I have a better-sqlite3 statement that orders and ranks my database, and I have a IN statement so I can select more than 1 row. That is where I run into an issue, I need to fetch multiple rows based on a dynamic array of IDs.
My SQLITE Statement looks like this:
Table.prepare('SELECT *, RANK () OVER (ORDER BY amount DESC) rank FROM table WHERE user IN(?)');
And I try to get from this statement with things like this:
getAll.get(['1','2','3']);
getAll.get('6,9,4');
getAll.get('7','5','8');
I get an error:
RangeError: Too many parameter values were provided
How exactly can I select multiple values without knowing the length of my array (so ?,? won't cut it), and allow as much values as possible? I used ?* and I get a Syntax error.
I am using better-sqlite3 for Node.JS
Instead of IN use the operator LIKE:
SELECT *, RANK () OVER (ORDER BY amount DESC) rank
FROM table
WHERE ',' || ? || ',' LIKE '%,' || user || ',%'
and pass the list as 1 string of comma separated values (without spaces):
all('6,9,4');
Related
I need the equivalent of this Count with Case for a Firebird 3 database. I get an error when I try it:
SQL error code = -104.
Invalid usage of boolean expression.
I was just recently introduced to the Case command and I can't seem to rework it myself. I managed to get it to work with SQLite just fine.
The intent is to do an AND operation, the Where can't do an AND because the keywords are in rows.
SELECT Count((CASE WHEN keywords.keyword LIKE '%purchased%'
THEN 1 END) AND
(CASE WHEN keywords.keyword LIKE '%item%'
THEN 1 END)) AS TRows
FROM products
LEFT OUTER JOIN keywords_products ON
products.product_rec_id = keywords_products.product_rec_id
LEFT OUTER JOIN keywords ON
keywords_products.keyword_rec_id = keywords.keyword_rec_id
WHERE (keywords.keyword LIKE '%purchased%' OR
keywords.keyword LIKE '%item%')
I have three SQLite tables, a products table, a keywords_products table, and a keywords table.
CREATE TABLE products (
product_rec_id INTEGER PRIMARY KEY NOT NULL,
name VARCHAR (100) NOT NULL
);
CREATE TABLE keywords_products (
keyword_rec_id INTEGER NOT NULL,
product_rec_id INTEGER NOT NULL
);
CREATE TABLE keywords (
keyword_rec_id INTEGER PRIMARY KEY NOT NULL,
keyword VARCHAR (50) NOT NULL UNIQUE
);
The keywords_products table holds the the record id of a product and a record id of a keyword. Each product can be assigned multiple keywords in the keywords table.
The keyword table looks like this:
keyword_rec_id keyword
-------------- -----------
60 melee
43 scifi
87 water
The keywords_products table looks like this (one keyword can be assigned to many products):
keyword_rec_id product_rec_id
-------------- --------------
43 1
60 1
43 2
87 3
The products table looks like this:
product_rec_id name
-------------- --------------
1 Scifi Melee Weapons
2 Scifi Ray Weapon
3 Lake House
I'm assuming you want to count how many rows there are where both conditions are true.
The error occurs because you can't use AND between integer values. The values must be true booleans.
So, change your code to
Count((CASE WHEN keywords.keyword LIKE '%purchased%'
THEN TRUE END) AND
(CASE WHEN keywords.keyword LIKE '%item%'
THEN TRUE END))
However that is far too complex. You can simplify your expression to
count(nullif(
keywords.keyword LIKE '%purchased%' and keywords.keyword LIKE '%item%',
false))
The use of NULLIF is needed because COUNT will count all non-NULL values (as required by the SQL standard), and false is non-NULL as well. So to achieve the (assumed) desired effect, we transform false to NULL using NULLIF.
You have to use ONE single CASE expression with multiple WHEN branches.
Making Boolean functions of distinct CASE expressions just makes no sense - the CASE is not Boolean function itself.
You can see rules and an example at CASE.
case
when Age >= 18 then 'Yes'
when Age < 18 then 'No'
end;
Remake you two CASE clauses to a single CASE clause following this pattern.
However, you only use CASE when you can not move filters and conditions into standard part of SQL select. Normal approach would be to minimize data that SQL engine has to fetch, using pre-filtering. The CASE uses post-filtering, it makes SQL engine to fetch all the data, regardless if it needs it or not, and then discard the unneeded fetched data. That is redundant work slowing down the process.
In your case you already extracted the condition into WHERE clause, that is good.
SELECT
...
WHERE (keywords.keyword LIKE '%purchased%')
OR (keywords.keyword LIKE '%item%')
Since you pre-filter your data stream to always contain "item" or "purchase" then the CASE clause of yours would always return 1 on all rows selected under this WHERE pre-filtering. Hence - just remove the redundant CASE clause and put "1" instead.
