I have an issue in production env, one of the work flow is running more tgan one day and inserting records in to sql server db. It s just direct load mapping, there is no sq over ride as well. Monitor shows sq count as 7 million and inseting same no of records inyo target. But source db shows around 3 million records only. How can this be possible?
Have you checked if the source qualifier is joining more than one table? A screenshot of the affected mapping pipeline and obfuscated logfile would help.
Another thought... given your job ran for a day, were there any jobs ran in that time to purge old records from the source table?
Cases when I saw this kind of things happening:
There's a SQL Query override doing something different than I thought (eg. joining some tables)
I'm looking at a different source - verify the connections and make sure to check the same object on the same database at the same server the PowerCenter is connecting to.
It's a reusable session being executed multiple times by different workflows. In such case in workflow monitor it may happen that Source/Target Statistics will refer to another execution.
Not sure if this question has been already asked. I face this problem where the 1st hit from the website to an Oracle SP takes a lot of time. Subsequent accesses work just fine.
The SP i'm taking about here is a dynamic SP used for Search functionality(With different search criteria selection option available)
1st access time ~200 seconds
subsequent access time ~20 to 30 seconds.
Stored Procedure logic on a high level.
Conditional JOINS are appended based on some logics.
Dynamic SQL and cursor used to retrieve data.
Any help to start tackling these kind of issues is very helpful..
Thanks,
Adarsh
The reason why it takes only a few secs to execute the query after the first run is that Oracle caches the results. If you change the SQL then Oracle considers it a different query and won't serve the results from the cache but executes the new query (even formatting the code again or adding a space in between will be a difference).
It is a hard question how to speed up first execution. You'll need to post your query and explain plan and probably you'll have to answer further questions if you want to get help on that.
We had a performance issue in our production environment.
We identified that Oracle was executing queries using a Index which is not correct.
The queries have in their WHERE CLAUSE all the columns of the Primary Key (and nothing else).
After rebuilding of Index and Gather Statistics, Oracle started using the PK_INDEX. And the plan of execution indicated Index Unique Scan.
It worked fine for a while and then Oracle started using the Wrong Index again. The index that it uses now comprise of 2 Columns of which only 1 appears in the WHERE CLAUSE of the query. Now the plan of execution indicates INDEX RANGE SCAN and the system is very slow.
Please let me know how we could get to the root of this issue.
Try gathering stats again. If you get the expected execution plan then it means that the changes made to the table since the last stats gathering made oracle think the least favorite execution plan is better.
so, You'r question here is really "How can I maintain plan stability ?"
You have several options
Use hints in your query to indicate the exact access path.
Use
outlines
I personally don't like these two approaches because if your data will change in the future in such a manner that the execution plan should change, you'll get lousy performance.
So the third option (and my personal favorite) is
enable periodic statistics gathering. Oracle knows to spot the
changes and incrementally update relevant stats.
I have a stored procedure that returns about 50000 records in 10sec using at most 2 cores in SSMS. The SSRS report using the stored procedure was taking 20min and would max out the processor on an 8 core server for the entire time. The report was relatively simple (i.e. no graphs, calculations). The report did not appear to be the issue as I wrote the 50K rows to a temp table and the report could display the data in a few seconds. I tried many different ideas for testing altering the stored procedure each time, but keeping the original code in a separate window to revert back to. After one Alter of the stored procedure, going back to the original code, the report and server utilization started running fast, comparable to the performance of the stored procedure alone. Everything is fine for now, but I am would like to get to the bottom of what caused this in case it happens again. Any ideas?
I'd start with a SQL Profiler trace of both the stored procedure when you execute it normally, and then the same SP when it's called by SSRS. Make sure you include the execution plans involved, so you can see if it's making some bad decisions (though that seems unlikely - the SQL Server should execute an optimal - or at least consistent - plan regardless of the query's source).
