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.
Related
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.
Problem:
I need to get data sets from CSV files into SQL Server Express (SSMS v17.6) as efficiently as possible. The data sets update daily into the same CSV files on my local hard drive. Currently using MS Access 2010 (v14.0) as a middleman to aggregate the CSV files into linked tables.
Using the solutions below, the data transfers perfectly into SQL Server and does exactly what I want. But I cannot figure out how to refresh/update/sync the data at the end of each day with the newly added CSV data without having to re-import the entire data set each time.
Solutions:
Upsizing Wizard in MS Access - This works best in transferring all the tables perfectly to SQL Server databases. I cannot figure out how to update the tables though without deleting and repeating the same steps each day. None of the solutions or links that I have tried have panned out.
SQL Server Import/Export Wizard - This works fine also in getting the data over to SSMS one time. But I also cannot figure out how to update/sync this data with the new tables. Another issue is that choosing Microsoft Access as the data source through this method requires a .mdb file. The latest MS Access file formats are .accdb files so I have to save the database in an older .mdb version in order to export it to SQL Server.
Constraints:
I have no loyalty towards MS Access. I really am just looking for the most efficient way to get these CSV files consistently into a format where I can perform SQL queries on them. From all I have read, MS Access seems like the best way to do that.
I also have limited coding knowledge so more advanced VBA/C++ solutions will probably go over my head.
TLDR:
Trying to get several different daily updating local CSV files into a program where I can run SQL queries on them without having to do a full delete and re-import each day. Currently using MS Access 2010 to SQL Server Express (SSMS v17.6) which fulfills my needs, but does not update daily with the new data without re-importing everything.
Thank you!
You can use a staging table strategy to solve this problem.
When it's time to perform the daily update, import all of the data into one or more staging tables. Execute SQL statement to insert rows that exist in the imported data but not in the base data into the base data; similarly, delete rows from the base data that don't exist in the imported data; similarly, update base data rows that have changed values in the imported data.
Use your data dependencies to determine in which order tables should be modified.
I would run all deletes first, then inserts, and finally all updates.
This should be a fun challenge!
EDIT
You said:
I need to get data sets from CSV files into SQL Server Express (SSMS
v17.6) as efficiently as possible.
The most efficient way to put data into SQL Server tables is using SQL Bulk Copy. This can be implemented from the command line, an SSIS job, or through ADO.Net via any .Net language.
You state:
But I cannot figure out how to refresh/update/sync the data at the end
of each day with the newly added CSV data without having to re-import
the entire data set each time.
It seems you have two choices:
Toss the old data and replace it with the new data
Modify the old data so that it comes into alignment with the new data
In order to do number 1 above, you'd simply replace all the existing data with the new data, which you've already said you don't want to do, or at least you don't think you can do this efficiently. In order to do number 2 above, you have to compare the old data with the new data. In order to compare two sets of data, both sets of data have to be accessible wherever the comparison is to take place. So, you could perform the comparison in SQL Server, but the new data will need to be loaded into the database for comparison purposes. You can then purge the staging table after the process completes.
In thinking further about your issue, it seems the underlying issue is:
I really am just looking for the most efficient way to get these CSV
files consistently into a format where I can perform SQL queries on
them.
There exist applications built specifically to allow you to query this type of data.
You may want to have a look at Log Parser Lizard or Splunk. These are great tools for querying and digging into data hidden inside flat data files.
An Append Query is able to incrementally add additional new records to an existing table. However the question is whether your starting point data set (CSV) is just new records or whether that data set includes records already in the table.
This is a classic dilemma that needs to be managed in the Append Query set up.
If the CSV includes prior records - then you have to establish the 'new records' data sub set inside the CSV and append just those. For instance if you have a sequencing field then you can use a > logic from the existing table max. If that is not there then one would need to do a NOT compare of the table data with the csv data to identify which csv records are not already in the table.
You state you seek something 'more efficient' - but in truth there is nothing more efficient than a wholesale delete of all records and write of all records. Most of the time one can't do that - but if you can I would just stick with it.
I have an ETL process that will run periodically. I was using kettle (PDI) to extract the data from the source database and copy it to a stage database. For this I use several transformations with table input and table output steps. However, I think I could get inconsistent data if the source database is modified during the process, since this way I don't get a snapshot of the data. Furthermore, I don't know if the source database would be blocked. This would be a problem if the extraction takes some minutes (and it will take them). The advantage of PDI is that I can select only the necessary columns and use timestamps to get only the new data.
By the other hand, I think mysqldump with --single-transaction allows me to get the data in a consistent way and don't block the source database (all tables are innodb). The disadventage is that I would get innecessary data.
Can I use PDI, or I need mysqldump?
PD: I need to read specific tables from specific databases, so I think xtrabackup it's not a good option.
