Do you know how to transfer only new records between two different databases (ie. Oracle and MSSQL) using SSIS? There is no problem transfering new data only between two tables in the same database and server, but is this possible to do such operation between completely different servers and databases?
Ps. I know about solution using Lookup but it is not very efficient if anybody needs to check and add a lot of records (50k and more) several times per day. I would like to operate with new data only.
You have several options:
Timestamp based solution
If you have a column which stores the insertation time in the source system, you can select only the new records created since the last load. With the same logic, you can transfer modified records too, just mark the records with the timestamp value when it change.
Sequence based solution
If there is a sequence in the source table, you can load the new records based on that sequence. Query the last value from the destination system, then load avarything which is larger than that value.
CDC based solution
If you have CDC (Change Data Capture) in your source system, you can track the changes and you can load them based on the CDC entries.
Full load
This is the most resource hungry solution: you have to copy all data from the source to the destination. If you do not have any column which marks the new records, you should use this solution.
You have several options to achieve this:
TRUNCATE the destination table and reload it from source
Use a Lookup component to determine which records are missing
Load all data from source to a temporary table and write a query which retrieves the new/changed records.
Summary
If you have at least one column, which marks the new/modified records, you can use it to implement a differential/incremental load with SSIS. If you do not have any clue, which columns/rows are changed, you have to load (or at least query) all of them.
There is no solution which enables a one-query (INSERT .. SELECT) solution using multiple servers without transferring all data. (Please note, that a multi-server query using Linked Servers are transfers the data from the source system).
What about variables? Is it possible to use the same variable between different databases and servers in SSIS?
I would like to transfer last id number from a destination table and transfer it to the source table (different server!).
I can set a variable in a database scope like this:
DECLARE #Last int
SET #Last = (SELECT TOP 1 Id FROM dbo.Table_1 ORDER BY Id DESC)
SELECT *
FROM dbo.Table_2
WHERE ID > #Last;
However it works between two tables in the same database (as a SQL command) only. I can create a variable for a entire SSIS package in Variables --> Add variable, but I don't know it is possible to use the variable in a similar way as above - to keep an information about last id in a destination table and pass it to another table on a source server as data limit.
Related
I have source and destination tables. In that almost 30 millions of records are there in Source Table in One server. Now I want to copy this data to another table which is in another server. And at the same time, this copy of data is not once. When ever the data changes in source table , need to insert/update/delete in destination by comparing with a key.
Solutions that I tried
Step 1. There is already linked connection between two servers. For inserting data to destination table, I used OPENROWSET function like this for copying data from one server to another server.
INSERT INTO destination table
SELECT *
FROM OPENROWSET('SQLOLEDB', 'provider string', query from source table)
Step 2. After this for making recent changes(delta mode) to destination table , I was using MERGE statement
I have created a procedure for step-1 & 2
Problem
But the problem is since the data is huge it is taking lot of time (more than 2 hours) for inserting the data and for MERGE statement.
Is anybody aware of how can I achieve this case with in less time. Please suggest
Thanks
I have been searching on the internet for a solution to my problem but I can not seem to find any info. I have a large single text file ( 10 million rows), I need to create an SSIS package to load these records into different tables based on the transaction group assigned to that record. That is Tx_grp1 would go into Tx_Grp1 table, Tx_Grp2 would go into Tx_Grp2 table and so forth. There are 37 different transaction groups in the single delimited text file, records are inserted into this file as to when they actually occurred (by time). Also, each transaction group has a different number of fields
Sample data file
date|tx_grp1|field1|field2|field3
date|tx_grp2|field1|field2|field3|field4
date|tx_grp10|field1|field2
.......
Any suggestion on how to proceed would be greatly appreciated.
This task can be solved with SSIS, just with some experience. Here are the main steps and discussion:
Define a Flat file data source for your file, describing all columns. Possible problems here - different data types of fields based on tx_group value. If this is the case, I would declare all fields as strings long enough and later in the dataflow - convert its type.
Create a OLEDB Connection manager for the DB you will use to store the results.
Create a main dataflow where you will proceed the file, and add a Flat File Source.
Add a Conditional Split to the output of Flat file source, and define there as much filters and outputs as you have transaction groups.
For each transaction group data output - add Data Conversion for fields if necessary. Note - you cannot change data type of existing column, if you need to cast string to int - create a new column.
Add for each destination table an OLEDB Destination. Connect it to proper transaction group data flow, and map fields.
Basically, you are done. Test the package thoroughly on a test DB before using it on a production DB.
I have a desktop application through which data is entered and it is being captured in MS Access DB. The application is being used by multiple users(at different locations). The idea is to download data entered for that particular day into an excel sheet and load it into a centralized server, which is an MSSQL server instance.
i.e. data(in the form of excel sheets) will come from multiple locations and saved into a shared folder in the server, which need to be loaded into SQL Server.
