I have a query that looks like this:
--Updated To remove Distinct per Aaron Bertrand's suggestion in the comments
SELECT TOP 100 ord.OrderId
FROM Customer cust
JOIN CustomerOrder ord
ON ord.CustomerId = cust.CustomerId
WHERE cust.FirstName LIKE (#firstName + '%')
ORDER BY ord.CreatedWhen DESC
And I have an index like this:
CREATE NONCLUSTERED INDEX [IX_MyIndex] ON CustomerOrder
(
OrderId DESC,
CustomerId DESC,
CreatedWhen Desc
)
GO
When I run my query, the index gets used, but it is an index scan. And it gives this message:
PROBE([Bitmap1011],[MyDatabase].[order].[CustomerOrder].[OrderId] as [ord].[OrderId],N'[IN ROW]')
The output list consists of the OrderId and CreatedWhen.
What is this PROBE doing and why I don't get an Index Seek?
UPDATE:
The FirstName column on the Customer table does have an index that is being used in an IndexSeek.
CREATE NONCLUSTERED INDEX [IX_Customer_FirstName] ON Customer
(
[FirstName] ASC
)
GO
The reason that an Index Scan gets used is because your WHERE clause predicate is based on CustomerId, but it appears as the SECOND column in the list of columns in your non-clustered index [IX_MyIndex].
If you want an Index Seek to be performed, you would need to specify a new non-clustered index just on column CustomerId.
And that would essentially be a good practice - have two separate NC indices for OrderId and CustomerId. So when you join Customer and CustomerOrder tables, it will use the NC Index for CustomerId, and when you join Order and CustomerOrder tables, it will use the NC index for OrderId.
Refer to this article to read more about the difference between a multi-column non-clustered index (which you currently have) and multiple non-clustered indexes (which I proposed using).
[UPDATE]
But creating separate non-clustered indexes is not sufficient in getting an Index Seek everytime. That will depend on the columns being selected in the query, and the size of the data being read - based on that the query optimizer will accordingly make a decision on whether to use an Index Seek or an Index Scan. See this answer for more information.
[UPDATE Feb 8, 2021]
At a high-level, the PROBE function in question would essentially try to verify whether the CustomerOrder.OrderId column value is present in the Customer table. This is achieved internally through the using of bitmaps and hash keys, and you can read in detail about it here.
Note that a PROBE is not specific to an Index Scan or an Index Seek. It is simply a function that is utilized for verifying matches (based on a certain hash keyed column(s)) between two tables in a join.
Simple reason: your FirstName column isn't in the index. It must scan every row to see if the row matches the pattern you want.
Related
I'm struggling to identify effective indexes (or rewrite the query) to improve a query with the following confounding predicates:
JOIN on a date from one table being in range - between two date fields on second table (one is nullable, one is not nullable in PK).
The date used is actually the value in date field (nullable) +1.
WHERE clauses includes OR logic on multiple flag fields.
The simplified version of the query is:
select
d.dim_date_id
,f.dim_provider_id
,f.dim_event_id
,d.date
from DWH.dbo.tbl_fact_outcome f
join DWH.dbo.tbl_dim_date d on DATEADD(DAY,1,d.date) between f.known_from and f.known_to
where
f.known_from > getdate()-12
and (d.flag_latest_day = 'Y' or d.flag_end_of_month = 'Y' or (d.flag_end_of_week = 'Y' AND d.flag_latest_week = 'Y'))
and d.flag_future_day = 'N'
and f.deleted = 0
tbl_fact_outcome has these indexes:
PK clustered index on input_form_id, known_from
Non-unique Nonclustered index on deleted, known_from, known_to (INCLUDES the required _dim_id fields)
tbl_dim_date has these indexes:
PK clustered index on dim_date_id
Non-unique nonclustered index on flag_future_day, date (INCLUDES relevant flag fields)
At present, it estimates 853 rows but returns 16,784.
Here is the query plan:
https://www.brentozar.com/pastetheplan/?id=rydKb_3AI
Statistics are up to date.
I have tried re-ordering the covering indexes but no improvement.
