I have a very large table from which I need to extract a subset of records, the last 30 days records, and to replicate this 30 days records to a second database, for reporting purposes. Now I am using transactional replication where I added a filter in the published articles to isolate the 30 days records, to get a near real time replication envirnment.
The issue I have is that : the replication seems to be incremental, meaning that the most recent records are added to the replica, but the older records are not removed so it keeps getting large.
When a record that is out of filtering criteria is updated and enters again under the filtering criteria the replication crashes with an "duplicate primary key error".
How to make it work so that the replica to contain only the last 30 days of data ?
Is the above described behaviour something that I shall expect to see ?
Many thanks,
Well the simplest way, is not to use mssql's filter. The simplest way is to change the SPS used for update and delete with custom sps so that you will not get errors on deleting (absent rows) and updating (absent rows). This is done from the article's advanced properties. In case of a delete you should just use a merge and filter there your criteria.
Also have a job that deletes from the tables what you need to have deleted.
Of course you will need to be very careful when doing structure updates, but it is doable.
Another more ugly way is to keep sql's stored procedures and just ignore the errors (through the distribution agent .. -SkipErrors 2601:2627:20598). This will require again a job to delete old rows and it will not bring you back into your scope the old rows that are just updated. All in all the first solution should be the best one.
Hope it helps.
Related
My data source cannot be a single table as I need data that spans across 6 tables. For that I have created a view that does joins on these tables.
When I use this view as data source, indexing takes a lot of times and times out. I tried increasing timeout to 40 minutes and one more suggested change:
"disableOrderByHighWaterMarkColumn" : true
It timed-out. I also set Batch Size:1000. This time it populated the index but failed after few hours saying "connection lost". and "thanks" to disableOrderByHighWaterMarkColumn, If I rerun indexer again it will process all the rows again.
My question is what is the best way to approach a solution to this problem.
Follow-up Question: Since I am relying on a view, I cannot have auto change tracking. I am using a high watermark column (LastUpdatedTime) to track changes in my View. I only want to keep 6 months of data in my index so I am not sure how I can do that when I am using View. I have "where CreateDateTime > dateadd(month, -6, getdate())" clause already in my View but this will not enable Indexer to delete "out-of-time-window" rows(documents) from index. How can I achieve my goals here?
Should I write a processor task to periodically query all documents using C# SDK and delete documents based on date?
Sorry to hear the Azure SQL Database indexer is giving you trouble. I noticed a couple of things in your question that might be worth thinking about in terms of SQL performance:
My data source cannot be a single table as I need data that spans across 6 tables. For that I have created a view that does joins on these tables When I use this view as data source, indexing takes a lot of times and times out.
It's worth taking a look at the query performance troubleshooting guide and figure out what exactly is happening in your Azure SQL database that is causing problems. Assuming you want to use change tracking support, the default query the indexer uses against the SQL database looks like this:
SELECT * FROM c WHERE hwm_column > #hwmvalue ORDER BY hwm_column
We frequently see issues with performance here when there isn't an index on the hwm_column or if hwm_column is computed. You can read more about issues with the high water mark column here.
I tried increasing timeout to 40 minutes and one more suggested change: "disableOrderByHighWaterMarkColumn" : true It timed-out. I also set Batch Size:1000. This time it populated the index but failed after few hours saying "connection lost". and "thanks" to disableOrderByHighWaterMarkColumn, If I rerun indexer again it will process all the rows again.
disableOrderByHighWaterMarkColumn doesn't seem like it will work for your scenario, so I agree that you shouldn't set it. Decreasing the batch size seems to have had a positive effect, I would consider measuring the performance gain here using the troubleshooting guide referenced above
Follow-up Question: Since I am relying on a view, I cannot have auto change tracking. I am using a high watermark column (LastUpdatedTime) to track changes in my View. I only want to keep 6 months of data in my index so I am not sure how I can do that when I am using View. I have "where CreateDateTime > dateadd(month, -6, getdate())" clause already in my View but this will not enable Indexer to delete "out-of-time-window" rows(documents) from index. How can I achieve my goals here? Should I write a processor task to periodically query all documents using C# SDK and delete documents based on date?
