There is scenario, I have table with 40 columns and I have to select all data of a table (including all columns). I have created a clustered index on the table and its including Clustered Index Scan while fetching full data set from the table.
I know that without any filter or join key, SQL Server will choose Clustered Index Scan instead of Clustered Index Seek. But, I want to have optimize execution plan by optimizing Clustered Index Scan into Clustered Index Seek. Is there any solution to achieve this? Please share.
Below is the screenshot of the execution plan:
Something is not quite right in the question / request, because what you are asking for will perform badly. I suspect it comes from mis-understanding what a clustered index is.
The clustered index - which is perhaps better stated as a clustered table - is the table of data, its not separate to the table, it is the table. If the order of the data on the table is already based on ITEM ID then the scan is the most efficient access method for your query (especially given the select *) - you do not want to seek in this scenario at all - and I don't believe that it is your scenario due to the sort operator.
If the clustered table is ordered based on another field, then you would need an additional non-clustered index to provide the correct order. You would then try to force a plan which was a non-clustered index scan, nested loop to a clustered index seek. That can be achieved using query hints, most likely an INNER LOOP JOIN would cause the seek - but a FORCESEEK also exists which can be used.
Performance wise this second option is never going to win - you are in effect looking at a tipping point notion (https://www.sqlskills.com/blogs/kimberly/the-tipping-point-query-answers/)
Well, I was trying to achieve the same, I wanted an index seek instead of an index scan on my top query.
SELECT TOP 5 id FROM mytable
Here is the execution plan being shown for the query:
I even tried the Offset Fetch Next approach, the plan was same.
To avoid a index scan, I included a fake primary key filter like below:
SELECT TOP 5 id FROM mytable where id != 0
I know, I won't have a 0 value in my primary key, so I added it in top query, which was resolved to an index seek instead of index scan:
Even though, the query plan comparison gives operation cost as similar to other, for index seek and scan in this regard. But I think to achieve index seek this way, it is an extra operation for the db to perform because it has to compare whether the id is 0 or not. Which we entirely do not need it to do if we want the top few records.
Related
I have a patient table with a few columns, and a clustered index on column ID and a non-clustered index on column birth.
create clustered index CI_patient on dbo.patient (ID)
create nonclustered index NCI_patient on dbo.patient (birth)
Here are my queries:
select * from patient
select ID from patient
select birth from patient
Looking at the execution plan, the first query is 'clustered index scan' (which is understandable because the table is a clustered table), the third one is 'index scan nonclustered' (which is also understandable because this column has a nonclustered index)
My question is why the second one is 'index scan nonclustered'? This column suppose to have a clustered index, in this sense, should that be clustered index scan? Any thoughts on this?
Basically, your second query wants to get all ID values from the table (no WHERE clause or anything).
SQL Server can do this two ways:
clustered index scan - basically a full table scan to read all the data from all rows, and extract the ID from each row - would work, but it loads the WHOLE table, one by one
do a scan across the non-clustered index, because each non-clustered index also includes the clustering column(s) on its leaf level. Since this is a index that is much smaller than the full table, to do this, SQL Server will need to load fewer data pages and thus can provide the answer - all ID values from all rows - faster than when doing a full table scan (clustered index scan)
The cost-based optimizer in SQL Server just picks the more efficient route to get the answer to the question you've asked with your second query.
I have two different queries in SQL Server and I want to clarify
how the execution plan would be different, and
which of them is more efficient
Queries:
SELECT *
FROM table_name
WHERE column < 2
and
SELECT column
FROM table_name
WHERE column < 2
I have a non-clustered index on column.
I used to use Postgresql and I am not familiar with SQL Server and these kind of indexes.
As I read many questions here I kept two notes:
When I have a non-clustered index, I need one more step in order to have access to data
With a non-clustered index I could have a copy of part of the table and I get a quicker response time.
So, I got confused.
One more question is that when I have "SELECT *" which is the influence of a non-clustered index?
1st query :
Depending on the size of the data you might face lookup issues such as Key lookup and RID lookups .
2nd query :
It will be faster because it will not fetch columns that are not part of the index , though i recommend using covering index ..
I recommend you check this blog post
The first select will use the non-clustered index to find the clustering key [clustered index exists] or page and slot [no clustered index]. Then that will be used to get the row. The query plan will be different depending on your STATS (the data).
The second query is "covered" by the non-clustered index. What that means is that the non-clustered index contains all of the data that you are selecting. The clustering key is not needed, and the clustered index and/or heap is not needed to provide data to the select list.