We used to have cases where Business Objects would execute stored procs dozens of times for no aparent reason and it lead to occasionally horrible performance, though I've never seen that same behavior with SSRS. It may be somewhere to start, though. You'll also see the execution begin/end times - that will make it clear if it's the database layer that's hanging up, or if the SQL Server hands back the data in 10 seconds and then it's the SSRS service that's choking somewhere.
The primary solution to speeding SSRS reports is to cache the reports. If one does this (either my preloading the cache at 7:30 am for instance) or caches the reports on-hit, one will find massive gains in load speed.
You may also find that monthly restarts of SSRS application domain to resolve your issue.
Please note that I do this daily and professionally and am not simply waxing poetic on SSRS
Caching in SSRS
http://msdn.microsoft.com/en-us/library/ms155927.aspx
Pre-loading the Cache
http://msdn.microsoft.com/en-us/library/ms155876.aspx
If you do not like initial reports taking long and your data is static i.e. a daily general ledger or the like, meaning the data is relatively static over the day, you may increase the cache life-span.
Finally, you may also opt for business managers to instead receive these reports via email subscriptions, which will send them a point in time Excel report which they may find easier and more systematic.
You can also use parameters in SSRS to allow for easy parsing by the user and faster queries. In the query builder type IN(#SSN) under the Filter column that you wish to parameterize, you will then find it created in the parameter folder just above data sources in the upper left of your BIDS GUI.
[If you do not see the data source section in SSRS, hit CTRL+ALT+D.
See a nearly identical question here: Performance Issuses with SSRS
I'm about to have to rewrite some rather old code using SQL Server's BULK INSERT command because the schema has changed, and it occurred to me that maybe I should think about switching to a stored procedure with a TVP instead, but I'm wondering what effect it might have on performance.
Some background information that might help explain why I'm asking this question:
The data actually comes in via a web service. The web service writes a text file to a shared folder on the database server which in turn performs a BULK INSERT. This process was originally implemented on SQL Server 2000, and at the time there was really no alternative other than chucking a few hundred INSERT statements at the server, which actually was the original process and was a performance disaster.
The data is bulk inserted into a permanent staging table and then merged into a much larger table (after which it is deleted from the staging table).
The amount of data to insert is "large", but not "huge" - usually a few hundred rows, maybe 5-10k rows tops in rare instances. Therefore my gut feeling is that BULK INSERT being a non-logged operation won't make that big a difference (but of course I'm not sure, hence the question).
The insertion is actually part of a much larger pipelined batch process and needs to happen many times in succession; therefore performance is critical.
The reasons I would like to replace the BULK INSERT with a TVP are:
Writing the text file over NetBIOS is probably already costing some time, and it's pretty gruesome from an architectural perspective.
I believe that the staging table can (and should) be eliminated. The main reason it's there is that the inserted data needs to be used for a couple of other updates at the same time of insertion, and it's far costlier to attempt the update from the massive production table than it is to use an almost-empty staging table. With a TVP, the parameter basically is the staging table, I can do anything I want with it before/after the main insert.
I could pretty much do away with dupe-checking, cleanup code, and all of the overhead associated with bulk inserts.
No need to worry about lock contention on the staging table or tempdb if the server gets a few of these transactions at once (we try to avoid it, but it happens).
I'm obviously going to profile this before putting anything into production, but I thought it might be a good idea to ask around first before I spend all that time, see if anybody has any stern warnings to issue about using TVPs for this purpose.
So - for anyone who's cozy enough with SQL Server 2008 to have tried or at least investigated this, what's the verdict? For inserts of, let's say, a few hundred to a few thousand rows, happening on a fairly frequent basis, do TVPs cut the mustard? Is there a significant difference in performance compared to bulk inserts?
Update: Now with 92% fewer question marks!
(AKA: Test Results)
The end result is now in production after what feels like a 36-stage deployment process. Both solutions were extensively tested:
Ripping out the shared-folder code and using the SqlBulkCopy class directly;
Switching to a Stored Procedure with TVPs.