I'm totally stumped as to what else to try with indexes or the code itself to improve performance, so any pointers appreciated.
EDIT 05/07/2020
Ruled out following suggestions here:
Filtered index (on deleted) on tbl_fact_outcome - less than 1% of records would be filtered out, so not worthwhile
Filtered index (using entire WHERE clause from query) on tbl_dim_date - not possible to use OR in index
Index on tbl_dim_date with INCLUDEd fields as key fields - tried this, made no difference, not used by optimizer.
Guessing all/most queries filter on deleted I would suggest a filtered index.
CREATE NONCLUSTERED INDEX TodoNewIndexName ON DWH.dbo.tbl_fact_outcome (
known_from ASC
,known_to ASC
)
INCLUDE (dim_event_id,dim_provider_id)
WHERE deleted = 0;
If this query is really running frequently you could also consider using a filterd index for tbl_dim_date. This will probably only be used by this query, since the where is an exact match of your query:
CREATE NONCLUSTERED INDEX TodoNewIndexName ON DWH.dbo.tbl_dim_date (DATE ASC)
WHERE (
d.flag_latest_day = 'Y'
OR d.flag_end_of_month = 'Y'
OR (
d.flag_end_of_week = 'Y'
AND d.flag_latest_week = 'Y'
)
)
AND d.flag_future_day = 'N'
If you don't want a filterd index on the flag fields. You should add the flag fields to the index instead of includes.
CREATE NONCLUSTERED INDEX TodoNewIndexName ON DWH.dbo.tbl_dim_date (
DATE ASC
,flag_latest_day ASC
,flag_end_of_month ASC
,flag_end_of_week ASC
,flag_latest_week ASC
)
What this should do is get rid of the Index Spool (Eager Spool) more info about eager spool.
Eager index spools are often a sign that a useful permanent index is
missing from the database schema. This is not always the case, as the
streaming table-valued function examples show.
Has your date dimension a nextDay column or something? If not you can add this column and replace DATEADD(DAY,1,d.date) with this new column.
I have a table [Documents] with the following columns:
Name (string)
Status (string)
DateCreated [datetime]
This table has around 1 million records. All three of these columns have an index (a single index for each one).
When I run this query:
select top 50 *
from [Documents]
where (Name = 'None' OR Name is null OR Name = '')
and Status = 'New';
Execution is really fast (300 ms.)
If I run the same query but with the ORDER BY clause, it's really slow (3000 ms)
select top 50 *
from [Documents]
where (Name = 'None' OR Name is null OR Name = '')
and Status = 'New'
order by DateCreated;
I understand that its searching in another index (DateCreated), but should it really be that much slower? If so, why? Anything I can do to speed this query up (a composite index)?
Thanks
BTW: All Indexes including DateCreated have really low fragmentation, in fact I ran a reorganize and it didn't change a thing.
As far as why the query is slower, the query is required to return the rows "in order", so it either needs to do a sort, or it needs to use an index.
Using the index with a leading column of CreatedDate, SQL Server can avoid a sort. But SQL Server would also have to visit the pages in the underlying table to evaluate whether the row is to be returned, looking at the values in Status and Name columns.
If the optimizer chooses not to use the index with CreatedDate as the leading column, then it needs to first locate all of the rows that satisfy the predicates, and then perform a sort operation to get those rows in order. Then it can return the first fifty rows from the sorted set. (SQL Server wouldn't necessarily need to sort the entire set, but it would need to go through that whole set, and do sufficient sorting to guarantee that it's got the "first fifty" that need to be returned.
NOTE: I suspect you already know this, but to clarify: SQL Server honors the ORDER BY before the TOP 50. If you wanted any 50 rows that satisfied the predicates, but not necessarily the 50 rows with the lowest values of DateCreated,you could restructure/rewrite your query, to get (at most) 50 rows, and then perform the sort of just those.
A couple of ideas to improve performance
Adding a composite index (as other answers have suggested) may offer some improvement, for example:
ON Documents (Status, DateCreated, Name)
SQL Server might be able to use that index to satisfy the equality predicate on Status, and also return the rows in DateCreated order without a sort operation. SQL server may also be able to satisfy the predicate on Name from the index, limiting the number of lookups to pages in the underlying table, which it needs to do for rows to be returned, to get "all" of the columns for the row.
