Partioning Large Tables
Nov 14, 2007
I am making a warehouse managment system. The system will cotain much data, but only a small portion of the data will be accessed frequently. Most of the data will only be accessed seldomly, but the customer wants to keep all historic data (just in case they should need it sometime). I have figured I need to partion the tables somehow to keep what is fresh in one place, and historical data in another place. What is the best way to do this? I am thinking about making historical tables. For example I can have a table named PickList and another table named PickListHistorical. When a picklist is processed/complete I can move it over to the PicklistHistorical table, but when the users need to search for a specific picklist I have to look in both tables. I can ofcourse create a view for this to make it transparant. Sql server 2005 introduced some automatically partioning. Will it be better to use this than create my own historic tables? If so, can you please tell me how I do it?
Thank you!
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Feb 13, 2007
Hi All,
I setup a Transactional replication between SQL Server 2000 and SQL Server 2005 via
wide area network.
The intial snapshoot failed because run into problems on a table with column 379 columns.
How do ceate Vertical Partioning a table on Publication?
Thank you.
TJ_1
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Oct 25, 2006
This full version of this reporting table will have about 12 million row for each of three years. Prior years will be in separate partitions and frozen but the current year will be reloaded each night by source_key, probably in parallel.
I am trying to do this with a computed column but I can't slide the partition back into the main table due to an apparent problem with the Check constraint. I have tried everything I can think of and still can't get it to work.
I hope I am missing something simple. Anyone know why this does not work or how to fix it?
ALTER TABLE SWITCH statement failed. Check constraints or partition function of source table 'db_template.dbo.foo_year_source_partition_test_stage' allows values that are not allowed by check constraints or partition function on target table 'db_template.dbo.foo_year_source_partition_test'.
------------------------------------------------------------
CREATE PARTITION SCHEME zzYearSourcePScheme
AS
PARTITION zzYearSourceRangePFN
TO
(
[fg_template_0],
[fg_template_0],
[fg_template_0],
[fg_template_0],
[fg_template_0]
)
go
CREATE TABLE [dbo].[foo_year_source_partition_test](
[detail_date] [datetime] NULL,
[source_key] [int] NULL,
[year_source] AS ((CONVERT([char](2),right(datepart(year,[detail_date]),2),0)+'-')
+right('0000'+CONVERT([varchar](3),[source_key],0),(3))) PERSISTED,
[ys_id] int identity (1,1)
) ON zzYearSourcePScheme(year_source)
go
create unique clustered index ix_year_source_ys_id on [foo_year_source_partition_test] ([year_source], [ys_id]) ON zzYearSourcePScheme(year_source)
go
insert into [foo_year_source_partition_test] values('20060131',2)
insert into [foo_year_source_partition_test] values('20060131',3)
insert into [foo_year_source_partition_test] values('20060131',4)
SELECT *, $PARTITION.zzYearSourceRangePFN(year_source) AS Partition from [foo_year_source_partition_test] order by detail_date
go
CREATE TABLE [dbo].[foo_year_source_partition_test_stage](
[detail_date] [datetime] NULL,
[source_key] [int] NULL,
[year_source] AS ((CONVERT([char](2),right(datepart(year,[detail_date]),2),0)+'-')
+right('0000'+CONVERT([varchar](3),[source_key],0),(3))) PERSISTED,
[ys_id] int identity (1,1)
) --on same one ON YearSourcePScheme(year_source)
create unique clustered index ix_year_source_ys_id
on [foo_year_source_partition_test_stage] ([year_source], [ys_id]) --ON YearSourcePScheme(year_source)
ALTER TABLE db_template.dbo.foo_year_source_partition_test
SWITCH PARTITION 3 to db_template.dbo.[foo_year_source_partition_test_stage]
TRUNCATE TABLE db_template.dbo.[foo_year_source_partition_test_stage]
ALTER TABLE db_template.dbo.foo_year_source_partition_test_stage
WITH CHECK
ADD CONSTRAINT CK_foo_year_source_partition_test_stage_YearSource
CHECK
(
[year_source] = '06-003'
)
insert into foo_year_source_partition_test_stage values('20060202',3)
insert into foo_year_source_partition_test_stage values('20060303',3)
insert into foo_year_source_partition_test_stage values('20060404',3)
insert into foo_year_source_partition_test_stage values('20060505',3)
ALTER TABLE db_template.dbo.foo_year_source_partition_test_stage
SWITCH TO db_template.dbo.foo_year_source_partition_test PARTITION 3
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Mar 8, 2008
To the Forum,
Hello, i wanted to give the forum my current process flow to see if i am close or have some more work to do. The object is to import the data as fast as possible without loosing query responsiveness of the search on the web side. Any type of response will be greatly appreciated.
