I need to convert all varchar columns in about 40 tables (filled with the data) to nvarchar columns. It is planned to happen in a dedicated MS SQL server used only for the purpose. The result should be moved to Azure SQL.
Where should be the conversion done: on the old SQL, or after moving it on Azure SQL Server?
According to Remus Rusanu's answer https://stackoverflow.com/a/8157951/1346705, new nvarchar columns are created in the process, and the old varchar columns are dropped. The space can be reclaimed by DBCC CLEANTABLE or using ALTER TABLE ... REBUILD. Are the dropped varchar columns packed into the backup table, or does the backup/restore also remove the dropped columns?
Can the process be somehow automated using a universal SQL script? Or is it necessary to write the script for each individual table?
Context: We are the 3rd party with respect to the enterprise information system. Our product reads from the information system SQL database and presents the data the way that would otherwise be expensive to implement in the IS. The enterprise information system is now migrated to the new version and is to be run on Azure SQL. The database of the IS have been changed heavily, and one of the changes was to abandon the old 8-bit text encoding (varchar) and to use Unicode instead (nvarchar). Our system was used also for collecting data typed manually -- using the same encoding that the old IS used.
Migration is to be done via doing old version of backup (SqlCmd that produces xxx.bak files), restoring on another good old SQL server. Then we run the script that removes all the tables, views, and stored procedures that can be reconstructed from the IS. One of the main reasons is that the SQL code uses features that are not accepted by the new backup tool SqlPackage.exe to produce xxx.bacpac file. Then the bacpac file is restored in Azure SQL.
Where should be the conversion done: on the old SQL, or after moving it on Azure SQL Server?
I would do it on local SQLServer First,Running this on Azure database,might cause you to run into some issues like hitting your DTU limits,disk IO throttling..
Are the dropped varchar columns packed into the backup table, or does the backup/restore also remove the dropped columns?
The space wont be released back to filesystem,also backup doesn't process free spaces,so you will not see much change there.You might want to read more on dbcc cleantable though,before proceeding ..
Can the process be somehow automated using a universal SQL script? Or is it necessary to write the script for each individual table?
It can be automated,may be you can use dynamic sql to see the column type and process further.You will also have to see if any of those columns are part of indexes,if so you have to drop them first
I suggest making the schema changes beforehand on the old instances. Even if you don't bother cleaning up space with DBCC CLEAANTABLE or ALTER...REBUILD, the resultant bacpac size will be the same because, unlike a physical backup/restore, a bacpac file is just a compressed package format of schema and data.
Consider using SQL Server Data Tools (SSDT) to facilitate the schema changes. This will consider all the dependencies (constraints, indexes, etc.) that is a challenge with a "universal" T-SQL solution. SSDT will generally generate a migration script that employs temp tables for such schema changes so the end result won't have wasted space in your old database. However, you will need sufficient unused space in the database to contain the old/new objects side-by-side.
Related
Requirement :
Transfer millions of records from source (SQL Server) to destination (SQL Server).
Structure of source tables is different from destination tables.
Refresh data once per week in destination server.
Minimum amount of time for the processing.
I am looking for optimized approach using SSIS.
Was thinking these options :
Create Sql dump from source server and import that dump in destination server.
Directly copy the tables from source server to destination server.
Lots of issues to consider here. Such as are the servers in the same domain, on same network, etc.
Most of the time you will not want to move the data as a single large chunk of millions of records but in smaller amounts. An SSIS package handles that logic for you, but you can always recreate it as well but iterating the changes easier. Sometimes this is a reason to push changes more often rather than wait an entire week as smaller syncs are easier to manage with less downtime.
Another consideration is to be sure you understand your delta's and to ensure that you have ALL of the changes. For this reason I would generally suggest using a staging table at the destination server. By moving changes to staging and then loading to the final table you can more easily ensure that changes are applied correctly. Think of the scenario of a an increment being out of order (identity insert), datetime ordered incorrectly or 1 chunk failing. When using a staging table you don't have to rely solely on the id/date and can actually do joins on primary keys to look for changes.
