I want to dynamically filter through data based on condition, which is stored in specific column. This condition can change for every row.
For example I have a table my_table with couple of columns, one of them is called foo, where there are couple of filter conditions such as AND bar > 1 or in the next row AND bar > 2 or in the next row AND bar = 33.
I have a query which looks like:
SELECT something from somewhere
LEFT JOIN otherthing on some_condition
WHERE first_condition AND second_condition AND
here_i_want_dynamically_load_condition_from_my_table.foo
What is the correct way to do it? I have read some articles about dynamic queries, but I am not able to find a correct way.
This is impossible in pure SQL: at query time, the planner has to know your exact logic. Now, you can hide it away in a function (in pseudo-sql):
CREATE FUNCTION do_I_filter_or_not(some_id) RETURNS boolean AS '
BEGIN
value = select some_value from table where id = some_id
condition_type = SELECT ... --Query a condition type for this row
condition_value = SELECT ... --Query a condition value for this row
if condition_type = 'equals' and condition_value = value
return true
if condition_type = 'greater_than' and condition_value < value
return true
if condition_type = 'lower_than' and condition_value > value
return true
return false;
END;
'
LANGUAGE 'plpgsql';
And query it like this:
SELECT something
FROM somewhere
LEFT JOIN otherthing on some_condition
WHERE first_condition
AND second_condition
AND do_I_filter_or_not(somewhere.id)
Now the performance will be bad: you have to invoke that function potentially on every row in the query; triggering lots of subqueries.
Thinking about it, if you just want <, >, =, and you have a table (filter_criteria) describing for each id what the criteria is you can do it:
CREATE TABLE filter_criteria AS(
some_id integer,
equals_threshold integer,
greater_than_threshold integer,
lower_than_threshold integer
-- plus a check that two thresholds must be null, and one not null
)
INSERT INTO filter_criteria (1, null, 5, null); -- for > 5
And query like this:
SELECT something
FROM somewhere
LEFT JOIN otherthing on some_condition
LEFT JOIN filter_criteria USING (some_id)
WHERE first_condition
AND second_condition
AND COALESCE(bar = equals_threshold, true)
AND COALESCE(bar > greater_than_threshold, true)
AND COALESCE(bar < lower_than_threshold, true)
The COALESCEs are here to default to not filtering (AND true) if the threshold is missing (bar = equals_threshold will yield null instead of a boolean).
The planner has to know your exact logic at query time: now you're just doing 3 passes of filtering, with a =, <, > check each time. That'd still be more performant than idea #1 with all the subquerying.
Related
Often times I find myself writing code such as:
const fooId = await pool.oneFirst(sql`
SELECT id
FROM foo
WHERE nid = 'BAR'
`);
await pool.query(sql`
INSERT INTO bar (foo_id)
VALUES (${fooId})
`);
oneFirst is a Slonik query method that ensures that the query returns exactly 1 result. It is needed there, because foo_id also accepts NULL as a valid value, i.e. if SELECT id FROM foo WHERE status = 'BAR' returned no results, this part of the program would fail silently.
The problem with this approach is that it causes two database roundtrips for what should be a single operation.
In a perfect world, postgresql supported assertions natively, e.g.
INSERT INTO bar (foo_id)
VALUES
(
(
SELECT id
FROM foo
WHERE nid = 'BAR'
EXPECT 1 RESULT
)
)
EXPECT 1 RESULT is a made up DSL.
The expectation is that EXPECT 1 RESULT would cause PostgreSQL to throw an error if that query returns anything other than 1 result.
Since PostgreSQL does not support this natively, what are the client-side solutions?
You can use
const fooId = await pool.oneFirst(sql`
INSERT INTO bar (foo_id)
SELECT id
FROM foo
WHERE nid = 'BAR'
RETURNING foo_id;
`);
This will insert all rows matched by the condition in foo into bar, and Slonik will throw if that was not exactly one row.
Alternatively, if you insist on using VALUES with a subquery, you can do
INSERT INTO bar (foo_id)
SELECT tmp.id
FROM (VALUES (
SELECT id
FROM foo
WHERE nid = 'BAR'
)) AS tmp
WHERE tmp.id IS NOT NULL
Nothing would be inserted if no row did match the condition and your application could check that. Postgres would throw an exception if multiple rows were matched, since a subquery in an expression must return at most one row.
That's a cool idea.
You can cause an error on extra results by putting the select in a context where only one result is expected. For example, just writing
SELECT (SELECT id from foo WHERE nid = 'bar')
will get you a decent error message on multiple results: error: more than one row returned by a subquery used as an expression.
To handle the case where nothing is returned, you could use COALESCE.
SUMMARY: I've two tables I want to derive info out of: family_values (family_name, item_regex) and product_ids (product_id) to be able to update the property family_name in a third.
Here the plan is to grab a json array from the small family_values table and use the column value item_regex to do a test match against the product_id for every row in product_ids.
MORE DETAILS: Importing static data from CSV to table of orders. But, in evaluating cost of goods and market value I'm needing to continuously determine family from a prefix regex (item_regex from family_values) match on the product_id.