Current Process
I receive multiple product inventory lists form multiple vendors. These inventory lists are in many different formats like .xls format, .txt format, .csv format and .dbf format. My server converts the file format to raw .csv. The table is very large and will consist of millions of rows. Inventory comes in alphanumeric format.
Each of the inventory lists are NOT in the same format. What i mean by this is that there are different header names for the users inventory list than what matches our database table. For Example, a user may have an excel document with the header name "Amt" but our database table field name is "Amount". In order to make this import process automated I make a single mapping file for each user. This mapping file relates the users field header in their inventory file to that of the database table.
Currently I have a process converting all files to .csv format. Every 15 minutes a routine runs that converts the .csv to XML and then performs the import Bulk Insert routine. The process deletes the users entire inventory then imports to a "tempinventory" table, which then updates the inventory table. During this 15 minutes we may get 20 inventory lists to import which could be a half a million records. I have this inventory table indexed using the primary key which is the inventory number. This is the search criteria used (Inventory Number) on the web side. The import routine to SQL works quickly ONLY if Full-Text Index is turned OFF. I assume i need the Full Text Indexing on so the queries of the full inventory lists a fast response on the web side.
Assumed Issues
Right now if I were to turn off the Indexing for each import then we would have slow queries against the database on the web side.
To have one table with millions of rows that is constantly updated as well as queried at the same time is not efficient.
Assumed Corrections
Right now it seems that partitioning the table into 10 numeric partitions, one for each number would leverage the import routine as well as the web side search routine. I would then partition the alpha partition in 1 letter increments so we would have 26 partitions, one for each letter for a total of 36 partitions.
If I have the partitions seperated then it will be easier to update the seperate index as well as perform maintenance on the index, i assume this is correct.
Future Plans
I am upgrading the web side application to .NET 3.5 so we can take advantage of XLINQ and LINQ so our searches from the web side are faster and more efficient.
I am also looking into building a SilverLight application that will allow the user to install the application locally that will take their live database file and send updates to my server so they do not need to send in their inventory file at all and the inventory lists are live. This will alleviate the need to delete the users full listing in order to make a complete update. As stated above sometimes an update may just include updating the amount of only 2 of 40,000 rows.
I was also looking into db4o to see if it would be beneficial as well, http://www.db4o.com/, has anyone worked with this before in a similar manner?
Questions
I would like to make this process much more efficient from the import routine to the search routine. Is setting up the partitions as discussed a stable plan for both routines?
Is the BULK INSERT using XML to SQL the most efficient way of importing the data to SQL?
How would i handle the full text indexing to allow fast import routines without slowing down the web side searches?
After import of new data do i need to "update" the index as well?
What is a good set of "preventative maintenance" standards should i follow when dealing with this many table updates as well as the catalogs and table data?
I know there are benefits of using LINQ when querying the database from the web side but are there any other benefits that would fit into this current process?
As for the SilverLight application would it be beneficial for the user as well as me to have the application poll their database file to find changes and send only the updated values of the list to the server via XML, which is then updated by SQL?
I am unsure what is the best way to make this process as easy and automated as possible giving the user the fastest experience possible when searching from the web side.
Is this a smarter idea so i can track just the changes made by the user on their inventory list instead of importing the same redundant data they have?
Would implementing something like db4o be beneficial for this process, http://www.db4o.com/?
Please let me know if i am way off on this process or if there are some benefits that i am not using in this process. I have been doing a lot of research and this is what i have come up with so i wanted to ask the community what they thought about it as many heads are better than one. Please feel free to rip the process apart to, i take constructive criticism.
Thanks again.
RC
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Jul 12, 2001
We currently have a data warehouse running on SQL 7.0, SP2. One of our primary fact tables is now well over 155 million rows in it. The table is not very wide, as it only contains 17 columns, most of which are defined as integers. The entire database is only 20 GB.
The issue is that the loads from the staging table to this fact table have significantly deteriorated over the last month or so, dropping from over 400 transactions per second to around 85. We drop all the indexes on the fact table before we load the data into it.