SELECT Count(1)
FROM products
LEFT JOIN keywords_products ON products.product_rec_id = keywords_products.product_rec_id
LEFT JOIN keywords ON keywords_products.keyword_rec_id = keywords.keyword_rec_id
WHERE (keywords.keyword LIKE '%purchased%')
OR (keywords.keyword LIKE '%item%')
Now, given that WHERE clause is processed logically after JOINing, this your query de facto transformed LEFT JOINs into FULL JOINs ( your WHERE clause just discards rows with NULL "keyword" column values ) but aghain in unreliable and inefficient method. Since you do not want to have "keyword is NULL" kind of rows anyway - just convert your left joins to normal joins.
I understand that SQLite does not have If-Else condition check, and people have been using case statements to get around it. However I want to do a if condition check before executing a certain portion of the script, like the following:
IF (condition = true)
INSERT INTO tableA(A, B)
VALUES (a, b)
....
END
From what I have been trying, case statement doesn't seem to work. Is there any way I can accomplish the above in SQLite?
Thanks for all your help!
You could perhaps use an INSERT SELECT
INSERT INTO table SELECT ...;
The second form of the INSERT statement contains a SELECT statement
instead of a VALUES clause.
A new entry is inserted into the table for
each row of data returned by executing the SELECT statement.
If a
column-list is specified, the number of columns in the result of the
SELECT must be the same as the number of items in the column-list.
Otherwise, if no column-list is specified, the number of columns in
the result of the SELECT must be the same as the number of columns in
the table.
Any SELECT statement, including compound SELECTs and SELECT
statements with ORDER BY and/or LIMIT clauses, may be used in an
INSERT statement of this form.
extract from SQL As Understood By SQLite - INSERT
e.g.
INSERT into xxx
SELECT null as id,
CASE
WHEN filesize < 1024 THEN 'just a little bit'
WHEN filesize >= 1024 THEN 'quite a bit'
END AS othercolumn
FROM filesizes
WHERE filesize < 1024 * 1024
The above will insert rows into table xxx which consists of 2 columns id (rowid alias) and othercolumn according to the results (2 columns id (always set as null) and othercolumn) of the SELECT, which is selecting from the filesizes table where the value of the filesize column is less than 1024 * 1024 (1048576), thus conditionally inserting.
Furthermore, if the filesize is less than 1024 the othercolumn is set to just a little bit, if the filesize is greater than 1023 then the othercolumn is set to quite a bit. So making the conditional insert more complex.
Assuming the filesizes table were :-
The running the above would result in :-
I have a SQLite table where one column contains a JSON array containing 0 or more values. Something like this:
id|values
0 |[1,2,3]
1 |[]
2 |[2,3,4]
3 |[2]
What I want to do is "unfold" this into a list of all distinct values contained within the arrays of that column.
To start, I am using the JSON1 extension's json_each function to extract a table of values from a row:
SELECT
value
FROM
json_each(
(
SELECT
values
FROM
my_table
WHERE
id == 2
)
)
Where I can vary the id (2, above) to select any row in the table.
Now, I am trying to wrap this in a recursive CTE so that I can apply it to each row across the entire table and union the results. As a first step I replicated (roughly) the results from above as follows:
WITH RECURSIVE result AS (
SELECT null
UNION ALL
SELECT
value
FROM
json_each(
(
SELECT
values
FROM
my_table
WHERE
id == 2
)
)
)
SELECT * FROM result;
As the next step I had originally planned to make id a variable and increment it (in a similar manner to the first example in the documentation, but haven't been able to get that to work.
I have gone through the other examples in the documentation, but they are somewhat more complex and I haven't been able to distill those down to see how they might apply to this problem.
Can someone provide a simple example of how to solve this (or a similar problem) with a recursive CTE?
Of course, my goal is to solve the problem with or without CTEs so Im also happy to hear if there is a better way...
You do not need a recursive CTE for this.
To call json_each for multiple source rows, use a join:
SELECT t1.id, t2.value
FROM my_table AS t1
JOIN json_each((SELECT "values" FROM my_table WHERE id = t1.id)) AS t2;
I have written a stored procedure below in MSSQL. It's throwing error in the ORDER BY clause.
a) It works fine if I put only one condition in ORDER BY clause.
b) I am not sure why it is executing both conditions of the CASE statement in the ORDER BY clause while executing the procedure. Ideally if the first condition is met, it should skip the second.
The error message is:
Error: Msg 408, Level 16, State 1, Line 3
A constant expression was encountered in the ORDER BY list, position 2.
This is the query:
SELECT *
FROM tb_officemaster
WHERE 1 = 1
AND officecity LIKE '%gurgaon%'
AND minprice > 100
AND maxprice < 1000
ORDER BY
CASE WHEN 'priceasc'='priceasc' THEN "minprice" END ASC,
CASE WHEN 'pricedesc'='priceasc' THEN minprice END DESC
Look at your CASE expression in your ORDER BY clause as below. Here the condition 'priceasc'='priceasc' is a constant expression and is always true no matter what and actually doesn't really makes any sense. It will not evaluate to anything. ORDER BY somehow has to evaluate the given expression to a row's value and order accordingly. In your case, THEN "minprice" is as well a constant.