I have a query that fails to execute with "Could not allocate a new page for database 'TEMPDB' because of insufficient disk space in filegroup 'DEFAULT'".
On the way of trouble shooting I am examining the execution plan. There are two costly steps labeled "Clustered Index Scan (Clustered)". I have a hard time find out what this means?
I would appreciate any explanations to "Clustered Index Scan (Clustered)" or suggestions on where to find the related document?
I would appreciate any explanations to "Clustered Index Scan
(Clustered)"
I will try to put in the easiest manner, for better understanding you need to understand both index seek and scan.
SO lets build the table
use tempdb GO
create table scanseek (id int , name varchar(50) default ('some random names') )
create clustered index IX_ID_scanseek on scanseek(ID)
declare #i int
SET #i = 0
while (#i <5000)
begin
insert into scanseek
select #i, 'Name' + convert( varchar(5) ,#i)
set #i =#i+1
END
An index seek is where SQL server uses the b-tree structure of the index to seek directly to matching records
you can check your table root and leaf nodes using the DMV below
-- check index level
SELECT
index_level
,record_count
,page_count
,avg_record_size_in_bytes
FROM sys.dm_db_index_physical_stats(DB_ID('tempdb'),OBJECT_ID('scanseek'),NULL,NULL,'DETAILED')
GO
Now here we have clustered index on column "ID"
lets look for some direct matching records
select * from scanseek where id =340
and look at the Execution plan
you've requested rows directly in the query that's why you got a clustered index SEEK .
Clustered index scan: When Sql server reads through for the Row(s) from top to bottom in the clustered index.
for example searching data in non key column. In our table NAME is non key column so if we will search some data in the name column we will see clustered index scan because all the rows are in clustered index leaf level.
Example
select * from scanseek where name = 'Name340'
please note: I made this answer short for better understanding only, if you have any question or suggestion please comment below.
Expanding on Gordon's answer in the comments, a clustered index scan is scanning one of the tables indexes to find the values you are doing a where clause filter, or for a join to the next table in your query plan.
Tables can have multiple indexes (one clustered and many non-clustered) and SQL Server will search the appropriate one based upon the filter or join being executed.
Clustered Indexes are explained pretty well on MSDN. The key difference between clustered and non-clustered is that the clustered index defines how rows are stored on disk.
If your clustered index is very expensive to search due to the number of records, you may want to add a non-clustered index on the table for fields that you search for often, such as date fields used for filtering ranges of records.
A clustered index is one in which the terminal (leaf) node of the index is the actual data page itself. There can be only one clustered index per table, because it specifies how records are arranged within the data page. It is generally (and with some exceptions) considered the most performant index type (primarily because there is one less level of indirection before you get to your actual data record).
A "clustered index scan" means that the SQL engine is traversing your clustered index in search for a particular value (or set of values). It is one of the most efficient methods for locating a record (beat by a "clustered index seek" in which the SQL Engine is looking to match a single selected value).
The error message has absolutely nothing to do with the query plan. It just means that you are out of space on TempDB.
I have been having issues with performance and timeouts due to a clustered index scan. However another seemingly identical database did not have the same issue.
Turns out the COMPATIBILITY_LEVEL flag on the db was different... the version with COMPATIBILITY_LEVEL 100 was using the scan, the db with level 130 wasn't. Performance difference is huge (from more than 1 minute to less that 1 second for same query)
ALTER DATABASE [mydb] SET COMPATIBILITY_LEVEL = 130
If you hover over the step in the query plan, SSMS displays a description of what the step does. That will give you a baseline understanding of "Clustered Index Scan (Clustered)" and all other steps involved.
So, we have a table, InventoryListItems, that has several columns. Because we're going to be looking for rows at times based on a particlar column (g_list_id, a foreign key), we have that foreign key column placed into a non-clustered index we'll call MYINDEX.
So when I search for data like this:
-- fake data for example
DECLARE #ListId uniqueidentifier
SELECT #ListId = '7BCD0E9F-28D9-4F40-BD67-803005179B04'
SELECT *
FROM [dbo].[InventoryListItems]
WHERE [g_list_id] = #ListId
I expected that it would use the MYINDEX index to find just the needed rows, and then look up the information in those rows. So not as good as just finding everything we need in the index itself, but still a big win over doing a full scan of the table.
But instead it seems that I'm still getting a clustered index scan. I can't figure out why that would happen.
If I do something like SELECTing only the values in the included columns of the index, it does what I would expect, an index seek, and just pulls everything from the index.
