the case.
CREATE TABLE T
(
X INT PRIMARY KEY,
Y INT,
Z CHAR(8000)
)
CREATE NONCLUSTERED INDEX NarrowIndex ON T(Y)
IF EXISTS (SELECT * FROM T)
PRINT 'Y'
Gives plan
This shows that SQL Server was able to use the narrowest index available to check the result despite the fact that the index does not include all columns. The index access is under a semi join operator which means that it can stop scanning as soon as the first row is returned.
So it is clear the above belief is wrong.
However Conor Cunningham from the Query Optimiser team explains here that he typically uses SELECT 1 in this case as it can make a minor performance difference in the compilation of the query.
The QP will take and expand all *'s
early in the pipeline and bind them to
objects (in this case, the list of
columns). It will then remove
unneeded columns due to the nature of
the query.
So for a simple EXISTS subquery like
this:
SELECT col1 FROM MyTable WHERE EXISTS (SELECT * FROM Table2 WHERE MyTable.col1=Table2.col2) The * will be
expanded to some potentially big
column list and then it will be
determined that the semantics of the
EXISTS does not require any of those
columns, so basically all of them can
be removed.
"SELECT 1" will avoid having to
examine any unneeded metadata for that
table during query compilation.
However, at runtime the two forms of
the query will be identical and will
have identical runtimes.
I tested four possible ways of expressing this query on an empty table with various numbers of columns. SELECT 1 vs SELECT * vs SELECT Primary_Key vs SELECT Other_Not_Null_Column.
I ran the queries in a loop using OPTION (RECOMPILE) and measured the average number of executions per second. Results below
+-------------+----------+---------+---------+--------------+
| Num of Cols | * | 1 | PK | Not Null col |
+-------------+----------+---------+---------+--------------+
| 2 | 2043.5 | 2043.25 | 2073.5 | 2067.5 |
| 4 | 2038.75 | 2041.25 | 2067.5 | 2067.5 |
| 8 | 2015.75 | 2017 | 2059.75 | 2059 |
| 16 | 2005.75 | 2005.25 | 2025.25 | 2035.75 |
| 32 | 1963.25 | 1967.25 | 2001.25 | 1992.75 |
| 64 | 1903 | 1904 | 1936.25 | 1939.75 |
| 128 | 1778.75 | 1779.75 | 1799 | 1806.75 |
| 256 | 1530.75 | 1526.5 | 1542.75 | 1541.25 |
| 512 | 1195 | 1189.75 | 1203.75 | 1198.5 |
| 1024 | 694.75 | 697 | 699 | 699.25 |
+-------------+----------+---------+---------+--------------+
| Total | 17169.25 | 17171 | 17408 | 17408 |
+-------------+----------+---------+---------+--------------+
As can be seen there is no consistent winner between SELECT 1 and SELECT * and the difference between the two approaches is negligible. The SELECT Not Null col and SELECT PK do appear slightly faster though.
All four of the queries degrade in performance as the number of columns in the table increases.
As the table is empty this relationship does seem only explicable by the amount of column metadata. For COUNT(1) it is easy to see that this gets rewritten to COUNT(*) at some point in the process from the below.
SET SHOWPLAN_TEXT ON;
GO
SELECT COUNT(1)
FROM master..spt_values
Which gives the following plan
|--Compute Scalar(DEFINE:([Expr1003]=CONVERT_IMPLICIT(int,[Expr1004],0)))
|--Stream Aggregate(DEFINE:([Expr1004]=Count(*)))
|--Index Scan(OBJECT:([master].[dbo].[spt_values].[ix2_spt_values_nu_nc]))
Attaching a debugger to the SQL Server process and randomly breaking whilst executing the below
DECLARE #V int
WHILE (1=1)
SELECT #V=1 WHERE EXISTS (SELECT 1 FROM ##T) OPTION(RECOMPILE)
I found that in the cases where the table has 1,024 columns most of the time the call stack looks like something like the below indicating that it is indeed spending a large proportion of the time loading column metadata even when SELECT 1 is used (For the case where the table has 1 column randomly breaking didn't hit this bit of the call stack in 10 attempts)
sqlservr.exe!CMEDAccess::GetProxyBaseIntnl() - 0x1e2c79 bytes
sqlservr.exe!CMEDProxyRelation::GetColumn() + 0x57 bytes
sqlservr.exe!CAlgTableMetadata::LoadColumns() + 0x256 bytes
sqlservr.exe!CAlgTableMetadata::Bind() + 0x15c bytes
sqlservr.exe!CRelOp_Get::BindTree() + 0x98 bytes
sqlservr.exe!COptExpr::BindTree() + 0x58 bytes
sqlservr.exe!CRelOp_FromList::BindTree() + 0x5c bytes
sqlservr.exe!COptExpr::BindTree() + 0x58 bytes
sqlservr.exe!CRelOp_QuerySpec::BindTree() + 0xbe bytes
sqlservr.exe!COptExpr::BindTree() + 0x58 bytes
sqlservr.exe!CScaOp_Exists::BindScalarTree() + 0x72 bytes
... Lines omitted ...
msvcr80.dll!_threadstartex(void * ptd=0x0031d888) Line 326 + 0x5 bytes C
kernel32.dll!_BaseThreadStart#8() + 0x37 bytes
This manual profiling attempt is backed up by the VS 2012 code profiler which shows a very different selection of functions consuming the compilation time for the two cases (Top 15 Functions 1024 columns vs Top 15 Functions 1 column).