Are there issues with a manageable table size in SQL 7.0 that we need to be concerned about? And should we consider partitioning the table into several smaller tables and join them with a "union all" view?
I really need to get this performance issue resolved, as our IT support vendor is pushing us to port the data warehouse to UDB because they tell us that SQL server is not scalable enough to handle this volume of data.
Thanks for any help you can provide.
George M. Parker
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Aug 10, 2000
Hi,
How can i partition the large tables so that the insert and updates which iam doing on the tables take less time.
I want to know how can i partition large tables and if i do that how is that the performance is going to be increased.
Thanks.
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Mar 13, 2001
How can I find largest 5 or 10 tables in a database?
Thanks in advance
Chan
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Mar 7, 2007
Hi there,i am having some problem related to SQL server........ Actually i am having a table called ZipCodes that have around 80,000 rows... and the size of the table is around 100 MB...... and my table is now on web Server,. now my problem is that when i fire some query that needs to go through whole of the table then it estimated time to execute the query comes to be 13 seconds and the corsor threshold is set to 7 seconds (and i can't change that)....... so the SQL server cancels the query to be fired........Now i need some Methodology/Technique through which i can search Large Tables with minimum calculations in minimum Time............(Any Ideas)....
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Mar 19, 2001
Is it possible to compress the large tables in the database,
like COMPRESS, ARCHIVE options we use to reduce the size of files
stored on any operating system.
I know there is a difference between the file stored on disk and the table created in the database, but currently I am facing space problems wherein, I have to manage my database within the space available, so please advice me if the option is available in SQL Server 6.5 or 7.
I will be happy if I get the solution immediatly as currently I am facing this problem and waiting for your reply.
Thank you
Amol
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Feb 12, 2008
I am fairly new to SQL, so please forgive me if my question is a bit elementary. I need to pull two individual tables out of a massive DB into a new DB for testing.
Thanks for the help.
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Feb 15, 2008
I'm in the midst of a long file conversion job. Today I found that one of the tables (converted from csv) to be 6.7 million records. My sql script which I use to reconfigure the weird original date format, into something the rest of the planet uses, times out due to the size.
Does anyone please know of a file utility to automagically split sql server 2005 tables for later re-combining once my scripts have successfully completed their task on the smaller tables?
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Oct 19, 2007
I've successfully created SSIS packages where I compare two tables in different databases on different servers. However, this is good enough to compare hundreds of thousands of records quickly. The process becomes a huge performance problem when trying to compare table differences when I'm looking at tables that each contain tens of millions of records.
One database is on a SQL 2005 box and the other DB is SQL 7.0 so the lookup component fails for this type of SQL Server. I've been implementing merge joins and conditional components to do my standard table comparisons.
Is there another way to implement this process or maybe partition it somehow to take pieces of the table at a time and compare them? I'm open to ideas.
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Jan 9, 2008
I'm using DataAdapters with my SQL database with the intention of all the SELECT, UPDATE, INSERT, DELETE commands to be automatically generated.One table is huge so I'm wondering is it more efficient to "SELECT Top(1) * FROM hugetable" instead of "SELECT * FROM hugetable" in order to facilitate the generation of commands.I hope this isn't too confusing.Thanks,Geoff
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May 10, 2008
I have 4 tables with the respective amount of records
1) 6755
2) 2021
3) 2021
4) 355
They all have the same columns. However, they need to be seperate, or at least when I query them. I'll be accessing this database via the web. i was first afraid that a large database would cause major slow down when accessing the db. So I broke it up into 4 tables. If I combined all 4 tables into one large table and just had a column that differentiated the 4, how significant would be the change in speed when accessing the table? It's not a big deal to keep them seperate, its just that when I have to add or remove a column from one table I have to remove it from all the tables. Furthermore, I'm using a module from DEVEXPRESS, don't know if anyone has heard of it, but when you use a gridview, it loads up the entire table even though your paging (which I think is retarded), so for that reason I was afraid it would slow up my access to the db. Any thoughts?
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Nov 29, 2000
We are inserting into a table, which includes an identity primary key column. When the table gets really large (i.e. 1.5 million records), the performance of the inserts reduce.
I noticed that when we insert into the table an exclusive lock on the table is obtained. Do inserts into tables with identities always lock the table?