There is a ID column with IDENTITY in the MSSQL server table, which is the primary key column and there are no other columns in the table which contains unique value. Though the data is coming from multiple sources, we need to maintain single auto-updating series(IDENTITY).
Suppose, if there are 2 sources,
Source1: Has 100 records entered for the day.
Source2: Has 200 records entered for the day.
When they get loaded into Destination(SQL Server), table should have 300 records, with ID column values from 1 to 300.
Also, for the next day, when the data comes from the sources, Destination has to load data from 301 ID column.
The issue is, there may be some requests to change the data at Source, which is already loaded in central server. So how to update the data for that row in the central server as the ID column value will not be same in Source and Destination. As mentioned earlier ID is the only unique value column in the table.
Please suggest some ides to do this or I've to take up different approach to accomplish this task.
Thanks in advance!
Krishna
Okay so first I would suggest .NET and doing it through a File Stream Reader, dumping it to the disconnected layer of ADO.NET in a DataSet with multiple DataTables from the different sources. But... you mentioned SSIS so I will go that route.
Create an SSIS project in Business Intelligence Development Studio(BIDS).
If you know for a fact you are just doing a bunch of importing of Excel files I would just create many 'Data Flow Task's or many Source to Destination tasks in a single 'Data Flow Task' up to you.
a. Personally I would create tables in a database for each location of an excel file and have their columns map up. I will explain why later.
b. In a data flow task, select 'Excel Source' as the source file. Put in the appropriate location of 'new connection' by double clicking the Excel Source
c. Choose an ADO Net Destination, drag the blue line from the Excel Source to this endpoint.
d. Map your destination to be the table you map to from SQL.
e. Repeat as needed for each Excel destination
Set up the SSIS task to automate from SQL Server through SQL Management Studio. Remember you to connect to an integration instance, not a database instance.
Okay now you have a bunch of tables right instead of one big one? I did that for a reason as these should be entry points and the logic to determinate dupes and import time I would leave to another table.
I would set up another two tables for the combination of logic and for auditing later.
a. Create a table like 'Imports' or similar, have the columns be the same except add three more columns to it: 'ExcelFileLocation', 'DateImported'. Create an 'identity' column as the first column and have it seed on the default of (1,1), assign it the primary key.
b. Create a second table like 'ImportDupes' or similar, repeat the process above for the columns.
c. Create a unique constraint on the first table of either a value or set of values that make the import unique.
c. Write a 'procedure' in SQL to do inserts from the MANY tables that match up to the excel files to insert into the ONE 'Imports' location. In the many inserts do a process similar to:
Begin try
Insert into Imports (datacol1, datacol2, ExcelFileLocation, DateImported) values
Select datacol1, datacol2, (location of file), getdate()
From TableExcel1
End try
-- if logic breaks unique constraint put it into second table
Begin Catch
Insert into ImportDupes (datacol1, datacol2, ExcelFileLocation, DateImported) values
Select datacol1, datacol2, (location of file), getdate()
From TableExcel1
End Catch
-- repeat above for EACH excel table
-- clean up the individual staging tables for the next import cycle for EACH excel table
truncate TableExcel1
d. Automate the procedure to go off
You now have two tables, one for successful imports and one for duplicates.
The reason I did what I did is two fold:
You need to know more detail than just the detail a lot of times like when it came in, from what source it came from, was it a duplicate, if you do this for millions of rows can it be indexed easily?
This model is easier to take apart and automate. It may be more work to set up but if a piece breaks you can see where and easily stop the import for one location by turning off the code in a section.
I receive new data files every day. Right now, I'm building the database with all the required tables to import the data and perform the required calculations.
Should I just append each new day's data to my current tables? Each file contains a date column, which would allow for a "WHERE" query in the future if I need to analyze data for one particular day. Or should I be creating a new set of tables for every day?
I'm new to database design (coming from Excel). I will be using SQL Server for this.
Assuming that the structure of the data being received is the same, you should only need one set of tables rather than creating new tables each day.
I'd recommend storing the value of the date column from your incoming data in your database, and also having a 'CreateDate' column in your tables, with a default value of 'GetDate()' so that it automatically gets populated with the current date when the row is inserted.
You may also want to have another column to store the data filename that the row was imported from, but if you're already storing the value of the date column and the date that the row was inserted, this shouldn't really be necessary.
In the past, when doing this type of activity using a custom data loader application, I've also found it useful to create log files to log success/error/warning messages, including some type of unique key of the source data and target database - ie. if coming from an Excel file and going into a database column, you could store the row index from Excel and the primary key of the inserted row. This helps tracking down any problems later on.
You might want to consider having a look at SSIS (SqlServer Integration Services). It's the SqlServer tool for doing ETL activities.
yes, append each day's data to the tables; 1 set of tables for all data.
yes, use a date column to identify the day that the data was loaded.
maybe have another table with a date column and a clob column. The date to contain the load date and the clob to contain the file that you imported.