But if I SELECT *, why does it just bail on the index and do a scan when it seems like it would still benefit greatly from using it because it's referenced in the WHERE clause?
Since you're doing a SELECT * and thus you retrieve all columns, SQL Server's query optimizer may have decided it's easier and more efficient to just do a clustered index scan - since it needs to go to the clustered index leaf level to get all the columns anyway (and doing a seek first, and then a key lookup to actually get the whole data page, is quite an expensive operation - scan might just be more efficient in this setup).
I'm almost sure if you try
SELECT g_list_id
FROM [dbo].[InventoryListItems]
WHERE [g_list_id] = #ListId
then there will be an index seek instead (since you're only retrieving a single column - not everything).
That's one of the reasons why I would recommend to be extra careful when using SELECT * .... - try to avoid it if ever possible.
Since both a Table Scan and a Clustered Index Scan essentially scan all records in the table, why is a Clustered Index Scan supposedly better?
As an example - what's the performance difference between the following when there are many records?:
declare #temp table(
SomeColumn varchar(50)
)
insert into #temp
select 'SomeVal'
select * from #temp
-----------------------------
declare #temp table(
RowID int not null identity(1,1) primary key,
SomeColumn varchar(50)
)
insert into #temp
select 'SomeVal'
select * from #temp
In a table without a clustered index (a heap table), data pages are not linked together - so traversing pages requires a lookup into the Index Allocation Map.
A clustered table, however, has it's data pages linked in a doubly linked list - making sequential scans a bit faster. Of course, in exchange, you have the overhead of dealing with keeping the data pages in order on INSERT, UPDATE, and DELETE. A heap table, however, requires a second write to the IAM.
If your query has a RANGE operator (e.g.: SELECT * FROM TABLE WHERE Id BETWEEN 1 AND 100), then a clustered table (being in a guaranteed order) would be more efficient - as it could use the index pages to find the relevant data page(s). A heap would have to scan all rows, since it cannot rely on ordering.
And, of course, a clustered index lets you do a CLUSTERED INDEX SEEK, which is pretty much optimal for performance...a heap with no indexes would always result in a table scan.
So:
For your example query where you select all rows, the only difference is the doubly linked list a clustered index maintains. This should make your clustered table just a tiny bit faster than a heap with a large number of rows.
For a query with a WHERE clause that can be (at least partially) satisfied by the clustered index, you'll come out ahead because of the ordering - so you won't have to scan the entire table.
For a query that is not satisified by the clustered index, you're pretty much even...again, the only difference being that doubly linked list for sequential scanning. In either case, you're suboptimal.
For INSERT, UPDATE, and DELETE a heap may or may not win. The heap doesn't have to maintain order, but does require a second write to the IAM. I think the relative performance difference would be negligible, but also pretty data dependent.
Microsoft has a whitepaper which compares a clustered index to an equivalent non-clustered index on a heap (not exactly the same as I discussed above, but close). Their conclusion is basically to put a clustered index on all tables. I'll do my best to summarize their results (again, note that they're really comparing a non-clustered index to a clustered index here - but I think it's relatively comparable):
INSERT performance: clustered index wins by about 3% due to the second write needed for a heap.
UPDATE performance: clustered index wins by about 8% due to the second lookup needed for a heap.
DELETE performance: clustered index wins by about 18% due to the second lookup needed and the second delete needed from the IAM for a heap.
single SELECT performance: clustered index wins by about 16% due to the second lookup needed for a heap.
range SELECT performance: clustered index wins by about 29% due to the random ordering for a heap.
concurrent INSERT: heap table wins by 30% under load due to page splits for the clustered index.
http://msdn.microsoft.com/en-us/library/aa216840(SQL.80).aspx
The Clustered Index Scan logical and physical operator scans the clustered index specified in the Argument column. When an optional WHERE:() predicate is present, only those rows that satisfy the predicate are returned. If the Argument column contains the ORDERED clause, the query processor has requested that the rows' output be returned in the order in which the clustered index has sorted them. If the ORDERED clause is not present, the storage engine will scan the index in the optimal way (not guaranteeing the output to be sorted).
http://msdn.microsoft.com/en-us/library/aa178416(SQL.80).aspx
The Table Scan logical and physical operator retrieves all rows from the table specified in the Argument column. If a WHERE:() predicate appears in the Argument column, only those rows that satisfy the predicate are returned.
A table scan has to examine every single row of the table. The clustered index scan only needs to scan the index. It doesn't scan every record in the table. That's the point, really, of indices.