Do nothing with (no) match output in the lookup transformation (SSIS) - sql-server

I'm new to SSIS as well as Stackoverflow.
Here's my situation.
I'm building a database and an archive database which need to be synced daily. The records in the database need to be copied to the archieve. I use SSIS and daily jobs to do this. Obviously, I don't want SSIS to load all the data everytime, only the new records (that aren't in the archive yet). I want to use the lookup transformation to achieve this. I'm testing it and it works, it only copies the new data to the "no match output" (which is my archive). But I linked the "match output" to a new destination. But as there are many columns and records, it would be way too much to keep all those redundant data (ofcourse I can purge the data but I don't want to have those extra columns in the first place!). I actually don't want the "match output" to be send to anywhere! How to do this? Or some solution that is more efficient than what I'm doing now (sending the matched outputs to new destinations and deleting those columns or records later on).
P.S.
I already found this question on stackoverflow which is a similar question (except the other way around, the TS wants to do nothing with "no match output"): Sending no match output rows to nowhere
But the thing is that I don't want to download/use "thrash destination", I'd rather use everything that is already built in SSIS itself. And I don't understand how the derived column transformation could solve the problem.
There are no other answers on that question, so that's why I made a new thread.
Can anyone help me with this? (and excuse my English, it's not my native language)

Just don't map the match output. In case that gives an error map it to a row count, that way you can keep track of the amount of duplicate data being handled.
Would be even better to filter this in the source component though, for performance reasons

Related

Count how many fields where cleansed and which fields on SSIS

I'm doing an exercise in which I have to clean data from a Flat File Source and write it on my Database. I have already managed to clean all of the fields by using some data quality rules for each field and also generate error codes which I write to a different table when a rule is broken.
My problem is that for the final step of the exercise I have to generate some Power BI graphics in which it shows how many fields were fixed from the source and which fields where cleansed. The only thing that I have thought compares the DB table to the flat file source or maybe do something with script components but I don't really think that those are really good solutions.
Has anybody encountered this problem? if somebody could point me out for info for something like this, it would be great. Thanks!
If I am facing a similar issue, I will do this in three steps:
Importing data without any transformation to a staging table
Cleaning data and loading it into the destination table
Comparing staging and destination table to get how many values were fixed.
From design standpoint - establishing a key is central before starting to clean.
Use could use SSIS derived column transformation to create a business key that is a concatenation of available fields to create a unique key, using FindString function and string functions.
Similar to the above step add a column in your staging table or use a derived column (depending on if you are using sql cleanup or ssis tasks to cleanup) to indicate if it was cleaned or not.

Performance issue, flat file vs database storage

I am working on a project that asked me to develop a system to provide JSON output, the following is the flow:
1a) Some tables will be updated via the administration panel (my company side)
1b) Some related tables will be updated via the administration panel (partner side)
-- Let say SuperHeroes & Males were updated in 1a), Studios & Years were updated in 1b)
2) Client browse our site and request an information set which:
Has an enabled and not deleted row in SuperHeroes (Ant-man)
Has an enabled and not deleted row in Males linked to SuperHeroes (Scott Lang)
Joined the above records then look if they are linked to and exists in Studios (Marvel)
Linked to an existing row in Years (2015)
3) A very small data will be outputted to a JSON string as the following: { id:1,type:marvel },{ id:1,type:dc }
All rows in the above 4 tables will be updated/deleted at anytime without notification, [No Foreign Key as well]
I am thinking to update the information in a flat file every time 1a is performed (since we can update the system of my company side but not the partner side, and they are rejected to save some extra information into a flat file, so the situation is we have no easy way to know if the Studios or Years tables are modified)
Then while the JSON request will first load the information from the flat file (all outputting data will be stored in this file), then use a simple SQL statement to filter if a linked record exists in Studios & Years
I have done my research and getting confused, I concluded when the data amount is small then flat file will be great but beware the file comes larger and larger (The flat file we are talking will noway more than 50 rows at 1 time, and that should not be modified frequently)
Some answer said database is good at Query data (I think so and the requirement will perform SQL check too)
So I don't know if its good when my data amounts are small but still need some communication with the database..
I appreciate your time and your help, all idea & hints are welcome, thanks!
Your conclusion regarding amount of data is absolutely correct, and file should handle those 50 rows, but..
Using database as storage should give you more options in the future, e.g.:
you'll be able to produce any output due to separation of data
representation (today it's JSON, but what if you have to produce XML
at some point? will you add files that store XML's next to JSON
files? and then CSV or any other?)
transactions will guarantee the ACID
scalability and performance - if your dataset get bigger (you never know :)), many
DB's offer you many possibilities like table partitioning, partitioning-based clustering
or replication
Wrong choices regarding architecture and technology made at the beginning of the project will always backfire.

ADO - Can I edit results of a complex query with multiple join statements?

