I'm looking for a way to speed up the following process: I have a SSIS package that loads data from Excel files on a weekly basis to SQL Server. There are 3 fields: Brand, Date, Value.
In the dataflow, I check for existing combinations of Brand+Date, and new combinations go to the table directly, the existing ones go to a RecordSet destination for updates:
The next step is to update the Value of the existing combinations:
As you can see, there are thousands of records to update, and it takes too long. The number of records tend to grow week by week. Please suggest.
The fastest way will be do this inside a Stored procedure using ELT (Extract Load Transform) approach.
Push all data from excel as is into a table(called load to a staging table in theory). Since you do not seem to be concerned with data validation steps, this table can be a replica of final destination table columns.
Next step is to call a stored procedure using Execute SQL task. Inside this procedure you can put all your business logic. Since this steps with native data manipulation on SQL server entities, it is the fastest alternative.
As a last part, please delete all entries from the staging table.
You can use indexes on staging table to make the SP part even faster.
Related
I have 2 tables. The source table being from a linked server and destination table being from the other server.
I want my data load to happen in the following manner:
Everyday at night I have scheduled a job to do a full dump i.e. truncate the table and load all the data from the source to the destination.
Every 15 minutes to do incremental load as data gets ingested into the source on second basis. I need to replicate the same on the destination too.
For incremental load as of now I have created scripts which are stored in a stored procedure but for future purposes we would like to implement SSIS for this case.
The scripts run in the below manner:
I have an Inserted_Date column, on the basis of this column I take the max of that column and delete all the rows that are greater than or equal to the Max(Inserted_Date) and insert all the similar values from the source to the destination. This job runs evert 15 minutes.
How to implement similar scenario in SSIS?
I have worked on SSIS using the lookup and conditional split using ID columns, but these tables I am working with have a lot of rows so lookup takes up a lot of the time and this is not the right solution to be implemented for my scenario.
Is there any way I can get Max(Inserted_Date) logic into SSIS solution too. My end goal is to remove the approach using scripts and replicate the same approach using SSIS.
Here is the general Control Flow:
There's plenty to go on here, but you may need to learn how to set variables from an Execute SQL and so on.
I have a database1 which has more than 500 tables and I have database2 which also has the same number of tables and in both the databases the name of tables are same.. some of the tables have different table definitions, for example a table reports in database1 has 9 columns and the table reports in database2 has 10.
I want to copy all the data from database1 to database2 and it should overwrite the same data and append the columns if structure does not match. I have tried the import export wizard in SQL Server 2008 but it gives an error when it comes to the last step of copying rows. I don't have the screen shot of that error right now, it is my office PC. It says that error inserting into the readonly column xyz, some times it says that vs_isbroken, for the read only column error as I mentioned a enabled the identity insert but it did not help..
Please help me. It is an opportunity in my office for me.
SSIS and SQL Server 2008 Wizards can be finicky tools.
If you get a "can't insert into column ABC", then it could be one of the following:
Inserting into a PK column -> when setting up the mappings, you need to indicate to overwrite the value
Inserting into a column with a smaller range -> for example from nvarchar(256) into nvarchar(50)
Inserting into a calculated column (pointed out by #Nick.McDermaid)
You could also get issues with referential integrity if your database uses this (most do).
If you're going to do this more often, then I suggest you build an SSIS package instead of using the wizard tooling. This way you will see warnings on all sorts of issues like the ones I've described above. You can then run your package on demand.
Another suggestion I would make, is that you insert DB1 into "stage" tables in DB2. These tables should have no relational integrity and will allow you to break the process into several steps as follows.
Stage the data from DB1 into DB2
Produce reports/queries on issues pertinent to your database/rules
Merge the data from stage tables into target tables using SQL
That last step is where you can use merge statements, or simple insert/updates depending on a key match. Using SQL here in the local database is then able to use set theory to manage the overlap of the two sets and figure out what is new or to be updated.
SSIS "can" do this, but you will not be able to do a bulk update using SSIS, whereas with SQL you can. SSIS would do what is known as RBAR (row by agonizing row), something slow and to be avoided.
I suggest you inform your seniors that this will take a little longer to ensure it is reliable and the results reportable. Then work step by step, reporting on each stages completion.
Another two small suggestions:
Create _Archive tables of each of the stage tables and add a Tstamp column to each. Merge into these after the stage step which will allow you to quickly see when which rows were introduced into DB2
After stage and before the SQL merge step, create indexes on your stage tables. This will improve the merge performance
Drop those Indexes after each merge, this will increase the bulk insert Performance
Basic on Staging (response to question clarification):
Links:
http://www.codeproject.com/Articles/173918/How-to-Create-your-First-SQL-Server-Integration-Se
http://www.jasonstrate.com/tag/31daysssis/
http://blogs.msdn.com/b/andreasderuiter/archive/2012/12/05/designing-an-etl-process-with-ssis-two-approaches-to-extracting-and-transforming-data.aspx
Staging is the act of moving data from one place to another without any checks.
First you need to create the target tables, the schema should match the source tables.
