I'm new in learning stored procedures in SQL.
I want to create a stored procedure for inserting values from automatic data by calculation.
Table Attendance:
EMPL_KODE |EMPL_NAME |DATE_IN |TIME_IN |TIME_OUT|TIME_IN |TIME_OUT
001 | Michel |25.04.2016 |06:50 |15:40 | |
002 | Clara |25.04.2016 |06:15 |15:43 | |
003 | Rafael |25.04.2016 |06:25 |15:45 | |
001 | Michel |26.04.2016 |06:23 |15:42 | |
002 | Clara |26.04.2016 |06:10 |15:41 | |
003 | Rafael |26.04.2016 |06:30 |15:42 | |
001 | Michel |27.04.2016 |06:33 |15:42 | |
002 | Clara |27.04.2016 |06:54 |15:44 | |
003 | Rafael |27.04.2016 |07:00 |15:45 | |
I want to fill TIME_IN and TIME_OUT values automatically by creating a stored procedure. Here is the code :
CREATE PROCEDURE InsertTotalEmployee
#TOTAL_MINUTES int,
#TOTAL_HOURS float
AS
BEGIN
INSERT INTO ATTENDANCE (TOTAL_MINUTES, TOTAL_HOURS)
VALUES (
SELECT
DATEDIFF(MINUTE, ATTENDANCE.TIME_IN, ATTENDANCE.TIME_OUT),
DATEDIFF(MINUTE, ATTENDANCE.TIME_IN, ATTENDANCE.TIME_OUT) / 60.0
)
END
After I write and execute my statement, a message error occurs:
Token unknown - line 2, column 5 #
I run the code using Flamerobin.
It looks like you are trying to use Microsoft SQL Server syntax in Firebird, that is not going to work.
For one, the # is not allowed like that in identifiers (unless you use double quotes around them), and the list of parameters must be enclosed in parentheses.
See the syntax of CREATE PROCEDURE. You need to change it to:
CREATE PROCEDURE InsertTotalEmployee(TOTAL_MINUTES int, TOTAL_HOURS float)
You also might want to change the datatype float to double precision, and the body of your stored procedure seems to be incomplete because you are selecting from nothing (a select requires a table to select from), and are missing a semicolon at the end of the statement.
All in all I suggest you study the Firebird language reference, then try to create a functioning insert and only then create a stored procedure around it.
Also note that when creating a stored procedure in Flamerobin, that you must switch statement terminators using set term otherwise Flamerobin can't send the stored procedure correctly, see also the first section in Procedural SQL (PSQL) Statements.
Related
I'm working on a new feature that involves labels for Apache AGE and I'm looking for tools with which I can work with.
In psql interface, when you input the command SELECT * FROM ag_catalog.ag_label; the following output is shown:
name | graph | id | kind | relation | seq_name
------------------+--------+----+------+-----------------------+-------------------------
_ag_label_vertex | 495486 | 1 | v | test._ag_label_vertex | _ag_label_vertex_id_seq
_ag_label_edge | 495486 | 2 | e | test._ag_label_edge | _ag_label_edge_id_seq
vtx_label | 495486 | 3 | v | test.vtx_label | vtx_label_id_seq
elabel | 495486 | 4 | e | test.elabel | elabel_id_seq
I came across this and wasn't able to figure out what kind of data I can retrieve from it, what is it used for or how can it help me.
Can you explain the seq_name column?
Seq_name refers to sequences. Sequences are single-row tables that can be thought of as 'number generators' that start at some minimum integer value and then increment as they are 'consumed'.
A sequence that is associated with a column can be used to assign values to it. For example, 'mytable_seq_id' associated with column 'id' in a particular table 'mytable' might start at 1. Then as you add more entries to mytable, the 'id' column begins to increment to 2,3 and so on.
Postgres docs on creating sequences:
https://www.postgresql.org/docs/current/sql-createsequence.html
As for AGE, here's a comment taken directly out of the 'graph_commands.c' source file. It describes how sequences are used to generate labels ids.
static Oid create_schema_for_graph(const Name graph_name)
{
char *graph_name_str = NameStr(*graph_name);
CreateSchemaStmt *schema_stmt;
CreateSeqStmt *seq_stmt;
TypeName *integer;
DefElem *data_type;
DefElem *maxvalue;
DefElem *cycle;
Oid nsp_id;
/*
* This is the same with running the following SQL statement.