Instead of filtering out data that is more than 6 months old, I would consider adding soft delete policy. The challenge here is that the indexer needs to pick up rows that should be deleted. The easiest way to accomplish this might updating your application logic to add a new column to your view indicating the row should be deleted. Once the value of this column changes, the LastUpdatedTime should also be updated so it shows up in the next indexer query.
You can write your own processor task, but querying all documents in Azure Cognitive Search and paging through them may have negative performance implications on your search performance. I would recommend trying to get it working with your indexer first.
I have a database table which have more than 1 million records uniquely identified by a GUID column. I want to find out which of these record or rows was selected or retrieved in the last 5 years. The select query can happen from multiple places. Sometimes the row will be returned as a single row. Sometimes it will be part of a set of rows. there is select query that does the fetching from a jdbc connection from a java code. Also a SQL procedure also fetches data from the table.
My intention is to clean up a database table.I want to delete all rows which was never used( retrieved via select query) in last 5 years.
Does oracle DB have any inbuild meta data which can give me this information.
My alternative solution was to add a column LAST_ACCESSED and update this column whenever I select a row from this table. But this operation is a costly operation for me based on time taken for the whole process. Atleast 1000 - 10000 records will be selected from the table for a single operation. Is there any efficient way to do this rather than updating table after reading it. Mine is a multi threaded application. so update such large data set may result in deadlocks or large waiting period for the next read query.
Any elegant solution to this problem?
Oracle Database 12c introduced a new feature called Automatic Data Optimization that brings you Heat Maps to track table access (modifications as well as read operations). Careful, the feature is currently to be licensed under the Advanced Compression Option or In-Memory Option.
Heat Maps track whenever a database block has been modified or whenever a segment, i.e. a table or table partition, has been accessed. It does not track select operations per individual row, neither per individual block level because the overhead would be too heavy (data is generally often and concurrently read, having to keep a counter for each row would quickly become a very costly operation). However, if you have you data partitioned by date, e.g. create a new partition for every day, you can over time easily determine which days are still read and which ones can be archived or purged. Also Partitioning is an option that needs to be licensed.
Once you have reached that conclusion you can then either use In-Database Archiving to mark rows as archived or just go ahead and purge the rows. If you happen to have the data partitioned you can do easy DROP PARTITION operations to purge one or many partitions rather than having to do conventional DELETE statements.
I couldn't use any inbuild solutions. i tried below solutions
1)DB audit feature for select statements.
2)adding a trigger to update a date column whenever a select query is executed on the table.
Both were discarded. Audit uses up a lot of space and have performance hit. Similary trigger also had performance hit.
Finally i resolved the issue by maintaining a separate table were entries older than 5 years that are still used or selected in a query are inserted. While deleting I cross check this table and avoid deleting entries present in this table.
I use SSMS 2016. I have a view that has a few millions of records. The view is not indexed and should not be as it's being updated (insert, delete, update) every 5 minutes by a job on the server to then display update data sets in to the client calling application in GUI.
The view does a very heavy volume of conversion INT values to VARCHAR appending to them some string values.
The view also does some CAST operations on the NULL assigning them column names aliases. And the worst performance hit is that the view uses FOR XML PATH('') function on 20 columns.
Also the view uses two CTEs as the source as well as Subsidiaries to define a single column value.
I made sure I created the right indexes (Clustered, nonclustered,composite and Covering) that are used in the view Select,JOIN,and WHERE clauses.
Database Tuning Advisor also have not suggested anything that could substantialy improve performance.