For SQL Server 2008 or later, I'd consider a filtered index... dependent on the cardinality of Status='New' (that is, if rows that satisfy the predicate Status='New' is a relatively small subset of the table.
CREATE NONCLUSTERED INDEX Documents_FIX
ON Documents (Status, DateCreated, Name)
WHERE Status = 'New'
I would also modify the query to specify ORDER BY Status, DateCreated, Name
so that the order by clause matches the index, it doesn't really change the order that the rows are returned in.
As a more complicated alternative, I would consider adding a persisted computed column and adding a filtered index on that
ALTER TABLE Documents
ADD new_none_date_created AS
CASE
WHEN Status = 'New' AND COALESCE(Name,'') IN ('','None') THEN DateCreated
ELSE NULL
END
PERSISTED
;
CREATE NONCLUSTERED INDEX Documents_FIXP
ON Documents (new_none_date_created)
WHERE new_none_date_created IS NOT NULL
;
Then the query could be re-written:
SELECT TOP 50 *
FROM Documents
WHERE new_none_date_created IS NOT NULL
ORDER BY new_none_date_created
;
If DateCreated field means insertion time to table, you can create an integer id field and order by that integer field.
You need an index by 2 columns: (Name, DateCreated). The order of fields in the index is important. So, replace your index for just Name with a new index for two columns (Name, DateCreated).
Im a begginer. I know indexes are necessary for performance boosts, but i want to know how they actually work behind the scenes. Beforehand, I used to think that we should make indexes on those columns which are included in where clause (which I realized is wrong)
For example, SELECT * from MARKS where marks_obtained > 50
Consider that there's a clustered index on primary key of this table and I created a non-clustered index on marks_obtained column as its there in my where clause.
My perception: So the leaf nodes will be containing pointers to clustered index and as clustered index points to actual rows, it will select entire rows (due to asteric in my query)
Scenario
I came across following query (from AdventureWorks DB on which a non-clustered index was created) which works fine and took less than a second to execute 3200000 rows until a new column was inserted into it:
Query
SELECT x.*
INTO#X
FROM dbo.bigProduct AS p
CROSS APPLY
(
SELECT TOP 1000 *
FROM dbo.bigTransactionHistory AS bth
WHERE
bth.ProductId = p.bth.ProductId
ORDER BY
TransactionDate DESC
) AS x
WHERE
p.ProductId BETWEEN 1000 AND 7500
GO
NEW INSERTED COLUMN
ALTER TABLE dbo.bigTransactionHistory
ADD CustomerId INT NULL
After insertion of above column it took 17 seconds! means 17 times slower. A non-clusered index was now missing CustomerId column in the index. Just after including CustomerId, problem was gone.
Question CustomerId seemed to be the culprit until it was added to the index. BUT HOW???
The execution plan would answer this but I'll make a guess: The non-clustered index was no longer enough to satisfy the query after the additional column had been added. This can cause the index to not be used anymore. It also can cause one clustered index seek per row.
Learn to read execution plans. Turn on the "actual execution plan" feature routinely for each query that you test.
I'm trying to optimize my INNER JOIN statements on the following tables:
[articlegroups] contains ~700 rows
[products] contains ~150.000 rows
[products_category_mapping] contains 1 up to 3 rows for each product in [products] (so anywhere between 150.000 and 450.000 rows)
Here's my current query:
SELECT ga.label_sp,ga.label_en,ga.slug_sp,ga.slug_en,ga.pagetitle_sp,ga.pagetitle_en,ga.image_sp,ga.image_en,ga.description_sp,ga.description_en,ga.metadescription_sp,ga.metadescription_en
FROM articlegroups ga WITH (NOLOCK)
INNER JOIN products_category_mapping pcm on pcm.articlegroup_id=ga.id
INNER JOIN products gp on gp.id=pcm.artikelid
WHERE gp.id=<PRODUCTID> AND ga.catlevel=0
I read here http://www.sql-server-performance.com/2006/tuning-joins/ that a thing I can do is to add indexes to the columns on which the tables are joined.
