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.
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.
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'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.
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 currently using a database that is poorly designed and a slow pipeline so i decided to copy a small portion of the database (15 tables) and only bring over some of those tables for example i want to bring only the rows that have a certain id.
But this is not a one time move i need to add all the stuff that is added to the old database added to the new one on an hourly basis. My research has led me to SSIS and that it may have a way of accomplishing this but i have found no clear examples on how it is done if in fact it is possible. Thanks in advance.
Yes it is possible . You can schedule your ssis package through sql agent to run on hourly basis .
For a table ,you can drag a Data Flow Task on to the control flow .Inside DFT ,you need to place an oledb Source component ,Lookup ,Data conversion (if the types are different in source and target table) and Oledb destination .
oledb Source component : Create a variable of type string and in the expression write your sql query to fetch the data based on ID.Now use this variable in source component.
Lookup: You need to select your source table and combine the primary key column from the source and destination table.It acts similar to inner join query .After combining the primary key from the both the tables ,select the columns which you need from the source .
Oledb destination : Simply select your target table and map the columns from Lookup no matched output .If you need to update the values from the source then use Lookup matched output and connect it to an execute SQL task and write the update query .
Please go thru the link and SO
Scheduling of SSIS package