Given the table size is unavoidable, does anyone have a suggestion to improve the performance?
Thanks,
Matt
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Aug 4, 2005
I have a few hundred users, maybe a dozen or two active at any given time, accessing the same database via ASP. The database has many tables, one being a very large orders table with a few million records, in which I have created a view against. A view only because I need to allow the user to filter quite extensively against the results. The users typically only need to view records for the last 30 days and results for each user might be five thousand records or less.
My question is this. Would I be better off writing each user's resultset to a temp table for that user's session and allow the filtering and sorting by the user go against that temp table and increase my hardware requirements to accomodate that. Possibly to the point of creating a database cluster. OR would I be better off leaving it as is where each users uses the same view.
FYI...each user may need visibility to only a hand full of fields, but over all the view must maintain many fields.
Any thoughts on this would be greatly appreciated. Thanks in advance.
Dave
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Jan 25, 2008
Hi gurus, I'm creating a web application where I will have a large number of tables (between 10k and 20k), this is done for the sake of scalability as tables will be moved to different database servers as the application grows and also for performance (smaller indexes). I'm worried though how having a large number of tables could affect the performance of SQL Server as the application will start on one single database server. I tried to find some resources on that on the internet but couldn't find any.
I would really appreciate if you can give me some advice and if you have any good links that would be great...
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Nov 1, 2007
I have the following table structure:
tableA (~85,000 rows) primary key = [colA,colB]
tableB (~850,000 rows) primary key = [colA,colC]
tableC (~120,000,000 rows) primary key = [colA,colB,colC]
IMPORTANT: colC is DATETIME
For a SET of rows in tableA (about 50,000) I need to pull the MOST RECENT (given a date) corresponding values from tables B and C. The only way I can think of doing this is the following:
SELECT tableA.colA
,(SELECT TOP 1 colX FROM tableB WHERE colA = tableA.colA AND colC <= @INPUTDATE ORDER BY colC desc)
,(SELECT TOP 1 colY FROM tableB WHERE colA = tableA.colA AND colC <= @INPUTDATE ORDER BY colC desc)
,... --some more columns from tableB
,(SELECT TOP 1 colX FROM tableC WHERE colA = tableA.colA AND colB = tableA.colB AND colC <= @INPUTDATE ORDER BY colC desc)
,(SELECT TOP 1 colY FROM tableC WHERE colA = tableA.colA AND colB = tableA.colB AND colC <= @INPUTDATE ORDER BY colC desc)
,... --some more columns from tableC
FROM tableA
WHERE tableA.colX = 'some criteria'
Is there any other way anyone can suggest? Unfortunately, because tableC is so large, the disk IO (I think) causes this query to take over an hour. (If I had monster RAM and super fast disk this wouldn't be as big an issue, but that's not an option right now )
Thanks in advance!
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Jan 25, 2008
Hi gurus, I'm creating a web application where I will have a large number of tables (between 10k and 20k), this is done for the sake of scalability as tables will be moved to different database servers as the application grows and also for performance (smaller indexes). I'm worried though how having a large number of tables could affect the performance of SQL Server as the application will start on one single database server. I tried to find some resources on that on the internet but couldn't find any.
I would really appreciate if you can give me some advice and if you have any good links that would be great...
Waleed Eissa
http://www.waleedeissa.com
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Dec 5, 2007
Hi,
I have a table with over 61 million records having a clustered index on an identity column(Primary key). Simple count queries are taking minutes to execute on this table (ex: select count(1) from table1). I have checked the statistics on the primary key which displayed me the histogram having the 39th million record as the Range-hi-key. I updated the statistics on this column and tried requerying, but still it took atleast 5 minutes to give me the count of records in the table. Also, there were no users using the table when I queried. Inserts into this table were working fine. I have other tables in my database with 41 million records having no such issues. Can anyone point me to the problem areas in such scenarios?
Thanks,
Harish
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Jan 2, 2003
What is the best procedure/sequence to reduce some tables containing large number of rows of
a SQL 2000 server?
The idea is first to check which tables grow extremely fast (all statistics, user or log tables), reduce the table
according to the number of months the user wishes to keep in the table.
As a second step backup remaining rows of table as txt files on harddisk (using DTS), UPDATE STATISTICS and re-indexing reduced table.
Run DTS Package every month once (delete oldest month and backup newest month) and do the same as above to keep size of tables adequate.