*
* CREATE SCHEMA `graph_name`
* CREATE SEQUENCE `LABEL_ID_SEQ_NAME`
* AS integer
* MAXVALUE `LABEL_ID_MAX`
* CYCLE
*
* The sequence will be used to assign a unique id to a label in the graph.
*
* schemaname doesn't have to be graph_name but the same name is used so
* that users can find the backed schema for a graph only by its name.
*
* ProcessUtilityContext of this command is PROCESS_UTILITY_SUBCOMMAND
* so the event trigger will not be fired.
*/
Note that sequences are used in other functions in the AGE internals as well, and the above function is just one example.
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 use PostgreSQL and I have a table 'PERSON' in schema 'public' that looks like this:
+----+-------------+-------+----------------------------+
| id | internal_id | name | created |
+----+-------------+-------+----------------------------+
| 1 | P0001-XX00 | Bob | 2021-05-24 22:10:01.93025 |
+----+-------------+-------+----------------------------+
| 2 | P0001-CX00 | Tom | 2021-06-27 22:10:01.93025 |
+----+-------------+-------+----------------------------+
| 3 | P0002-XX00 | Anna | 2021-05-24 22:10:01.93025 |
+----+-------------+-------+----------------------------+
id -> bigint; internal_id -> character varying; name -> character varying; created -> timestamp without timezone
I need to write procedure that delete those records that are older than fixed timestamp, for example: now(). But as soon as such an old record has been found, I need to check if there are other records in the table which are not old yet and with the same first 5 characters in internal_id as the found old record. If there are such records, then I should not delete the old record.
So I wrote the following procedure with plpgsql and it seems to work:
BEGIN
DELETE FROM public."PERSON" AS t1
WHERE t1.created < now()
AND NOT EXISTS
(
SELECT
FROM public."PERSON" AS t2
WHERE left(t2.internal_id, 5) = left(t1.internal_id, 5)
AND t2.created >= now()
);
COMMIT;
END;
Questions:
Could it have been made more correct or prettier or cleaner? Perhaps, instead of using the left() function, it was necessary to use LIKE, or, in principle, to do it somehow differently?
Do you think this procedure has normal performance or it can be improved?
Thank you in advance!
That should work just fine.
For good performance, create an index:
CREATE INDEX ON public."PERSON" (left(internal_id, 5), created);
How do I check in postgres that a varchar contains 'aaa' or 'bbb'?
I tried myVarchar IN ('aaa', 'bbb') but, obviously, it's true when myvarchar is exactly equal to 'aaa' or 'bbb'.
for multiple similarity check the best fit in terms of speed and laconic syntax would be
SIMILAR TO '%(aaa|bbb|ccc)%'
you can use ANY & LIKE operators together.
SELECT * FROM "myTable" WHERE "myColumn" LIKE ANY( ARRAY[ '%aaa%', '%bbb%' ] );
Assuming this is your table:
CREATE TABLE t
(
myVarchar varchar
) ;
INSERT INTO t (myVarchar)
VALUES
('something aaa else'),
('also some bbb'),
('maybe ccc') ;
-- (some random data, this query is PostgreSQL specific)
INSERT INTO t (myVarchar)
SELECT
random()::varchar
FROM
generate_series(1, 10000) ;
SQL Standard approach:
You can do (in all SQL standard databases):
SELECT
*
FROM
t
WHERE
myVarchar LIKE '%aaa%' or myVarchar LIKE '%bbb%' ;
and you'll get:
| myvarchar |
| :----------------- |
| something aaa else |
| also some bbb |
PostgreSQL specific approaches
Specifically for PostgreSQL, you can use a (single) regex with multiple values to look for:
SELECT
*
FROM
t
WHERE
myVarchar ~ 'aaa|bbb' ;
| myvarchar |
| :----------------- |
| something aaa else |
| also some bbb |
dbfiddle here
If you need quick finds, you can use trigram indexes, like this:
CREATE EXTENSION pg_trgm; -- Only needed if extension not already installed
CREATE INDEX myVarchar_like_idx
ON t
USING GIST (myVarchar gist_trgm_ops);
... the query using LIKE will be much faster.
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.