Taking a closer look at the execution plan XML, notice these problematic statistics:
<Wait WaitType="ASYNC_NETWORK_IO" WaitTimeMs="1328" WaitCount="403"/>
<QueryTimeStats CpuTime="353" ElapsedTime="1853"/>
The query spent 1.3 seconds waiting on the results to be consumed by the application. The query only ran for 1.8 seconds total. So the ...
For a LIMIT 1, Postgres may estimate it to be faster to traverse the index supporting the ORDER BY and just keep filtering until the first row is found. This is fast as long as more than a few rows qualify and one of those pops up early according to ORDER BY. But it is (very) slow if no qualifying row pops up early, or even a worst case scenario if no ...
What is currently happening
When running your query, the table scan, stream agg & compute scalar operators are not evaluated at runtime.
Why is it happening
The apply NL join means that for each row in #Docs, return a row from #Docsitems that matches the predicate. This predicate should be WHERE IDDocs = D.ID
But the compute scalar operator (EXPR1007)...
As per my understanding in above scenario we do not need order by as index have those columns already sorted
That understanding is incorrect, and that plan shows one reason why. A parallel index scan doesn't output rows in index order, as each thread reads at a different location in the sort order. You can't expect rows in any particular order without an ...
The table in the question isn't partitioned. I assume the intended definitions are:
CREATE PARTITION FUNCTION DemoPartitionFunction (datetime)
AS RANGE RIGHT
FOR VALUES (DATEADD(dd, DATEDIFF(dd, 0, GETUTCDATE()), -7),
DATEADD(dd, DATEDIFF(dd, 0, GETUTCDATE()), -6),
DATEADD(dd, DATEDIFF(dd, 0, GETUTCDATE()), -5),
It thinks it is going to find 78722, but it really finds 16, so that is going to lead to some bad plans.
When a value in the in-list is not present in the MCV list of the stats table, it guesses their frequency using the n_distinct value, which is probably way off (you didn't answer my question about that). The way it does this is to take the number of ...
You should be able to get the estimated query plan in SSMS without running the query.
If you do, you'll see that SQL Server is not going to be able to use partition elimination because you have a function on the partitioning column. Just like using a function on an indexed column prevents SQL Server from using the index, using a function on a partitioning ...
One possible cause for this sudden increase in duration is that there is another process blocking this query from making progress.
You mentioned that you have query store enabled. I would run a query like this, and look for the point where avg_duration jumps up from 2 hours to 6 hours (after 9/15):
BigQuery reduces how much data is scanned in a couple scenarios:
You have a partitioned table, and you filter on the partitioning column.
You have a clustered table, and you filter on one of the columns used for clustering.
For other types of filters, however, such as if you don't partition or cluster a table, you will incur the cost of scanning the entire ...
Applying functions to columns in WHERE and JOIN clause predicates prevents indexes from being used efficiently.
RTRIM is unnecessary since trailing spaces are ignored during string comparison so that can be removed.
Update the underlying data to remove leading [Order ID] spaces so the LTRIM is unnecessary in queries. You can then modify the JOIN clause can ...
You may want to use EXISTS operator with Sub-query, but that serve in different scenarios, in your case moving NotificationQueue table down to the sub-query can make you to do join that your looking for, following is the example of same:
op.Name AS [OpportunityName],
ua.Email AS OwnerEmail,
The simple solution is to modify the ORDER BY condition so that the semantics are unchanged, but PostgreSQL cannot use the index any more:
SELECT * FROM mcqueen_base_imagemeta2
WHERE image_id IN ( 123, ... )
ORDER BY id + 0 DESC
Can it be?
select distinct s2.user_name
from submission s1
join submission s2
on s1.md5 = s2.copy_of
or s1.copy_of = s2.copy_of
or s1.copy_of = s2.md5
where s1.user_name = ?1
and s2.copy_of is not null;
s1.md5 = s2.copy_of will match submission which is copy from this user.
s1.copy_of = s2.copy_of or s1.copy_of = s2.md5 will match ...
There is nothing obviously wrong with the plan, so there is no obvious large optimization to be done. You are fundamentally doing a lot of work, and it takes a lot of time.
I would probably start by taking a step back and looking at your business case. Why do you need exactly this output? Could you perhaps "need" something easier to optimize? Like, ...
One thing stands out clearly for me - this warning in the XML query plan:
<PlanAffectingConvert ConvertIssue="Seek Plan" Expression="N'Public'=CONVERT_IMPLICIT(nvarchar(20),[r].[SecurityLevel],0)"/>
A little known speed killer in SQL Server is passing an nvarchar() parameter to use in an indexed seek against a ...
Not having the full table definition, I'm going to take a stab at what it might be. Based on the screenshot in your question, the table could look something like this:
CREATE TABLE dbo.TaskSchedulerItem (
TaskSchedulerItemID int IDENTITY(1,1),
Since only the estimated plan is present, these are going to be some guesses.
WHERE j.Status >= 60 AND (j.Status <= 70 OR (dsp.BatchNumber > 1 AND x.CabinetCount IS NULL))
Creates a filter far in the execution plan:
on this part:
(j.Status <= 70 OR (dsp.BatchNumber > 1 AND x.CabinetCount IS NULL))
You could try adding a union ...
Clustered Index is must.Unless we do not have table structure and their description we cannot say which column should be CI.
Provide volume of data in each table and expected volume of output.
DATEPART(hour,TABLE1.COL1) BETWEEEN 1 AND 2 is not SARGAble.
So you can rewrite the query as below.Always check the performance with parameter instead of HARD coded ...
I would use a self-join
select u1.name, string_agg(s2.user_name, ',') as other users
from users u1
join submission s1 on u1.name = s1.user_name
join submission s2 on s1.md5 = s2.copy_of
where name = ?1
group by u1.name;
I dont have the reputation to add comments so I will take a stab at an answer. My experience is with MSSQL but I think it is transferable here.
It seems like this query is doing a bunch of redundant checks.
Do you get different results from this:
SELECT distinct job_id, truck_id, customer from jobs where driver_id = '$driver'
AND truck_id in
Very often joining to a VALUES clause improves performance in these cases:
JOIN "Phrase" ON "TranslationText"."phrase" = "Phrase"."id"
[.. your other joins ...]
($1, $2, $3, $4),
($5, $6, $7, $8),
) as v(org_text, org_lang, new_lang, description)
on v.org_text = "...
Put together, Request A WHERE IN Request B is very long. Is that
Yes, that's fairly common when elaborating queries. In the first case, the IN(...) clause has only a handful of constants. The planner knows exactly how many values and how frequent they are in the table, so it has a good chance to find an optimal execution plan (in this case, an ...
It depends on a number of things. You list postgres in one of your tags, so it should be noted that the CTE will be materialised in full as CTEs are an optimisation fence that block predicate push-down. I'm not sure about sqlite, the other DB you list in the tags, but this is not the case for all databases, SQL Server for one can optimise across CTEs.
Please try this:
DELETE FROM journal
WHERE id NOT IN (
WHERE j.created_at >= 636742944000000000
ORDER BY j.created_at DESC
Please make sure to create the index on created_at and id.
In additional, I think id in a table should be unique/primary key.