What is a fast way to reduce number of rows of a large table - the following example produces an error (timeout expired) of my
ADO connection when executing:
SET @str = 'DELETE FROM ' + @ProcessTable + ' WHERE ' + @SelectedColumn + ' < DATEADD (m,' +' -' +
@KeepMonthsInDatabase + ',
+ GETDATE())'
EXEC (@str)
Adding ConnectionTimout = 0 did not help unfortunately.
What is the best way to re-index the table just maintained?
Thanks
mipo
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Mar 8, 2014
We are having very big tables in TBS and wanted to setup a strategy for index maintenance.
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Jul 7, 2015
I have come across a database system which isn't designed to work optimally. It is fairly large (~400GB) and performance of loading and querying is degrading (improper data types, fragmented indexes, non unique clustering key and other problems). So, I have quite a task in front of me, but I am up for the challenge. I figure this is not a unique situation, many of us would have come across this before. I have done this before too, but only for smaller databases, some of the operations here I expect to take a couple of hours or more to complete (depending on load/infrastructure speed etc, I know).
My plan is thus:
+ Take a full backup of the database
+ Set the recovery model of the DB to simple
+ Drop non clustered indexes
+ Drop clustered indexes
+ Remove PKs (wrong data types, too large!)
+ Narrow data types (add new column, update column in batches to old value, rename new column to old column)
+ Add PKs, which will create clustered indexes automatically based on PK ID
+ Create non clustered indexes
+ Run a SHRINKDB (normal operations I would never do this, but this is a special case, ensure log file is truncated to a logical size especially after all those table modifications...)
+ Set the recovery model of the DB to Full
+ Ensure everything works OK or better
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Jul 14, 2015
How many no of records of the tables are called large tables.
We are getting more deadlocks. We are using default isolation. Read & insert statements are blocking each other and causes dead locks.
I am thinking that might be purging will reduce deadlocks.
The table has 15million records. Is this table consider as large table or not in OLTP systems?
In general how many records we need to consider as large table.
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Mar 28, 2006
We have a simple UPDATE query, joining two tables, that takes much longer than 10 hours to run, but if we break the table in six (10 million rows in each table), it takes only fifteen minutes to run each part.
Why? And how can we tell in advance whether a query will cross the threshold into l.o.n.g.r.u.n.n.i.n.g query? Or, how can we prevent it?
The system is Windows XP Pro with 4GB RAM (/3GB switch), and SQL Server Standard 2005. Log files, swap files, dbf files are on separate drives. The system is dedicated to SQL Server. No other queries are running at the same time. The database is in Simple logging mode. Each table is a few GB with 60 million rows.
An example problem query is: (updating fewer than 10 bytes)
UPDATE bigtable
SET bigtable.custage = scores.custage, bigtable.custscore = scores.custscore
FROM bigtable
JOIN t2 ON bigtable.custid = scores.custid
In this case, each table has 60 million rows. 'custid' is a sequential, unique integer. SCORES table is clustered on 'custid' and is 1.5GB in size. BIGTABLE has an index on 'custid', and is 6GB in size. There is a one-to-one match between the tables on 'custid', but not enforced. The SCORES table was created by exporting a few fields (but all 60 million records) from BIGTABLE, updating the values in a separate program, then importing back in SQL Server into the SCORES table.
The first time this query was run, we stopped it after it ran 16 hours. When we broke up the bigtable into 10 million record chunks (big1, big2, big3..., big6) each update only took 15 minutes, for 90 minutes total.
* How can in we tell in advance that the full chunk would take more than a few hours?
* Why is it taking SO MUCH LONGER than in smaller chunks?
* When a query is taking that long to run, is there any way to tell where in the plan it is?
* What should we do differently?
Thanks for any help; this is a real head scratcher for us.
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Sep 20, 2007
Hello,
I hope I am posting this in the right forum.
I am using tableDiff.exe to create a diff SQL script for a very large table (~4 million rows).
After a few minutes, I recieve a "System.OutOfMemoryException".
I have 4GB of ram on the machine executing the table diff.
The server is 32-bit, so adding ram is not an option.
I am executing the following command line:
Code Snippet
TableDiff.exe" -sourceserver "SERVER" -sourcedatabase "SourceDB" -sourcetable "Table1" -destinationserver "SERVER" -destinationdatabase "DestDB" -destinationtable "Table1" -f "C:TableDiffsTable1"
I have seen reports of other users executing tableDiff against 2million row tables.
