Are inserts quicker to heap or clustered tables?

Is it quicker and/or lower overhead to insert into a heap vs. a clustered table?
I don’t know. So I decided to do a test. Some background information first:

The test was inspired from a sidebar with Gert-Jan Strik in the open newsgroups. Basically I expressed that a heap doesn’t automatically carry lower overhead… just because it is a heap. Now, heaps vs. clustered tables is a huge topic with many aspects. I will not cover anything else here except inserts into a heap vs. a table which is clustered on an ever increasing key. No other indexes. There will be no fragmentation. I do not cover searches, covering etc. Only the pure insert aspect. OK? Good!

One might think that a heap has lower overhead because it is a … heap. But hang on for a second and think about what happens when you do an insert:

Heap:
SQL Server need to find where the row should go. For this it uses one or more IAM pages for the heap, and it cross references these to one or more PFS pages for the database file(s). IMO, there should be potential for a noticable overhead here. And even more, with many users hammering the same table I can imagine blocking (waits) against the PFS and possibly also IAM pages.

Clustered table:
Now, this is dead simple. SQL server navigates the clustered index tree and find where the row should go. Since this is an ever increasing index key, each row will go to the end of the table (linked list).

The result:
So what is the conclusion? I did several executions of the code at the end of this post, with some variations. Basically there was no or very little difference whith only one user. I.e., no contention to the GAM or PFS pages. This was pretty consistent for below three scenarios:

  1. Insert with subselect. I.e., this inserts lots of rows in the same statement.
  2. Insert in a loop (one insert and row per iteration), many rows in the same transaction.
  3. Insert in a loop, one row per transaction.

Now the difference between 2 and 3 is important.
With many transactions, we incur an overhead of force-log-write-at-commit *for each row*. I.e., much more overhead against the transaction log. And indeed, the timings between 2 and 3 for one of my executions (10000 rows) showed that 2 took on average 650 ms where the same number for 3 was 5600 ms. This is about 9 times longer!!! Now, this was more or less expected, but another important aspect is when we have several users. With many users, we might run into blocking on the PFS and IAM pages. Also, with several users it is meaningless to do it all in one transaction since we will block and essentially single-thread the code anyhow. I.e., the only revelant measure where we run many users is the loop construction where each row is its own transaction (3).

There was indded a noticeable difference when I executed several inserts in parallell and had each insert in its own transaction (for clustered table vs. heap table).

Some numbers:
I did 4 repeated testsĀ and calculated average execution time for inserting 10000 rows for a thread. With 6 parallel thread I had 22 seconds for a clustered table and 29 seconds for a heap table. With 10 threads I had 31 seconds for a clustered table and 42 seconds for a heap table.

I didn’t find performance difference more than a couple of percents for batch inserts, when I single threaded (only one thread pumping inserts), or when I had all inserts in the loop as one transaction.

Now, I would need lots of more time to run exchaustive tests, but my interpretation is that with many users doing inserts, there is an noticable overhead for the heap vs clustering on a increasing key.

The code:
Note that for parallell executions, I recommend starting the DoTheInserts procedure using SQLCMD, a BAT file and START. As always, read the code carefully (so you understand it) and execute at your own risk.

——————————————–
–Create the database etc.
——————————————–
USE master SET NOCOUNT ON
GO
IF DB_ID(‘TestDb’) IS NOT NULL DROP DATABASE TestDb
GO
–Makes files large enough so that inserts don’t causes autogrow
CREATE DATABASE TestDb
ONĀ  PRIMARY
(NAME = ‘TestDb’, FILENAME = ‘C:\TestDb.mdf’, SIZE = 300MB, FILEGROWTH = 50MB)
LOG ON
(NAME = ‘TestDb_log’, FILENAME = ‘C:\TestDb_log.ldf’, SIZE = 200MB, FILEGROWTH = 100MB)
GO
–Full recovery to avoid effect of system caused log truncation
ALTER DATABASE TestDb SET RECOVERY FULL
BACKUP DATABASE TestDb TO DISK = ‘nul’
USE TestDb

–Execution time log table
IF OBJECT_ID(‘TimeLogger’) IS NOT NULL DROP TABLE TimeLogger
GO
CREATE TABLE TimeLogger
(
SomeId int identity
,spid int
,TableStructure varchar(10) CHECK (TableStructure IN (‘heap’, ‘clustered’))
,InsertType varchar(20) CHECK (InsertType IN(‘one statement’, ‘loop’))
,ExecutionTimeMs int
)
GO

IF OBJECT_ID(‘RowsToInsert’) IS NOT NULL DROP TABLE RowsToInsert
CREATE TABLE RowsToInsert(#rows int)
GO

–Support procedures
IF OBJECT_ID(‘CreateTables’) IS NOT NULL DROP PROC CreateTables
GO
CREATE PROC CreateTables AS
IF OBJECT_ID(‘HeapLoop’) IS NOT NULL DROP TABLE HeapLoop
CREATE TABLE HeapLoop(c1 int identity, c2 int DEFAULT 2, c3 datetime DEFAULT GETDATE(), c4 char(200) DEFAULT ‘g’)
IF OBJECT_ID(‘ClusteredLoop’) IS NOT NULL DROP TABLE ClusteredLoop
CREATE TABLE ClusteredLoop(c1 int identity, c2 int DEFAULT 2, c3 datetime DEFAULT GETDATE(), c4 char(200) DEFAULT ‘g’)
CREATE CLUSTERED INDEX x ON ClusteredLoop(c1)
IF OBJECT_ID(‘HeapOneStatement’) IS NOT NULL DROP TABLE HeapOneStatement
CREATE TABLE HeapOneStatement(c1 int identity, c2 int DEFAULT 2, c3 datetime DEFAULT GETDATE(), c4 char(200) DEFAULT ‘g’)
IF OBJECT_ID(‘ClusteredOneStatement’) IS NOT NULL DROP TABLE ClusteredOneStatement
CREATE TABLE ClusteredOneStatement(c1 int identity, c2 int DEFAULT 2, c3 datetime DEFAULT GETDATE(), c4 char(200) DEFAULT ‘g’)
CREATE CLUSTERED INDEX x ON ClusteredOneStatement(c1)
GO