Open up BIDS and create a new Project and in it a new SSIS package.
In the package, create a connection for the source server and another for the destination.
Then create a data flow step, in the step create a data source for each table you want to copy from.
Connect each source to a new data destination and set the appropriate connection and table.
When done, save and do a test run.
Before the data flow step, you might like to add a SQL step that will truncate all the target tables.
If you're open to using tools then what about using something like Red Gate Sql Compare and Red Gate SQL Data Compare?
First I would use data compare to manage the schema differences, add the new columns you want to your destination database (database2) from the source (database1). Then with data compare you match the contents of the tables any columns it can't match based on names you specify how to handle. Then you can pick and choose what data you want to copy from your destination. So you'll see what data is new and what's different (you can delete data in the destination that's not in the source or ignore it). You can either have the tool do the work or create you a script to run when you want.
There's a 15 day trial if you want to experiment.
Seems like maybe you are looking for Replication technology as is offered by SQL Server Replication.
Well, if i understood your requirement correctly, you need to make database2 a replica of database1. Why not take a full backup of database1 and restore it as database2? Your database2 will be exactly what database1 is at the time of backup.
I am new to SSIS.I got the task have according to the scenario as explained.
Scenario:
I have two databases A and B on different machines and have around 25 tables and 20 columns with relationships and dependencies. My task is to create a database C with selected no of tables and in each table I don't require all the columns but selected some. Conditions to be met are that the relationships should be intact and created automatically in new database.
What I have done:
I have created a package using the transfer SQL Server object task to transfer the tables and relationships.
then I have manually edited the columns that are not required
and then I transferred the data using the data source and destination
My question is: can I achieve all these things in one package? Also after I have transferred the data how can I schedule the package to just transfer the recently inserted rows in the database to the new database?
Please help me
thanks in advance
You can schedule the package by using a SQL Server Agent Job - one of the options for a job step is run SSIS package.
With regard to transferring new rows, I would either:
Track your current "position" in another table, assumes you have either an ascending key or a time stamp column - load the current position into an SSIS variable, use this variable in the WHERE statement of your data source queries.
Transfer all data across into "dump" copies of each table (no relationships/keys etc required just the same schema) & use a T-SQL MERGE statement to load new rows in, then truncate "dump" tables.
Hope this makes sense - its a bit difficult to get across in writing.
I have a .csv file that gets pivoted into 6 million rows during a SSIS package. I have a table in SQLServer 2005 of 25 million + rows. The .csv file has data that duplicates data in the table, is it possible for rows to get updated if it already exists or what would be the best method to achieve this efficiently?
Comparing 6m rows against 25m rows is not going to be too efficient with a lookup or a SQL command data flow component being called for each row to do an upsert. In these cases, sometimes it is most efficient to load them quickly into a staging table and use a single set-based SQL command to do the upsert.
Even if you do decide to do the lookup - split the flow into two streams, one which inserts and the other which inserts into a staging table for an update operation.
If you don't mind losing the old data (ie. the latest file is all that matters, not what's in the table) you could erase all the records in the table and insert them again.
You could also load into a temporary table and determine what needs to be updated and what needs to be inserted from there.
You can use the Lookup task to identify any matching rows in the CSV and the table, then pass the output of this to another table or data flow and use a SQL task to perform the required Update.
In one SQL Task can I create a table variable
DELCARE #TableVar TABLE (...)
Then in another SQL Task or DataSource destination and select or insert into the table variable?
The other option I have considered is using a Temp Table.
CREATE TABLE #TempTable (...)
I would prefer to use Table Variable so that it remains in memory. But can use temp table if it is not possible to use table variable. Also I cannot use the record set destination as I need to preform straight SQL tasks on it later on.
The use case that this is trying to solve is essentially performing a transformation in the stead of BizTalk. There is a very large flat file to flat file transformation that BizTalk has to transform unfortunately the data volume would produce unacceptable load on the BizTalk server so the idea is to off load it to SSIS. However, it is not a simple row to row transformation, there are different types of rows which have relations to each other. The first task in SSIS is to load the row into appropriate (temp) tables, then in the second data task a select is preformed with the correct format for output.
You could use some of the techniques in this post: http://consultingblogs.emc.com/jamiethomson/archive/2006/11/19/SSIS_3A00_-Using-temporary-tables.aspx
especially the ones about using RetainSameConnection=TRUE on the connection manager.
I would be interested to see more information about what use case you have that requires you to write out data to a temp table or table variable before further SSIS processing. Couldn't you take care of all of the SQL required steps in your source query before you start processing the dataflow with SSIS?
Table variables are not kept solely in memory and can be written to disk under memory pressure. I tend to use table variables for very small lookups. If you Need to push a table into SQL Server due to necessary and complex transformations, then use a 'permanent' temp table that is truncated within the SSIS package prior to insert. Simple and will get what you need done.
The SSIS package would be run in a job. I assume it runs inside a SQL job. In that case, using a temp table won't harm. SQL Jobs are generally run after office hours so it does not matter.