Is there anyway to buffer tableDiff, so that I do not run out of memory on the server?
Could anything else be causing this error?
Thanks,
Dave
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May 31, 2007
Hi,
I currently have a large table (35 million rows, over 80GB). I have one varchar(max) column on the table that is used in the fulltext index.
To query the complete index is fast, for example:
SELECT 'ipod', COUNT(*)
FROM CONTAINSTABLE(MyDB.dbo.Contents, [Body], 'ipod') CT
This took 70 seconds (which I can live with). However, I seldom run queries like this, most are more like:
SELECT 'ipod', COUNT(*)
FROM CONTAINSTABLE(MyDB.dbo.Contents, [Body], 'ipod') CT
JOIN Pages ITP ON ITP.PageID = CT.[Key]
JOIN Feeds ITF ON ITP.IPID = ITF.IPID
JOIN Buyers ITB ON ITB.IBID = ITF.IBID
WHERE ITB.ID IN (1342,246)
These queries are much slower (this example took 17 minutes). I understand that FT searches the index and returns all rows that match the query to SQL. SQL then performs the joins and counts only the correct results. (Correct me if I'm wrong here).
One solution I've seen to this to put data or "tags" into the FT column - so my Body column would become something like:
'{ID:1342}' + [Body]
That sounds like a very good idea. I could then change the 2nd query above to be:
SELECT 'ipod', COUNT(*)
FROM CONTAINSTABLE(MyDB.dbo.Contents, [Body], '("ID:1342" OR "ID:246") AND "ipod"') CT
That all works well until I want to select 1000 different ID's because the FT query will become very long and complex. Also I'm only including one column (ID) in this example - but I have about 7 or 8 columns that I would need to include in these "tags". Quering multiple columns become very complex quickly and no doubt I will reach a query limit at somepoint.
If anyone has any other suggestions to the above I'd love to hear them. Another thought I'm having is to partition the table. I can find very little online about how FT behaves on partitioned tables - I fear it behaves exactly the same, what I'd like to think is that I could partition the table on an ID say 100 per partition or something, and then fulltext would only search the relevant partitions. If it behaves like this it may work. If no-one knows then I'll give it ago, but this will take me a while due to the table size - so I'm hoping one of you clever lot know!
Many thanks for any advice.
Simon
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Jan 4, 2006
I have a general SQL design-type question.
I want to log errors to a table. If the error is with a URL, I want to store the URL. These URLs can be very large, hundreds of characters, but I only need to store it if it causes the error, which should be very infrequent. Which is the better design:
Create a large varchar field in the log table to hold the URL, or null if the error wasn't with the URL.
Create a foreign key field in the log table to a second URL table, which has a unique ID and a large varchar, and only create a record in this table if the error is with the URL.
One concern I have with design 2 is that there could be many other fields that are infrequent. Do I create a separate table for every one?
Richard
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Mar 1, 2007
hi all,
i have a large table in sql server 2005 (it has about 6 columns and 10 million records).
i need to work in a linear way on all the records (i know it sounds dumb but i need to work on all records).
now, obviously when trying to work on this table sql server get stuck for timeout or something like that...
i've noticed that a simple function like "select top 100 * from ExportTable" still works.
is there any way to have sql send me the data when it access it so that i'll still be able to proccess it on the same time, i basically work using dataset so that fixing the timeout wont be helpfull since windows probably wont allow me to load this amount of data into memory.
can any1 help?
Z
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May 23, 2002
Table structure: col1 IDENTITY (seed=1 increment=1) + few other columns (col2...col7) + one text column (col 8)
I have around 50,000,000 rows per day inserted in the table T1. At the end of the day 40,000,000 rows are deleted. I have to keep the records for 12 months and then archive it. Database is 24/7 web serving and there is no down time allowed. IDENTITY column will go out of range (overflow) after less than two years, unless the identity seed is reset to the start value (seed=1, increment=1).
At the end of 12th month data is archived in another table and only last month is kept in the table T1. So table T1 enters new year with data from last month of the previous year. There are few other tables that refer to this table by using there own field with values from T1.IDENTITY column (referential integrity is not enforced). Identity column in T1 is needed as a unique id for some search actions. Performance is an issue therefore bigint data type is used for this identity column rather than decimal.