Good question. You most definitely should have a single set of tables and append the data daily. Consider this: if you create a new set of tables each day, what would, say, a monthly report query look like? A quarterly report query? It would be a mess, with UNIONs and JOINs all over the place.
A single set of tables with a WHERE clause makes the querying and reporting manageable.
You might do a little reading on relational database theory. Wikipedia is a good place to start. The basics are pretty straightforward if you have the knack for it.
I would have the data load into a stage table regardless and append to the main tables after. Once a week i would then refresh all data in the main table to ensure that the data remains correct as per the source.
Marcus
I am copying some user data from one SqlServer to another. Call them Alpha and Beta. The SSIS package runs on Beta and it gets the rows on Alpha that meet a certain condition. The package then adds the rows to Beta's table. Pretty simple and that works great.
The problem is that I only want to add new rows into Beta. Normally I would just do something simple like....
INSERT INTO BetaPeople
SELECT * From AlphaPeople
where ID NOT IN (SELECT ID FROM BetaPeople)
But this doesn't work in an SSIS package. At least I don't know how and that is the point of this question. How would one go about doing this across servers?
Your example seems simple, looks like you are adding only new people, not looking for changed data in existing records. In this case, store the last ID in the DB.
CREATE TABLE dbo.LAST (RW int, LastID Int)
go
INSERT INTO dbo.LAST (RW, LastID) VALUES (1,0)
Now you can use this to insert the last ID of the row transferred.
UPDATE dbo.LAST SET LastID = #myLastID WHERE RW = 1
When selecting OLEDB source, set data access mode to SQL Command and use
DECLARE #Last int
SET #Last = (SELECT LastID FROM dbo.LAST WHERE RW = 1)
SELECT * FROM AlphaPeople WHERE ID > #Last;
Note, I do assume that you are using ID int IDENTITY for your PK.
If you have to monitor for data changes of existing records, then have the "last changed" column in every table, and store time of the last transfer.
A different technique would involve setting-up a linked server on Beta to Alpha and running your example without using SSIS. I would expect this to be way slower and more resource intensive than the SSIS solution.
INSERT INTO dbo.BetaPeople
SELECT * FROM [Alpha].[myDB].[dbo].[AlphaPeople]
WHERE ID NOT IN (SELECT ID FROM dbo.BetaPeople)
Add a lookup between your source and destination.
Right click the lookup box to open Lookup Transformation Editor.
Choose [Redirect rows to no match output].
Open columns, map your key columns.
Add an entry with the table key in lookup column , lookup operation as
Connect lookup box to destination, choose [Lookup no Match Output]
Simplest method I have used is as follows:
Query Alpha in a Source task in a Dataflow and bring in records to the data flow.
Perform any needed Transformations.
Before writing to the Destination (Beta) perform a lookup matching the ID column from Alpha to those in Beta. On the first page of the Lookup Transformation editor, make sure you select "Redirect rows to no match output" from the dropdown list "Specify how to handle rows with now matching error"
Link the Lookup task to the Destination. This will give you a prompt where you can specify that it is the unmatched rows that you want to insert.
This is the classical Delta detection issue. The best solution is to use Change Data Capture with/without SSIS. If what you are looking for is a once in a life time activity, no need to go for SSIS. Use other means such as linked server and compare with existing records.
The following should solve issue of loading Changed and New records using SSIS:
Extract Data from Source usint Data flow.
Extract Data from Target.
Match on Primary key Add Unmatch records and split matched and unmatched records from Source and Matched records from Target call them Matched_Source,
Unmatch_Source and Matched_Target.
Compare Matched_Source and Matched_Target and Split Matched_Source to Changed and Unchanged.
Null load TempChanged Table.
Add Changed Records to TempChanged.
Execute SQL script/stored proc to Delete Records from Target for primary key in TempChanged and add records in TempChanged to Target.
Add Unmatched_Source to Target.
Another solution would be to use a temporary table.
In the properties for Beta's connection manager, change RetainSameConnection to true (by default SSIS runs each query in it's own connection, this would mean the temporary table would be killed as soon as it has been created).
Create a SQL Task using Beta's connection and use the following SQL to create your temporary table:
SELECT TOP 0 *
INTO ##beta_temp
FROM Beta
Next create a data flow that pulls data from Alpha and loads into ##beta_temp (you will need to run the SQL statement above on SSMS first so that Visual Studio can see the table at design time and you will also need to set the DelayValidation property to true on the Data Flow task).
Now you have two tables on the same server and you can just use your example SQL modified to use the temporary table.
INSERT INTO Beta
SELECT * FROM ##beta_temp
WHERE ID NOT IN (SELECT ID FROM Beta)