Now I wonder what would result in the best performance:
Adding an index to products_category_mapping.artikelid and/or to products_category_mapping.articlegroup_id and what kind of index? Should I add indexes to both columns? Should I make one of them clustered and if so which one?
I have now added indexes to both columns and a clustered index on products_category_mapping.artikelid since I though that last column could have the most different results and would require the most speed. I'm not sure if I'm correct in what I'm doing now though.
ARTICLEGROUPS has just 700 rows.This is a small table and you can try not indexing this as well. The columns used here are GA.ID, GA.CATLEVEL. May be you can try the below index.
Create Index IX_id on ARTICLEGROUPS (id) Include (CATLEVEL asc);
PRODUCTS has 150000 rows, and column used is GP.ID. If LABEL and PAGE are not from PRODUCTS, try
Create Clustered Index IX_id on PRODUCTS (id);
else create
Create Index IX_id on PRODUCTS (id) Include (..); -- Pls fill include part.
PRODUCTS_CATEGORY_MAPPING has 150000 < rows. Columns used PCM.ARTICLEGROUP_ID and PCM.ARTIKELID. try the below and see.
Create Index IX_agid on PRODUCTS_CATEGORY_MAPPING (ARTICLEGROUP_ID) Include (..) --If LABEL or PAGE is from this table add thosem coumns in the include part)
Create Index IX_aid on PRODUCTS_CATEGORY_MAPPING (ARTIKELID) Include (..) --If LABEL or PAGE is from this table add those columns in the include part)
See the execution plan for the query after adding index. I am adding this in the answer part, as i found it very clumsy when I wrote this in comment part, hope this will help you.
I have the following query:
Select TOP 5000
CdCl.SubId
From dbo.PanelCdCl CdCl WITH (NOLOCK)
Inner Join dbo.PanelHistory PH ON PH.SubId = CdCl.SubId
Where CdCl.PanelCdClStatusId IS NULL And PH.LastProcessNumber >= 1605
Order By CdCl.SubId
The query plan looks as follows:
Both the PanelCdCl and PanelHistory tables have a clustered index / primary key on SubId, and it's the only column in the index. There is exactly one row for each SubId in each table. Both tables have ~35M total rows in them.
I'm curious why the query plan is showing a clustered index scan on PanelHistory when the join is being done on the clustered index column.
It's not scanning PanelHistory's clustered index(SubId) to find a SubId, it's scanning on it to find all rows where LastProcessNumber >= 1605. This is the first logical step.
Then it likewise scans PanelCdCl to find all non-null PanelCdClStatusId rows. Then since they had the same index (SubId), they are both already sorted on the Join column, so it can do a Merge-Join without an additional sort. (Merge-Join is almost always the most efficient if it doesn't have to re-sort the input rows).
Then it doesn't have to do a Sort for the ORDER BY, because it's already in SubId order.
And finally, it does the TOP, which has to be after everything else (by the rules of SQL clause logical execution ordering).
So the only place it tests SubId values is in the Merge-Join, it never pushes it down to the scans. This would probably remain true if it did a Hash-Join instead. Only for a Nested-Loop Join would it have to push the SubId test down as a seek on a table, and that should only be the lower branch, not the upper one.
The merge join operator needs two sorted inputs. The clustered key is SubId in both tables which means that the scan in PanelHistory will give the rows in correct order. The clustered key is included in all non clustered key indexes so because of that you will have all rows in NCI IX_PanelCdCl_PanelCdClStatusId where PanelCdClStatusId is null ordered by SubId as well so that can also be used directly by the merge join.
What you see here is actually two scans, one of the clustered key in PanelHistory with a residual predicate on LastProcessNumber > 1605 and one index range scan in IX_PanelCdCl_PanelCdClStatusId as long as PanelCdClStatusId is null.
They will however not scan the entire table/index. The query is executed from left to right in the query plan where select is asking for one row at a time until there is no more rows to be had. That means that the top operator will stop asking for new rows from the merge join when it has the required 5000 rows.