Just so readers can get an idea of what exactly was tested, to allay any doubts as to the reliability of this data, here is a more detailed explanation of what this import process actually does:
Start with a temporal data sequence that is ordinarily about 20-50 data points (although it can sometimes be up a few hundred);
Do a whole bunch of crazy processing on it that's mostly independent of the database. This process is parallelized, so about 8-10 of the sequences in (1) are being processed at the same time. Each parallel process generates 3 additional sequences.
Take all 3 sequences and the original sequence and combine them into a batch.
Combine the batches from all 8-10 now-finished processing tasks into one big super-batch.
Import it using either the BULK INSERT strategy (see next step), or TVP strategy (skip to step 8).
Use the SqlBulkCopy class to dump the entire super-batch into 4 permanent staging tables.
Run a Stored Procedure that (a) performs a bunch of aggregation steps on 2 of the tables, including several JOIN conditions, and then (b) performs a MERGE on 6 production tables using both the aggregated and non-aggregated data. (Finished)
OR
Generate 4 DataTable objects containing the data to be merged; 3 of them contain CLR types which unfortunately aren't properly supported by ADO.NET TVPs, so they have to be shoved in as string representations, which hurts performance a bit.
Feed the TVPs to a Stored Procedure, which does essentially the same processing as (7), but directly with the received tables. (Finished)
The results were reasonably close, but the TVP approach ultimately performed better on average, even when the data exceeded 1000 rows by a small amount.
Note that this import process is run many thousands of times in succession, so it was very easy to get an average time simply by counting how many hours (yes, hours) it took to finish all of the merges.
Originally, an average merge took almost exactly 8 seconds to complete (under normal load). Removing the NetBIOS kludge and switching to SqlBulkCopy reduced the time to almost exactly 7 seconds. Switching to TVPs further reduced the time to 5.2 seconds per batch. That's a 35% improvement in throughput for a process whose running time is measured in hours - so not bad at all. It's also a ~25% improvement over SqlBulkCopy.
I am actually fairly confident that the true improvement was significantly more than this. During testing it became apparent that the final merge was no longer the critical path; instead, the Web Service that was doing all of the data processing was starting to buckle under the number of requests coming in. Neither the CPU nor the database I/O were really maxed out, and there was no significant locking activity. In some cases we were seeing a gap of a few idle seconds between successive merges. There was a slight gap, but much smaller (half a second or so) when using SqlBulkCopy. But I suppose that will become a tale for another day.
Conclusion: Table-Valued Parameters really do perform better than BULK INSERT operations for complex import+transform processes operating on mid-sized data sets.
I'd like to add one other point, just to assuage any apprehension on part of the folks who are pro-staging-tables. In a way, this entire service is one giant staging process. Every step of the process is heavily audited, so we don't need a staging table to determine why some particular merge failed (although in practice it almost never happens). All we have to do is set a debug flag in the service and it will break to the debugger or dump its data to a file instead of the database.
In other words, we already have more than enough insight into the process and don't need the safety of a staging table; the only reason we had the staging table in the first place was to avoid thrashing on all of the INSERT and UPDATE statements that we would have had to use otherwise. In the original process, the staging data only lived in the staging table for fractions of a second anyway, so it added no value in maintenance/maintainability terms.
Also note that we have not replaced every single BULK INSERT operation with TVPs. Several operations that deal with larger amounts of data and/or don't need to do anything special with the data other than throw it at the DB still use SqlBulkCopy. I am not suggesting that TVPs are a performance panacea, only that they succeeded over SqlBulkCopy in this specific instance involving several transforms between the initial staging and the final merge.
So there you have it. Point goes to TToni for finding the most relevant link, but I appreciate the other responses as well. Thanks again!
I don't really have experience with TVP yet, however there is an nice performance comparison chart vs. BULK INSERT in MSDN here.
They say that BULK INSERT has higher startup cost, but is faster thereafter. In a remote client scenario they draw the line at around 1000 rows (for "simple" server logic). Judging from their description I would say you should be fine with using TVP's. The performance hit - if any - is probably negligible and the architectural benefits seem very good.