However, I think I could get inconsistent data if the source database is modified during the process, since this way I don't get a snapshot of the data
I think "Table Input" step doesn't take into account any modifications that are happening when you are reading. Try a simple experiment:
Take a .ktr file with a single table input and table output. Try loading the data into the target table. While in the middle of data load, insert few records in the source database. You will find that those records are not read into the target table. (note i tried with postgresql db and the number of rows read is : 1000000)
Now for your question, i suggest you using PDI since it gives you more control on the data in terms of versioning, sequences, SCDs and all the DWBI related activities. PDI makes it easier to load to the stage env. rather than simply dumping the entire tables.
Hope it helps :)
Interesting point. If you do all the table inputs in one transformation then at least they all start at same time but whilst likely to be consistent it's not guaranteed.
There is no reason you can't use pdi to orchestrate the process AND use mysql dump. In fact for bulk insert or extract it's nearly always better to use the vendor provided tools.
How do I copy data from multiple tables within one database to another database residing on a different server?
Is this possible through a BTEQ Script in Teradata?
If so, provide a sample.
If not, are there other options to do this other than using a flat-file?
This is not possible using BTEQ since you have mentioned both the databases are residing in different servers.
There are two solutions for this.
Arcmain - You need to use Arcmain Backup first, which creates files containing data from your tables. Then you need to use Arcmain restore which restores the data from the files
TPT - Teradata Parallel Transporter. This is a very advanced tool. This does not create any files like Arcmain. It directly moves the data between two teradata servers.(Wikipedia)
If I am understanding your question, you want to move a set of tables from one DB to another.
You can use the following syntax in a BTEQ Script to copy the tables and data:
CREATE TABLE <NewDB>.<NewTable> AS <OldDB>.<OldTable> WITH DATA AND STATS;
Or just the table structures:
CREATE TABLE <NewDB>.<NewTable> AS <OldDB>.<OldTable> WITH NO DATA AND NO STATS;
If you get real savvy you can create a BTEQ script that dynamically builds the above statement in a SELECT statement, exports the results, then in turn runs the newly exported file all within a single BTEQ script.
There are a bunch of other options that you can do with CREATE TABLE <...> AS <...>;. You would be best served reviewing the Teradata Manuals for more details.
There are a few more options which will allow you to copy from one table to another.
Possibly the simplest way would be to write a smallish program which uses one of their communication layers (ODBC, .NET Data Provider, JDBC, cli, etc.) and use that to take a select statement and an insert statement. This would require some work, but it would have less overhead than trying to learn how to write TPT scripts. You would not need any 'DBA' permissions to write your own.
Teradata also sells other applications which hides the complexity of some of the tools. Teradata Data Mover handles provides an abstraction layer between tools like arcmain and tpt. Access to this tool is most likely restricted to DBA types.
If you want to move data from one server to another server then
We can do this with the flat file.
First we have fetch data from source table to flat file through any utility such as bteq or fastexport.
then we can load this data into target table with the help of mload,fastload or bteq scripts.
I'm looking to execute a series of queries as part of a migration project. The scripts to be generated are produced from a tool which analyses the legacy database then produces a script to map each of the old entities to an appropriate new record. THe scripts run well for small entities but some have records in the hundreds of thousands which produce script files of around 80 MB.
What is the best way to run these scripts?
Is there some SQLCMD from the prompt which deals with larger scripts?
I could also break the scripts down into further smaller scripts but I don't want to have to execute hundreds of scripts to perform the migration.
If possible have the export tool modified to export a BULK INSERT compatible file.
Barring that, you can write a program that will parse the insert statements into something that BULK INSERT will accept.
BULK INSERT uses BCP format files which come in traditional (non-XML) or XML. Does it have to get a new identity and use it in a child and you can't get away with using SET IDENTITY INSERT ON because the database design has changed so much? If so, I think you might be better off using SSIS or similar and doing a Merge Join once the identities are assigned. You could also load the data into staging tables in SQL using SSIS or BCP and then use regular SQL (potentially within SSIS in a SQL task) with the OUTPUT INTO feature to capture the identities and use them in the children.
Just execute the script. We regularly run backup / restore scripts that are 100's Mb in size. It only takes 30 seconds or so.
If it is critical not to block your server for this amount to time, you'll have to really split it up a bit.
Also look into the -tab option of mysqldump with outputs the data using TO OUTFILE, which is more efficient and faster to load.
It sounds like this is generating a single INSERT for each row, which is really going to be pretty slow. If they are all wrapped in a transaction, too, that can be kind of slow (although the number of rows doesn't sound that big that it would cause a transaction to be nearly impossible - like if you were holding a multi-million row insert in a transaction).
You might be better off looking at ETL (DTS, SSIS, BCP or BULK INSERT FROM, or some other tool) to migrate the data instead of scripting each insert.
You could break up the script and execute it in parts (especially if currently it makes it all one big transaction), just automate the execution of the individual scripts using PowerShell or similar.
I've been looking into the "BULK INSERT" from file option but cannot see any examples of the file format. Can the file mix the row formats or does it have to always be consistent in a CSV fashion? The reason I ask is that I've got identities involved across various parent / child tables which is why inserts per row are currently being used.