AS a workaround I decided to create two identical physical tables with clustered indexes on each and using the Merge statement (further converted into a SP and then Into as SQL Server Agent Job) maintain them updated. And to assure there is no long locking of the view. I will then swap(rename) the tables names immediately after each merge finishes. So in this case all the heavy workload falls onto a SQL Server Agent Job keep the tables updated.
The problem is that the merge will take roughly 15 minutes considering current size of the data, which may increase in the future. So, I need to have a real time design to assure that the view has the most up-to-date information.
Any ideas?
I am in charge of maintaining a horribly written application and database that has 11 million records in some tables. I just recently optimized a query by adding a full text index. However, I believe there is some arcane DTS package that actually drops the entire table that i am searching, pulls data from a linked server, and repopulates it. my question is, when it deletes, truncates or drops the table, will the full-text have to get rebuilt, even though the table will get repopulated with almost the same data? Or does the index get maintained completely separately?
--edit---
It definitely looks like what they are doing in the DTS is truncating the old table and reimporting everything.
Thanks,
Craig
It actually depends whether the Changes Tracking is activated (set to AUTO) for this full-text index or not (set to MANUAL). In the latter case you need to manually rebuild your index and addition of new rows or deletions does not affect your index.
We have an indexed view that runs across three large tables. Two of these tables (A & B) are constantly getting updated with user transactions and the other table (C) contains data product info that is needs to be updated once a week. This product table contains over 6 million records.
We need this view across these three tables for our core business process and unfortunately we cannot change this aspect. We even had a sql server MVP come in to help test under load to make sure we have the most efficient configuration. There is one column in the product table that gets utilized in the view and has to be updated each week.
The problem we are now encountering is that as volume is increasing on our transactions against tables A & B, the update to Table C is causing deadlocks.
I have tried several different methods to no avail:
1) I was hoping that we could change the view so that table C could be a dirty read "WITH (NOLOCK)" but apparently that functionality is not available with indexes views.
2) I thought about updating a new column in Table C and then just renaming it when the process is done but you cannot do that due to the dependency in the view.
3) I also entertained the idea of writing this value to a temporary product table, and then running an ALTER statement against the view to have it point to my new table. however when i did that the indexes on my view were dropped and it took quite a bit of time to recreate them.
4) we tried to do the weekly update in small chunks (as small as 100 records at a time) but we still run into dead locks.
questions:
a) we are using sql server 2005. Does sql server 2008 have a new functionality with their indexed views that would help us? Is there now a way to do dirty reads w/ an indexed view?
b) a better approach to altering an existing view to point to a new table?
thanks!
The issue you're experiencing is that adding the indexed view between the three tables is causing lock contention. There is a really good post about the issue here : http://sqlblog.com/blogs/alexander_kuznetsov/archive/2009/06/02/be-ready-to-drop-your-indexed-view.aspx
Partitioning the table might provide some relief, although I don't know if the partitioning will circumvent the lock issue. You will have to upgrade to 2008 if you want to investigate this option however - as you need to use partition-aligned indexed views. 2005 will require you to drop the view before you swap in/out any partitions.
More information about partition-aligned indexed views: http://msdn.microsoft.com/en-us/library/dd171921.aspx
Have you considered making C a partitioned table and swapping in/out a partition as your price update mechanism? I'm not sure how that would work with an indexed view - I would think the index needs to be rebuilt at that point. I think this is probably the same situation you are seeing with the ALTER TABLE, actually.
Is the indexed view really necessary? i.e. could appropriate indexes on the 3 underlying tables perform just as well when a normal view is used? Remember that the indexed view may have to be updated on key changes to any of the three tables, while a index on a single table would only have to be updated if a key changes or data moves in just that table. Typically indexed views are indexed on different columns than the base tables because it is a different kind of section accross the data than is available in the underlying tables - does that description really apply?
How long does the pricing update take? This would appear to be the core of your problem, but it's hard to say without more information.
We can try this for avoid locking.
SELECT a,b,c FROM indexedview as v WITH (NOEXPAND,NOLOCK) WHERE ...