Another problem I have is how to do table update on one column (1 mil rows to be updated out of 2 mil of rows) with the minimum impact on the users who are querying this table heavily. Not need to mention that it is web app 24/7 no down time.
Thank you in advance.
Goran
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Jan 24, 2015
We are in the middle of re-designing few tables (namely transaction tables) that would store very large data and would be hosted on cloud (Azure). The old design of this product breaks transaction tables into monthly tables. i.e. say ORDERS Table would be physically broke into twelve monthly tables over a year like ORDERS0115 (mmyy), ORDERS0215 and so on.
We are in the opinion that keeping the entire transactions in one Table is better. Would like to know what's the best practices for transaction tables like the one mentioned above? Is it better to use one table with partitions. I read somewhere that partitions can slow down SELECT queries if not designed and thought properly.Since this would be hosted on cloud (Azure), do you think some additional things are to be taken care? How a site like Amazon keeps their transactions tables?
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Dec 5, 2007
I have a query that joins two large partitioned tables and depending on the values in the where clause, I can get dramatically different performance results.
The first query completed in around 7s and has 47,000 logical reads.
select mo.monitor_id,
mo.site_id,
mo.testtime,
sum(mo.NumBytes),
sum(mo.DNSTime),
sum(mo.ConnectTime),
sum(mo.FirstByteTime),
sum(mo.ContentTime),
sum(mo.RelocTime)
from monitor_raw mr(nolock), monitor_object mo(nolock)
where mr.monitor_id in (5339, 5341, 5342, 943842, 943866)
and mr.testtime between 'Oct 31 2007 3:00:00:000PM' and 'Nov 30 2007 3:00:00:000PM'
and mo.returncode = 200
and mr.site_id in (101,102,105,109,110,112,115,117,119,122,126,151,132,139,129,135,121,138,143,142,159,148,128,171,176,177,178,111,113,116,118,120,127,133,131,130,174,179,185,205,200,202,203,204,210,211,208,209,212,213,216,199,214,224,225,229,230,232,235,241,245,247,250,254,261,267,264,265,266,268,269)
and mr.escalationlevel = 0
and mr.monitor_id = mo.monitor_id
and mr.testtime = mo.testtime
and mr.site_id = mo.site_id group by mo.monitor_id, mo.site_id, mo.testtime
The second query takes 188s to complete and has 1.8m logical reads. The only difference between the two is the value of the monitor_ids in the where clause.
select mo.monitor_id,
mo.site_id,
mo.testtime,
sum(mo.NumBytes),
sum(mo.DNSTime),
sum(mo.ConnectTime),
sum(mo.FirstByteTime),
sum(mo.ContentTime),
sum(mo.RelocTime)
from monitor_raw mr(nolock), monitor_object mo(nolock)
where mr.monitor_id in (152682, 5339, 5341, 5342, 268080)
and mr.testtime between 'Oct 31 2007 3:00:00:000PM' and 'Nov 30 2007 3:00:00:000PM'
and mo.returncode = 200
and mr.site_id in (101,102,105,109,110,112,115,117,119,122,126,151,132,139,129,135,121,138,143,142,159,148,128,171,176,177,178,111,113,116,118,120,127,133,131,130,174,179,185,205,200,202,203,204,210,211,208,209,212,213,216,199,214,224,225,229,230,232,235,241,245,247,250,254,261,267,264,265,266,268,269)
and mr.escalationlevel = 0
and mr.monitor_id = mo.monitor_id
and mr.testtime = mo.testtime
and mr.site_id = mo.site_id group by mo.monitor_id, mo.site_id, mo.testtime
The two tables have clustered indexes on monitor_id, testtime and site_id. Comparing the execution plan, I can see why there is such a difference in performance. The second query performs a clustered index seek on the monitor_object table starting at the lowest monitor_id, testtime & site_id through the highest monitor_id, testtime & site_id. The first query performs a clustered index seek where the monitor_id, testtime and site_id equals the same values from the monitor_raw table.
My question is, how can I force the second query to use the same execution plan as the first so that I can get better performance?
One possible workaround that I could use is to execute five individual queries, one for each monitor_id and then union the results together but this would require significant code changes to my stored procs.
Thanks,
Tim
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Nov 14, 2011
I would like to know the impacts (if any) of adding nonclustered index with included columns on large tables (these tables are populated by bulk insert from text files).
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