Linked Servers proposed by Alex K. can be a great fit, but you will need to pay close attention to a couple of things. Always do it from Destination server so that it is a PULL not a push. Linked servers are fast at querying the data but horrible at updating/inserting in bulk. 1 XML column cannot be in the table at all. You may need to set some specific properties for distributed transactions.
I have done this task both ways and I would say that SSIS does give a bit of advantage over Linked Server just because of its robust error handling, threading logic, and ability to use different adapters (OLEDB, ODBC, etc. they have different performance do a search and you will find some results). But the key to your #4 is to do it in smaller chunks and from a staging table and if you can do it more often it is less likely to have an impact. E.g. daily means it would already be ~1/7th of the size as weekly assuming even daily distribution of changes.
Take 10,000,000 records changed a week.
Once weekly = 10mill
once daily = 1.4 mill
Once hourly = 59K records
Once Every 5 minutes = less than 5K records
And if it has to be once a week. just think about still doing it in small chunks so that each insert will have more minimal affect on your transaction logs, actual lock time on production table etc. Be sure that you never allow loading of a partially staged/transferred data otherwise identifying delta's could get messed up and you could end up missing changes/etc.
One other thought if this is a scenario like a reporting instance and you have enough server resources. You could bring over your entire table from production into a staging or update a copy of the table at destination and then simply do a drop of current table and rename the staging table. This is an extreme scenario and not one I generally like but it is possible and actual impact to the user would be very nominal.
I think SSIS is good at transfer data, my approach here:
1. Create a package with one Data Flow Task to transfer data. If the structure of two tables is different then it's okay, just map them.
2. Create a SQL Server Agent job to run your package every weekend
Also, feature Track Data Changes (SQL Server) is also good to take a look. You can config when you want to sync data and it's good at performance too
With SQL Server versions >2005, it has been my experience that a dump to a file with an export is equal to or slower than transferring data directly from table to table with SSIS.
That said, and in addition to the excellent points #Matt makes, this the usual pattern I follow for this sort of transfer.
Create a set of tables in your destination database that have the same table schemas as the tables in your source system.
I typically put these into their own database schema so their purpose is clear.
I also typically use the SSIS OLE DB Destination package's "New" button to create the tables.
Mind the square brackets on [Schema].[TableName] when editing the CREATE TABLE statement it provides.
Use SSIS Data Flow tasks to pull the data from the source to the replica tables in the destination.
This can be one package or many, depending on how many tables you're pulling over.
Create stored procedures in your destination database to transform the data into the shape it needs to be in the final tables.
Using SSIS data transformations is, almost without exception, less efficient than using server side SQL processing.
Use SSIS Execute SQL tasks to call the stored procedures.
Use parallel processing via Sequence Containers where possible to save time.
This can be one package or many, depending on how many tables you're transforming.
(Optional) If the transformations are complex, requiring intermediate data sets, you may want to create a separate Staging database schema for this step.
You will have to decide whether you want to use the stored procedures to land the data in your ultimate destination tables, or if you want to have the procedures write to intermediate tables, and then move the transformed data directly into the final tables. Using intermediate tables minimizes down time on the final tables, but if your transformations are simple or very fast, this may not be an issue for you.
If you use intermediate tables, you will need a package or packages to manage the final data load into the destination tables.
Depending on the number of packages all of this takes, you may want to create a Master SSIS package that will call the extraction package(s), then the transformation package(s), and then, if you use intermediate processing tables, the final load package(s).
I have to recover a SQL 2008 R2 database for a POS system that broke down without proper backups in place. The .BAK file has been recovered, but was corrupted. However, I was able to retrieve most of the data and get it back into usable shape.
My problem now is as following:
I have database A, which is a fresh installation for the POS system, and database B, which is the recovered .BAK file.
Most of the tables in B are missing their index values, while A has an intact structure, but is (obviously) lacking all the valuable data.