Both the SELECT 1 and SELECT * versions wind up checking column permissions and fail if the user is not granted access to all columns in the table.
An example I cribbed from a conversation on the heap
CREATE USER blat WITHOUT LOGIN;
GO
CREATE TABLE dbo.T
(
X INT PRIMARY KEY,
Y INT,
Z CHAR(8000)
)
GO
GRANT SELECT ON dbo.T TO blat;
DENY SELECT ON dbo.T(Z) TO blat;
GO
EXECUTE AS USER = 'blat';
GO
SELECT 1
WHERE EXISTS (SELECT 1
FROM T);
/* ↑↑↑↑
Fails unexpectedly with
The SELECT permission was denied on the column 'Z' of the
object 'T', database 'tempdb', schema 'dbo'.*/
GO
REVERT;
DROP USER blat
DROP TABLE T
So one might speculate that the minor apparent difference when using SELECT some_not_null_col is that it only winds up checking permissions on that specific column (though still loads the metadata for all). However this doesn't seem to fit with the facts as the percentage difference between the two approaches if anything gets smaller as the number of columns in the underlying table increases.
In any event I won't be rushing out and changing all my queries to this form as the difference is very minor and only apparent during query compilation. Removing the OPTION (RECOMPILE) so that subsequent executions can use a cached plan gave the following.
+-------------+-----------+------------+-----------+--------------+
| Num of Cols | * | 1 | PK | Not Null col |
+-------------+-----------+------------+-----------+--------------+
| 2 | 144933.25 | 145292 | 146029.25 | 143973.5 |
| 4 | 146084 | 146633.5 | 146018.75 | 146581.25 |
| 8 | 143145.25 | 144393.25 | 145723.5 | 144790.25 |
| 16 | 145191.75 | 145174 | 144755.5 | 146666.75 |
| 32 | 144624 | 145483.75 | 143531 | 145366.25 |
| 64 | 145459.25 | 146175.75 | 147174.25 | 146622.5 |
| 128 | 145625.75 | 143823.25 | 144132 | 144739.25 |
| 256 | 145380.75 | 147224 | 146203.25 | 147078.75 |
| 512 | 146045 | 145609.25 | 145149.25 | 144335.5 |
| 1024 | 148280 | 148076 | 145593.25 | 146534.75 |
+-------------+-----------+------------+-----------+--------------+
| Total | 1454769 | 1457884.75 | 1454310 | 1456688.75 |
+-------------+-----------+------------+-----------+--------------+
The test script I used can be found here
Best way to know is to performance test both versions and check out the execution plan for both versions. Pick a table with lots of columns.
There is no difference in SQL Server and it has never been a problem in SQL Server. The optimizer knows that they are the same. If you look at the execution plans, you will see that they are identical.
Personally I find it very, very hard to believe that they don't optimize to the same query plan. But the only way to know in your particular situation is to test it. If you do, please report back!
Not any real difference but there might be a very small performance hit. As a rule of thumb you should not ask for more data than you need.
I have a table EmployeeMoves:
| EmployeeID | CityIDs
+------------------------------
| 24 | 23,21,22
| 25 | 25,12,14
| 29 | 1,2,5
| 31 | 7
| 55 | 11,34
| 60 | 7,9,21,23,30
I'm trying to figure out how to expand the comma-delimited values from the EmployeeMoves.CityIDs column to populate an EmployeeCities table, which should look like this:
| EmployeeID | CityID
+------------------------------
| 24 | 23
| 24 | 21
| 24 | 22
| 25 | 25
| 25 | 12
| 25 | 14
| ... and so on
I already have a function called SplitADelimitedList that splits a comma-delimited list of integers into a rowset. It takes the delimited list as a parameter. The SQL below will give me a table with split values under the column Value:
select value from dbo.SplitADelimitedList ('23,21,1,4');
| Value
+-----------
| 23
| 21
| 1
| 4
The question is: How do I populate EmployeeCities from EmployeeMoves with a single (even if complex) SQL statement using the comma-delimited list of CityIDs from each row in the EmployeeMoves table, but without any cursors or looping in T-SQL? I could have 100 records in the EmployeeMoves table for 100 different employees.
This is how I tried to solve this problem. It seems to work and is very quick in performance.