On the client this looks like this:
const families = {
FOOBAR: 'Big Ogre',
FOOBA: 'Wood Elf',
FOO: 'Valkyrie'
};
// And to find family, and subsequently COGs and Market Value:
const findFamily = product_id => Object.keys(families).find(f => new RegExp('^' + f).test(product_id));
This is a huge hit for the client so I made a family_values table in PG to include a representative: family_name, item_regex, cogs, market_value.
Then, the product_ids has a list of only the products the app cares about (out of millions). This is actually used with an insert trigger 'on before' to ignore any CSV entries that aren't in the product_ids view. So, I guess after that the product_ids view could be taken out of the equation because the orders, after inserting readonly data, has its own matching product_id. It does NOT have family_name, so I still have the issue of determining that client-side.
PSUEDO CODE: update family column of orders with family_name from family_values regex match against orders.product_id
OR update the product_ids table with a new family column and use that with the existing on insert trigger (used to left pad zeros and normalize data right now). Now I'm thinking this may be just an update as suggested, but not real good with regex in PG. I'm a PG novice.
PROBLEM: But, I'm having a hangup in doing what I thought would be like a JS Array Find operation. The family_values have been sorted on the item_regex so that the most strict match would be on top, and therefor found first.
For example, with sorting we have:
family_values_array = [
{"family_name": "Big Ogre", "item_regex": "FOOBAR"},
{"family_name": "Wood Elf", "item_regex": "FOOBA"},
{"family_name": "Valkyrie", "item_regex": "FOO"}]
So, that the comparison of product_id of ^FOOBA would yield family "Wood Elf".
SOLUTION:
The solution I finally came about using was simply using concat to write out the front-anchored regex. It was so simple in the end. The key line I was missing is:
select * into family_value_row from iol.family_values
where lvl3_id = product_row.lvl3_id and product_row.product_id
like concat(item_regex, '%') limit 1;
Whole function:
create or replace function iol.populate_families () returns void as $$
declare
product_row record;
family_value_row record;
begin
for product_row in
select product_id, lvl3_id from iol.products
loop
-- family_name is what we want after finding the BEST match fr a product_id against item_regex
select * into family_value_row from iol.family_values
where lvl3_id = product_row.lvl3_id and product_row.product_id like concat(item_regex, '%') limit 1;
-- update family_name and value columns
update iol.products set
family_name = family_value_row.family_name,
cog_cents = family_value_row.cog_cents,
market_value_cents = family_value_row.market_value_cents
where product_id = product_row.product_id;
end loop;
end;
$$
LANGUAGE plpgsql;
Use concat as updated above:
select * into family_value_row from iol.family_values
where lvl3_id = product_row.lvl3_id and product_row.product_id
like concat(item_regex, '%') limit 1;
I'm trying to decipher another programmer's code who is long-gone, and I came across a select statement in a stored procedure that looks like this (simplified) example:
SELECT #Table2.Col1, Table2.Col2, Table2.Col3, MysteryColumn = CASE WHEN y.Col3 IS NOT NULL THEN #Table2.MysteryColumn - y.Col3 ELSE #Table2.MysteryColumn END
INTO #Table1
FROM #Table2
LEFT OUTER JOIN (
SELECT Table3.Col1, Table3.Col2, Col3 = SUM(#Table3.Col3)
FROM Table3
INNER JOIN #Table4 ON Table4.Col1 = Table3.Col1 AND Table4.Col2 = Table3.Col2
GROUP BY Table3.Col1, Table3.Col2
) AS y ON #Table2.Col1 = y.Col1 AND #Table2.Col2 = y.Col2
WHERE #Table2.Col2 < #EnteredValue
My question, what does the fourth column of the primary selection do? does it produce a boolean value checking to see if the values are equal? or does it set the #Table2.MysteryColumn equal to some value and then inserts it into #Table1? Or does it just update the #Table2.MysteryColumn and not output a value into #Table1?
This same thing seems to happen inside of the sub-query on the third column, and I am equally at a loss as to what that does as well.
MysteryColumn = gives the expression a name also called a column alias. The fact that a column in the table#2 also has the same name is besides the point.
Since it uses INTO syntax it also gives the column its name in the resulting temporary table. See the SELECT CLAUSE and note | column_alias = expression and the INTO CLAUSE
I have a table with a varchar column, and I want to find values that match a certain number. So lets say that column contains the following entries (except with millions of rows in real life):
123456789012
2345678
3456
23 45
713?2
00123456789012
So I decide I want all the rows which are numerically 123456789012 write a statement that looks something like this:
SELECT * FROM MyTable WHERE CAST(MyColumn as bigint) = 123456789012
It should return the first and last row, but instead the whole query blows up because it can't convert the "23 45" and "713?2" to bigint.
Is there another way to do the conversion that will return NULL for values that can't convert?