ORDER BY CASE WHEN 'priceasc'='priceasc' THEN "minprice" END ASC
Per your posted query, the order by clause doesn't make sense and you can just omit it. Your query can simply be
select *
from tb_officemaster
where 1=1
and officecity like'%gurgaon%'
and minprice >100
and maxprice < 1000
Per your comment, change your ORDER BY to be like below
ORDER BY CASE WHEN pricedesc = priceasc THEN minprice END DESC
I want to execute a SELECT query on a database table that has 6 key fields, let's assume they are keyA, keyB, ..., keyF.
As input parameters to my ABAP function module I do receive an internal table with exactly that structure of the key fields, each entry in that internal table therefore corresponds to one tuple in the database table.
Thus I simply need to select all tuples from the database table that correspond to the entries in my internal table.
Furthermore, I want to aggregate an amount column in that database table in exactly the same query.
In pseudo SQL the query would look as follows:
SELECT SUM(amount) FROM table WHERE (keyA, keyB, keyC, keyD, keyE, keyF) IN {internal table}.
However, this representation is not possible in ABAP OpenSQL.
Only one column (such as keyA) is allowed to state, not a composite key. Furthermore I can only use 'selection tables' (those with SIGN, OPTIOn, LOW, HIGH) after they keyword IN.
Using FOR ALL ENTRIES seems feasible, however in this case I cannot use SUM since aggregation is not allowed in the same query.
Any suggestions?
For selecting records for each entry of an internal table, normally the for all entries idiom in ABAP Open SQL is your friend. In your case, you have the additional requirement to aggregate a sum. Unfortunately, the result set of a SELECT statement that works with for all entries is not allowed to use aggregate functions. In my eyes, the best way in this case is to compute the sum from the result set in the ABAP layer. The following example works in my system (note in passing: using the new ABAP language features that came with 7.40, you could considerably shorten the whole code).
report zz_ztmp_test.
start-of-selection.
perform test.
* Database table ZTMP_TEST :
* ID - key field - type CHAR10
* VALUE - no key field - type INT4
* Content: 'A' 10, 'B' 20, 'C' 30, 'D' 40, 'E' 50
types: ty_entries type standard table of ztmp_test.
* ---
form test.
data: lv_sum type i,
lt_result type ty_entries,
lt_keys type ty_entries.
perform fill_keys changing lt_keys.
if lt_keys is not initial.
select * into table lt_result
from ztmp_test
for all entries in lt_keys
where id = lt_keys-id.
endif.
perform get_sum using lt_result
changing lv_sum.
write: / lv_sum.
endform.
form fill_keys changing ct_keys type ty_entries.
append :
'A' to ct_keys,
'C' to ct_keys,
'E' to ct_keys.
endform.
form get_sum using it_entries type ty_entries
changing value(ev_sum) type i.
field-symbols: <ls_test> type ztmp_test.
clear ev_sum.
loop at it_entries assigning <ls_test>.
add <ls_test>-value to ev_sum.
endloop.
endform.
I would use FOR ALL ENTRIES to fetch all the related rows, then LOOP round the resulting table and add up the relevant field into a total. If you have ABAP 740 or later, you can use REDUCE operator to avoid having to loop round the table manually:
DATA(total) = REDUCE i( INIT sum = 0
FOR wa IN itab NEXT sum = sum + wa-field ).
One possible approach is simultaneous summarizing inside SELECT loop using statement SELECT...ENDSELECT statement.
Sample with calculating all order lines/quantities for the plant:
TYPES: BEGIN OF ls_collect,
werks TYPE t001w-werks,
menge TYPE ekpo-menge,
END OF ls_collect.
DATA: lt_collect TYPE TABLE OF ls_collect.
SELECT werks UP TO 100 ROWS
FROM t001w
INTO TABLE #DATA(lt_werks).
SELECT werks, menge
FROM ekpo
INTO #DATA(order)
FOR ALL ENTRIES IN #lt_werks
WHERE werks = #lt_werks-werks.
COLLECT order INTO lt_collect.
ENDSELECT.
The sample has no business sense and placed here just for educational purpose.
Another more robust and modern approach is CTE (Common Table Expressions) available since ABAP 751 version. This technique is specially intended among others for total/subtotal tasks:
WITH
+plants AS (
SELECT werks UP TO 100 ROWS
FROM t011w ),
+orders_by_plant AS (
SELECT SUM( menge )
FROM ekpo AS e
INNER JOIN +plants AS m
ON e~werks = m~werks
GROUP BY werks )
SELECT werks, menge
FROM +orders_by_plant
INTO TABLE #DATA(lt_sums)
ORDER BY werks.
cl_demo_output=>display( lt_sums ).
The first table expression +material is your internal table, the second +orders_by_mat quantities totals selected by the above materials and the last query is the final output query.