Edit: On a side note you can avoid the server-local file and still use bulk copy by using the SqlBulkCopy object. Just populate a DataTable, and feed it into the "WriteToServer"-Method of an SqlBulkCopy instance. Easy to use, and very fast.
The chart mentioned with regards to the link provided in #TToni's answer needs to be taken in context. I am not sure how much actual research went into those recommendations (also note that the chart seems to only be available in the 2008 and 2008 R2 versions of that documentation).
On the other hand there is this whitepaper from the SQL Server Customer Advisory Team: Maximizing Throughput with TVP
I have been using TVPs since 2009 and have found, at least in my experience, that for anything other than simple insert into a destination table with no additional logic needs (which is rarely ever the case), then TVPs are typically the better option.
I tend to avoid staging tables as data validation should be done at the app layer. By using TVPs, that is easily accommodated and the TVP Table Variable in the stored procedure is, by its very nature, a localized staging table (hence no conflict with other processes running at the same time like you get when using a real table for staging).
Regarding the testing done in the Question, I think it could be shown to be even faster than what was originally found:
You should not be using a DataTable, unless your application has use for it outside of sending the values to the TVP. Using the IEnumerable<SqlDataRecord> interface is faster and uses less memory as you are not duplicating the collection in memory only to send it to the DB. I have this documented in the following places:
How can I insert 10 million records in the shortest time possible? (lots of extra info and links here as well)
Pass Dictionary<string,int> to Stored Procedure T-SQL
Streaming Data Into SQL Server 2008 From an Application (on SQLServerCentral.com ; free registration required)
TVPs are Table Variables and as such do not maintain statistics. Meaning, they report only having 1 row to the Query Optimizer. So, in your proc, either:
Use statement-level recompile on any queries using the TVP for anything other than a simple SELECT: OPTION (RECOMPILE)
Create a local temporary table (i.e. single #) and copy the contents of the TVP into the temp table
I think I'd still stick with a bulk insert approach. You may find that tempdb still gets hit using a TVP with a reasonable number of rows. This is my gut feeling, I can't say I've tested the performance of using TVP (I am interested in hearing others input too though)
You don't mention if you use .NET, but the approach that I've taken to optimise previous solutions was to do a bulk load of data using the SqlBulkCopy class - you don't need to write the data to a file first before loading, just give the SqlBulkCopy class (e.g.) a DataTable - that's the fastest way to insert data into the DB. 5-10K rows isn't much, I've used this for up to 750K rows. I suspect that in general, with a few hundred rows it wouldn't make a vast difference using a TVP. But scaling up would be limited IMHO.
Perhaps the new MERGE functionality in SQL 2008 would benefit you?
Also, if your existing staging table is a single table that is used for each instance of this process and you're worried about contention etc, have you considered creating a new "temporary" but physical staging table each time, then dropping it when it's finished with?
Note you can optimize the loading into this staging table, by populating it without any indexes. Then once populated, add any required indexes on at that point (FILLFACTOR=100 for optimal read performance, as at this point it will not be updated).
Staging tables are good! Really I wouldn't want to do it any other way. Why? Because data imports can change unexpectedly (And often in ways you can't foresee, like the time the columns were still called first name and last name but had the first name data in the last name column, for instance, to pick an example not at random.) Easy to research the problem with a staging table so you can see exactly what data was in the columns the import handled. Harder to find I think when you use an in memory table. I know a lot of people who do imports for a living as I do and all of them recommend using staging tables. I suspect there is a reason for this.
Further fixing a small schema change to a working process is easier and less time consuming than redesigning the process. If it is working and no one is willing to pay for hours to change it, then only fix what needs to be fixed due to the schema change. By changing the whole process, you introduce far more potential new bugs than by making a small change to an existing, tested working process.
And just how are you going to do away with all the data cleanup tasks? You may be doing them differently, but they still need to be done. Again, changing the process the way you describe is very risky.
Personally it sounds to me like you are just offended by using older techniques rather than getting the chance to play with new toys. You seem to have no real basis for wanting to change other than bulk insert is so 2000.