SQL Server does NOT guarantee boolean operator short-circuit, see On SQL Server boolean operator short-circuit. So all solution using ISNUMERIC(...) AND CAST(...) are fundamentally flawed (they may work, but hey can arbitrarily fail later dependiong on the generated plan). A better solution is using CASE, as Thomas suggests: CASE ISNUMERIC(...) WHEN 1 THEN CAST(...) ELSE NULL END. But, as gbn pointed out, ISNUMERIC is notoriously finicky in identifying what 'numeric' means and many cases where one would expect it to return 0 it returns 1. So mixing the CASE with the LIKE:
CASE WHEN MyRow NOT LIKE '%[^0-9]%' THEN CAST(MyRow as bigint) ELSE NULL END
But the real problem is that if you have millions of rows and you have to search them like this, you'll always end up scanning end-to-end since the expression is not SARG-able (no matter how we rewrite it). The real issue here is data purity, and should be addressed at the appropriate level, where the data is populated. Another thing to consider is if is possible to create a persisted computed column with this expression and create a filtered index on it which eliminates NULL (ie. non-numeric). That would speed up things a little.
If you are using SQL Server 2012 you can use the 2 new methods:
TRY_CAST()
TRY_CONVERT()
Both methods are equivalent. They return a value cast to the specified data type if the cast succeeds; otherwise, returns null. The only difference is that CONVERT is SQL Server specific, CAST is ANSI. using CAST will make your code more portable (although not sure if any other database provider implements TRY_CAST)
ISNUMERIC will accept empty string and values like 1.23 or 5E-04 so could be unreliable.
And you don't know what order things will be evaluated in so it could still fail (SQL is declarative, not procedural, so the WHERE clause probably won't be evaluated left to right)
So:
you want to accept value that consist only of the characters 0-9
you need to materialise the "number" filter so it's applied before CAST
Something like:
SELECT
*
FROM
(
SELECT TOP 2000000000 *
FROM MyTable
WHERE MyColumn NOT LIKE '%[^0-9]%' --double negative rejects anything except 0-9
ORDER BY MyColumn
) foo
WHERE
CAST(MyColumn as bigint) = 123456789012 --applied after number check
Edit: quick example that fails.
CREATE TABLE #foo (bigintstring varchar(100))
INSERT #foo (bigintstring )VALUES ('1.23')
INSERT #foo (bigintstring )VALUES ('1 23')
INSERT #foo (bigintstring )VALUES ('123')
SELECT * FROM #foo
WHERE
ISNUMERIC(bigintstring) = 1
AND
CAST(bigintstring AS bigint) = 123
SELECT *
FROM MyTable
WHERE ISNUMERIC(MyRow) = 1
AND CAST(MyRow as float) = 123456789012
The ISNUMERIC() function should give you what you need.
SELECT * FROM MyTable
WHERE ISNUMERIC(MyRow) = 1
AND CAST(MyRow as bigint) = 123456789012
And to add a case statement like Thomas suggested:
SELECT * FROM MyTable
WHERE CASE(ISNUMERIC(MyRow)
WHEN 1 THEN CAST(MyRow as bigint)
ELSE NULL
END = 123456789012
http://msdn.microsoft.com/en-us/library/ms186272.aspx
SELECT *
FROM MyTable
WHERE (ISNUMERIC(MyColumn) = 1) AND (CAST(MyColumn as bigint) = 123456789012)
Additionally you can use a CASE statement in order to get null values.
SELECT
CASE
WHEN (ISNUMERIC(MyColumn) = 1) THEN CAST(MyColumn as bigint)
ELSE NULL
END AS 'MyColumnAsBigInt'
FROM tableName
If you require additional filtering, for numerics which are not valid to be cast to bigint, you can use the following instead of ISNUMERIC:
PATINDEX('%[^0-9]%',MyColumn)) = 0
If you need decimal values instead of integers, cast to float instead and change the regex to '%[^0-9.]%'
I have a large database, that I want to do some logic to update new fields.
The primary key is id for the table harvard_assignees
The LOGIC GOES LIKE THIS
Select all of the records based on id
For each record (WHILE), if (state is NOT NULL && country is NULL), update country_out = "US" ELSE update country_out=country
I see step 1 as a PostgreSQL query and step 2 as a function. Just trying to figure out the easiest way to implement natively with the exact syntax.
====
The second function is a little more interesting, requiring (I believe) DISTINCT:
Find all DISTINCT foreign_keys (a bivariate key of pat_type,patent)
Count Records that contain that value (e.g., n=3 records have fkey "D","388585")
Update those 3 records to identify percent as 1/n (e.g., UPDATE 3 records, set percent = 1/3)
For the first one:
UPDATE
harvard_assignees
SET
country_out = (CASE
WHEN (state is NOT NULL AND country is NULL) THEN 'US'
ELSE country
END);
At first it had condition "id = ..." but I removed that because I believe you actually want to update all records.
And for the second one:
UPDATE
example_table
SET
percent = (SELECT 1/cnt FROM (SELECT count(*) AS cnt FROM example_table AS x WHERE x.fn_key_1 = example_table.fn_key_1 AND x.fn_key_2 = example_table.fn_key_2) AS tmp WHERE cnt > 0)
That one will be kind of slow though.
I'm thinking on a solution based on window functions, you may want to explore those too.