IF OBJECT_ID(‘TruncateTables’) IS NOT NULL DROP PROC TruncateTables
GO
CREATE PROC TruncateTables AS
TRUNCATE TABLE HeapLoop
TRUNCATE TABLE ClusteredLoop
TRUNCATE TABLE HeapOneStatement
TRUNCATE TABLE ClusteredOneStatement
GO

IF OBJECT_ID(‘DoBefore’) IS NOT NULL DROP PROC DoBefore
GO
CREATE PROC DoBefore AS
BACKUP LOG TestDb TO DISK = ‘nul’
CHECKPOINT
GO

IF OBJECT_ID(‘iHeapLoop’) IS NOT NULL DROP PROC iHeapLoop
GO
CREATE PROC iHeapLoop @rows int AS
DECLARE @i int = 1
WHILE @i <= @rows
BEGIN
INSERT INTO HeapLoop (c2) VALUES(2)
SET @i = @i + 1
END
GO

IF OBJECT_ID(‘iClusteredLoop’) IS NOT NULL DROP PROC iClusteredLoop
GO
CREATE PROC iClusteredLoop @rows int AS
DECLARE @i int = 1
WHILE @i <= @rows
BEGIN
INSERT INTO ClusteredLoop (c2) VALUES(2)
SET @i = @i + 1
END
GO

IF OBJECT_ID(‘iHeapOneStatement’) IS NOT NULL DROP PROC iHeapOneStatement
GO
CREATE PROC iHeapOneStatement @rows int AS
INSERT INTO HeapOneStatement (c2)
SELECT TOP(@rows) 2 FROM syscolumns a CROSS JOIN syscolumns b
GO

IF OBJECT_ID(‘iClusteredOneStatement’) IS NOT NULL DROP PROC iClusteredOneStatement
GO
CREATE PROC iClusteredOneStatement @rows int AS
INSERT INTO ClusteredOneStatement (c2)
SELECT TOP(@rows) 2 FROM syscolumns a CROSS JOIN syscolumns b
GO

–Proc to do the inserts
IF OBJECT_ID(‘DoTheInserts’) IS NOT NULL DROP PROC DoTheInserts
GO
CREATE PROC DoTheInserts
AS
DECLARE @dt datetime, @NumberOfRowsToInsert int
SET @NumberOfRowsToInsert = (SELECT #rows FROM RowsToInsert)
EXEC DoBefore –Batch allocation, heap:
SET @dt = GETDATE()
EXEC iHeapOneStatement @rows = @NumberOfRowsToInsert
INSERT INTO TimeLogger (spid, TableStructure, InsertType, ExecutionTimeMs)
VALUES(@@SPID, ‘heap’, ‘one statement’, DATEDIFF(ms, @dt, GETDATE()))

EXEC DoBefore –Batch allocation, clustered:
SET @dt = GETDATE()
EXEC iClusteredOneStatement @rows = @NumberOfRowsToInsert
INSERT INTO TimeLogger (spid, TableStructure, InsertType, ExecutionTimeMs)
VALUES(@@SPID, ‘clustered’, ‘one statement’, DATEDIFF(ms, @dt, GETDATE()))

EXEC DoBefore –Single allocations, heap:
SET @dt = GETDATE()
–BEGIN TRAN
EXEC iHeapLoop @rows = @NumberOfRowsToInsert
–COMMIT
INSERT INTO TimeLogger (spid, TableStructure, InsertType, ExecutionTimeMs)
VALUES(@@SPID, ‘heap’, ‘loop’, DATEDIFF(ms, @dt, GETDATE()))

EXEC DoBefore –Single allocations, clustered
SET @dt = GETDATE()
–BEGIN TRAN
EXEC iClusteredLoop @rows = @NumberOfRowsToInsert
–COMMIT
INSERT INTO TimeLogger (spid, TableStructure, InsertType, ExecutionTimeMs)
VALUES(@@SPID, ‘clustered’, ‘loop’, DATEDIFF(ms, @dt, GETDATE()))
GO

–Run the tests
EXEC CreateTables
TRUNCATE TABLE TimeLogger
TRUNCATE TABLE RowsToInsert INSERT INTO RowsToInsert VALUES(10000)

–<Below can be executed over several connections>
EXEC DoTheInserts
EXEC DoTheInserts
EXEC DoTheInserts
EXEC DoTheInserts
–</Below can be executed over several connections>

–How did we do?
SELECT COUNT(*) AS NumberOfExecutions, TableStructure, InsertType, AVG(ExecutionTimeMs) AS AvgMs
FROM TimeLogger WITH(NOLOCK)
GROUP BY TableStructure, InsertType
ORDER BY InsertType, TableStructure

–Verify that no fragmentation
SELECT
OBJECT_NAME(OBJECT_ID) AS objName
,index_type_desc
,avg_fragmentation_in_percent AS frag
,page_count AS #pages
,record_count
FROM sys.dm_db_index_physical_stats(DB_ID(), NULL, NULL, NULL, ‘DETAILED’)
WHERE OBJECT_NAME(OBJECT_ID) <> ‘TimeLogger’ AND index_level = 0

 

One Reply to “Are inserts quicker to heap or clustered tables?”

  1. “There was indded a noticeable difference when I executed several inserts in parallell and had each insert in its own transaction ”

    What difference??

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