INSERT INTO EmployeeCities
SELECT
em.EmployeeID,
c.Value
FROM EmployeeMoves em
CROSS APPLY dbo.SplitADelimitedList(em.CityIDs) c;
UPDATE 1:
This update provides the definition of the user-defined function dbo.SplitADelimitedList. This function is used in above query to split a comma-delimited list to table of integer values.
CREATE FUNCTION dbo.fn_SplitADelimitedList1
(
#String NVARCHAR(MAX)
)
RETURNS #SplittedValues TABLE(
Value INT
)
AS
BEGIN
DECLARE #SplitLength INT
DECLARE #Delimiter VARCHAR(10)
SET #Delimiter = ',' --set this to the delimiter you are using
WHILE len(#String) > 0
BEGIN
SELECT #SplitLength = (CASE charindex(#Delimiter, #String)
WHEN 0 THEN
datalength(#String) / 2
ELSE
charindex(#Delimiter, #String) - 1
END)
INSERT INTO #SplittedValues
SELECT cast(substring(#String, 1, #SplitLength) AS INTEGER)
WHERE
ltrim(rtrim(isnull(substring(#String, 1, #SplitLength), ''))) <> '';
SELECT #String = (CASE ((datalength(#String) / 2) - #SplitLength)
WHEN 0 THEN
''
ELSE
right(#String, (datalength(#String) / 2) - #SplitLength - 1)
END)
END
RETURN
END
Preface
This is not the right way to do it. You shouldn't create comma-delimited lists in SQL Server. This violates first normal form, which should sound like an unbelievably vile expletive to you.
It is trivial for a client-side application to select rows of employees and related cities and display this as a comma-separated list. It shouldn't be done in the database. Please do everything you can to avoid this kind of construction in the future. If at all possible, you should refactor your database.
The Right Answer
To get the list of cities, properly expanded, from a table containing lists of cities, you can do this:
INSERT dbo.EmployeeCities
SELECT
M.EmployeeID,
C.CityID
FROM
EmployeeMoves M
CROSS APPLY dbo.SplitADelimitedList(M.CityIDs) C
;
The Wrong Answer
I wrote this answer due to a misunderstanding of what you wanted: I thought you were trying to query against properly-stored data to produce a list of comma-separated CityIDs. But I realize now you wanted the reverse: to query the list of cities using existing comma-separated values already stored in a column.
WITH EmployeeData AS (
SELECT
M.EmployeeID,
M.CityID
FROM
dbo.SplitADelimitedList ('23,21,1,4') C
INNER JOIN dbo.EmployeeMoves M
ON Convert(int, C.Value) = M.CityID
)
SELECT
E.EmployeeID,
CityIDs = Substring((
SELECT ',' + Convert(varchar(max), CityID)
FROM EmployeeData C
WHERE E.EmployeeID = C.EmployeeID
FOR XML PATH (''), TYPE
).value('.[1]', 'varchar(max)'), 2, 2147483647)
FROM
(SELECT DISTINCT EmployeeID FROM EmployeeData) E
;
Part of my difficulty in understanding is that your question is a bit disorganized. Next time, please clearly label your example data and show what you have, and what you're trying to work toward. Since you put the data for EmployeeCities last, it looked like it was what you were trying to achieve. It's not a good use of people's time when questions are not laid out well.
in Java the following is a common idiom:
if( null != obj && obj.getSomeNumber() > 0 ) { ... }
This will perform the length check only, if null != obj is true.
However, in a JPA NamedQuery this does not work:
#NamedQuery(
name = "query"
query = "SELECT o FROM SomeObjectList o WHERE o.someObject is not null AND o.someObject.someNumber > 0")
(This is what I've expected, as this would also not work in SQL.)
o.someObject is either 'null' or an foreign key to a table where SomeObjects are stored. (Each column of the table corresponds to an attribute of SomeObject.)
------------------------- ----------------------------
| Table: SomeObjectList | | Table: SomeObject |
------------------------- ----------------------------
| id | someObject | | id | number | name |
------------------------- ----------------------------
| 1 | 4 | | 3 | -4 | foo |
------------------------- ----------------------------
| 2 | null | | 4 | 2 | bar |
------------------------- ----------------------------
So I'd like to create a NamedQuery which will return all Objects from SomeObjectList which either have no object (someObject == null) or where SomeObject.number > 0.
Currently, I obtain all objects and check myself if someObject is set.
But is there a way to get an similar behavior in JPA or does I have to perform the checks on the returned objects?
edit: Added graphics and clarified the problem. (Thanks to James.)
You need to use an outer join for this.
Note your query is wrong, you want seem to want an OR not an AND, otherwise just remove the null check.
SELECT o FROM SomeObjectList o left join o.someObject so WHERE o.someObject is null OR so.someNumber > 0
Not sure I understand?
You don't even need the "not null", just the length > 0 will not return true for null?
Also your code is wrong, length is a function, not a navigation.
It should be,
SELECT o FROM SomeObject o WHERE LENGTH(o.arry) > 0
Or is arry a collection relationship? In this case you would need to use SIZE, and the join will also filter absent relationships.