How would I go about merging the two, so that I get a fully-indexed database with the correct structure?
One simple way is to use the builtin command line tool tablediff.exe. It can compare two tables/views, and print out the differences.
The tablediff utility is used to compare the data in two tables for non-convergence, and is particularly useful for troubleshooting non-convergence in a replication topology. This utility can be used from the command prompt or in a batch file to perform the following tasks:
A row by row comparison between a source table in an instance of Microsoft SQL Server acting as a replication Publisher and the destination table at one or more instances of SQL Server acting as replication Subscribers.
Perform a fast comparison by only comparing row counts and schema.
Perform column-level comparisons.
Generate a Transact-SQL script to fix discrepancies at the destination server to bring the source and destination tables into convergence.
Log results to an output file or into a table in the destination database.
I'm copying data from a SQLServer2012 database to a SQLServer2014 database using Tasks>>Generate scripts... and selecting Data only in the Advanced Options.
The problem appears when I try to execute the resulting script in the SQLServer2014 database. The error is:
The conversion of a nvarchar data type to a datetime data type
resulted in an out-of-range
I know that's probably because the databases have different cultures and the inserts which the first server are generating:
INSERT [dbo].[CollectionSet] ([Id], [CreationDate], [Active], [MenuOrder]) VALUES (1, CAST(N'2015-09-18 00:00:00.000' AS DateTime), 1, 1)
do not work in the second server.
So, my question is: How can I generate a script with the correct date format so it can work on the second server?
PD: I have no access to Management Studio on the destination server.
If I can recall it correctly (fixme?) the Generate Scripts SSMS feature will not allow to do any transformation and it assumes that the destination where you want to execute the output has the same (or at least compatible) configuration (collation, table structure, etc).
Here are some solutions/workarounds (braindump):
ETL Tool (SSIS for example)
Your best bet is to use an ETL tool such as SSIS (shipped with SQL Server Standard and above) to extract-transorm-load your data across servers.
You can generate SSIS Packages by using the Import / Export wizard(s) (under Tasks in the database context menu).
Using backups
You can always create a database backup on the source server, then restore it on the destination server. To migrate the data into the new database, you can use regular SQL queries.
Workarounds
Create a view on the problematic table and transform the problematic column in the view, then export the view.
Build a view on the destination server (with transformations), insert into that view.
In my opinion, the most flexible solution is to use an ETL tool, like SSIS, create the packages and execute them.
As a last thought: Most probably you can't solve this problem without investing some time in it (like write queries manually for each problematic tables, or to build/edit SSIS packages).
I have an application that produce approximately 15000 rows int a table named ExampleLog for each Task. The task has a taskID, that is saved in a table named TaskTable, thus it's possible to retrieve data from the ExampleLog table to run some queries.
The problem is that the ExampleLog table is getting very big, since I run everyday at least 1 task. At the time being my ExampleLog table is over 60 GB.
I would like to compress the 15000 rows which belong to a TaskID, and compress them or just Zip them and then save the compressed data somewhere inside the database as Blob or as Filestream. But it is important for me to be able to query easily the compressed or zipped file and proccess some query in a efficient manner inside the compressed or zipped data. (I don't know, if it's possible or I may lost in term of performance)
PS: The compressed data should not be considered as backup data.
Did someone can recommend an good approach or technique to resolve this problem. My focus is on the speed and of the query running on the ExampleLog and the place taken on the disk.
I'm using SQL Server 2008 on Windows 7
Consider Read-Only Filegroups and Compression.
Using NTFS Compression with Read-Only User-defined Filegroups and Read-Only Databases
SQL Server supports NTFS compression of read-only
user-defined filegroups and read-only databases. You should consider
compressing read-only data in the following situations: You have a
large volume of static or historical data that must be available for
limited read-only access. You have limited disk space.
Also, you can try and estimate the gains from page compression applied to the log table using Data Compression Wizard.
The answer of Denis could not solve my Problem completely, however I will use it for some optimization inside the DB.
Regarding the problem of storing data in package/group, there are 2 solutions of my problem:
The first solution is the use of the Partitioned Table and Index Concepts.
For example, if a current month of data is primarily used for INSERT, UPDATE, DELETE, and MERGE operations while previous months are used primarily for SELECT queries, managing this table may be easier if it is partitioned by month. This benefit can be especially true if regular maintenance operations on the table only have to target a subset of the data. If the table is not partitioned, these operations can consume lots of resources on an entire data set. With partitioning, maintenance operations, such as index rebuilds and defragmentations, can be performed on a single month of write-only data, for example, while the read-only data is still available for online access.
The second solution it to insert from the code (C# in my case) a List or Dictionary of row from a Task, then save them inside a FILESTREAM (SQL Server) on the DB server. Data will later by retrived by Id; the zip will be decompressed and data will be ready to use.
We have decided to use the second solution.
I am a C# developer, I am not really good with SQL. I have a simple questions here. I need to move more than 50 millions records from a database to other database. I tried to use the import function in ms SQL, however it got stuck because the log was full (I got an error message The transaction log for database 'mydatabase' is full due to 'LOG_BACKUP'). The database recovery model was set to simple. My friend said that importing millions records using task->import data will cause the log to be massive and told me to use loop instead to transfer the data, does anyone know how and why? thanks in advance
If you are moving the entire database, use backup and restore, it will be the quickest and easiest.
http://technet.microsoft.com/en-us/library/ms187048.aspx
If you are just moving a single table read about and use the BCP command line tools for this many records:
The bcp utility bulk copies data between an instance of Microsoft SQL Server and a data file in a user-specified format. The bcp utility can be used to import large numbers of new rows into SQL Server tables or to export data out of tables into data files. Except when used with the queryout option, the utility requires no knowledge of Transact-SQL. To import data into a table, you must either use a format file created for that table or understand the structure of the table and the types of data that are valid for its columns.
http://technet.microsoft.com/en-us/library/ms162802.aspx
The fastest and probably most reliable way is to bulk copy the data out via SQL Server's bcp.exe utility. If the schema on the destination database is exactly identical to that on the source database, including nullability of columns, export it in "native format":
http://technet.microsoft.com/en-us/library/ms191232.aspx
http://technet.microsoft.com/en-us/library/ms189941.aspx
If the schema differs between source and target, you will encounter...interesting (yes, interesting is a good word for it) problems.
If the schemas differ or you need to perform any transforms on the data, consider using text format. Or another format (BCP lets you create and use a format file to specify the format of the data for export/import).
You might consider exporting data in chunks: if you encounter problems it gives you an easier time of restarting without losing all the work done so far.
You might also consider zipping the exported data files up to minimize time on the wire.
Then FTP the files over to the destination server.
bcp them in. You can use the bcp utility on the destination server for the BULK IMPORT statement in SQL Server to do the work. Makes no real difference.
The nice thing about using BCP to load the data is that the load is what is described as a 'non-logged' transaction, though it's really more like a 'minimally logged' transaction.
If the tables on the destination server have IDENTITY columns, you'll need to use SET IDENTITY statement to disable the identity column on the the table(s) involved for the nonce (don't forget to reenable it). After your data is imported, you'll need to run DBCC CHECKIDENT to get things back in synch.
And depending on what your doing, it can sometimes be helpful to put the database in single-user mode or dbo-only mode for the duration of the surgery: http://msdn.microsoft.com/en-us/library/bb522682.aspx
Another approach I've used to great effect is to use Perl's DBI/DBD modules (which provide access to the bulk copy interface) and write a perl script to suck out the data from the source server, transform it and bulk load it directly into the destination server, without having to save it to disk and move it. Also means you can trap errors and design things for recovery and restart right at the point of failure.
Use BCP to migrate data.
Another approach i have used in the past is to take a backup of the transaction log and shrink the log Prior to the migration. Split the migration script in parts and run the log backup- shrink - migrate iteration a few times.