I'm working on a data conversion utility which can push data from one master database out to a number of different databases. The utility its self will have no knowledge of how data is kept in the destination (table structure), but I would like to provide writing a SQL statement to return data from the destination using a complex SQL query with multiple join statements. As long as the data is in a standardized format that the utility can recognize (field names) in an ADO query.
What I would like to do is then modify the live data in this ADO Query. However, since there are multiple join statements, I'm not sure if it's possible to do this. I know at least with BDE (I've never used BDE), it was very strict and you had to return all fields (*) and such. ADO I know is more flexible, but I don't know quite how flexible in this case.
Is it supposed to be possible to modify data in a TADOQuery in this manner, when the results include fields from different tables? And even if so, suppose I want to append a new record to the end (TADOQuery.Append). Would it append to two different tables?
The actual primary table I'm selecting from has a complimentary table which is joined by the same primary key field, one is a "Small" table (brief info) and the other is a "Detail" table (more info for each record in Small table). So, a typical statement would include something like this:
select ts.record_uid, ts.SomeField, td.SomeOtherField from table_small ts
join table_detail td on td.record_uid = ts.record_uid
There are also a number of other joins to records in other tables, but I'm not worried about appending to those ones. I'm only worried about appending to the "Small" and "Detail" tables - at the same time.
Is such a thing possible in an ADO Query? I'm willing to tweak and modify the SQL statement in any way necessary to make this possible. I have a bad feeling though that it's not possible.
Compatibility:
SQL Server 2000 through 2008 R2
Delphi XE2
Editing these Fields which have no influence on the joins is usually no problem.
Appending is ... you can limit the Append to one of the Tables by
procedure TForm.ADSBeforePost(DataSet: TDataSet);
begin
inherited;
TCustomADODataSet(DataSet).Properties['Unique Table'].Value := 'table_small';
end;
but without an Requery you won't get much further.
The better way will be setting Values by Procedure e.g. in BeforePost, Requery and Abort.
If your View would be persistent you would be able to use INSTEAD OF Triggers
Jerry,
I encountered the same problem on FireBird, and from experience I can tell you that it can be made(up to a small complexity) by using CachedUpdates . A very good resource is this one - http://podgoretsky.com/ftp/Docs/Delphi/D5/dg/11_cache.html. This article has the answers to all your questions.
I have abandoned the original idea of live ADO query updates, as it has become more complex than I can wrap my head around. The scope of the data push project has changed, and therefore this is no longer an issue for me, however still an interesting subject to know.
The new structure of the application consists of attaching multiple "Field Links" on various fields from the original set of data. Each of these links references the original field name and a SQL Statement which is to be executed when that field is being imported. Multiple field links can be on one single field, therefore can execute multiple statements, placing the value in various tables, etc. The end goal was an app which I can easily and repeatedly export a common dataset from an original source to any outside source with different data structures, without having to recompile the app.
However the concept of cached updates was not appealing to me, simply for the fact pointed out in the link in RBA's answer that data can be changed in the database in the mean-time. So I will instead integrate my own method of customizable data pushes.

Importing CSV to database (duplicate entries)

My job requires that I look up information on a long spreadsheet that's updated and sent to me once or twice a week. Sometimes the newest spreadsheet leaves off information that was in the last spreadsheet causing me to have to look through several different spreadsheets to find the info I need. I recently discovered that I could convert the spreadsheet to a CSV file and then upload it to a database table. With a few lines of script all I have to do is type in what I'm looking for and Voila! Now I just got the newest spreadsheet and I'm wondering if I can just Import it on top of the old one. There is a unique number for each row that I have set to primary in the database. If I try to import it on top of the current info will it just skip the rows where the primary would be duplicated or would it just mess up my database?
Thought I'd ask the experts before I tried it. Thanks for your input!
Details:
the spreadsheet consists of clients of ours. Each row contains the client's name, a unique id number, their address and contact info. I can set the row containing the unique ID to primary, then upload it. My concern is that there is nothing to signify a new row in a csv file (i think). when I upload it it it gives me the option to skip duplicates but will it skip the entire row or just that cell causing my data to be placed in the wrong rows.. It's apache server IDK what versions of mysql. I'm using 000webhost for this.
Higgs,
This issue in database/ETL terminology is called deduplication strategy.
There is not a template answer for this, but I suggest these helpful readings:
Academic paper - Joint Deduplication of Multiple Record Types
in Relational Data
Deduplication article
Some open source tools:
Duke tool
Data cleaner
there's a little checkbox when you click on import near the bottom that says 'ignore duplicates' or something like that. simpler than i thought.

Better way to store updatable scientific data?

I am using a file consisting of published scientific data. I'm using this file with a program that reads in the first 5 space delimited data fields, and everything after that is considered a comment by the program.
2 example lines (of thousands):
FeII 1608.4511 0.521 55.36 -1300 M03 Journal of Physics
FeII 1611.23045 0.0321 55.36 1100 01J AJ
The program reads it as:
FeII 1608.4511 0.521 55.36 -1300
FeII 1611.23045 0.0321 55.36 1100
These numbers are each measurements and most (don't get me started) have associated errors that are not listed in this file. I would like to store this information in a useful and updatable way. That is, say the first entry FeII 1608.4511 has an error of plus/minus 0.002. Consider when a new measurement is made and changes it to: FeII 1608.45034 plus/minus 0.0005. I would like to update the value, the error, and record some information about the publication that it came from.
The program that uses this file is legacy code and is both crucial and inflexible: and it needs the file to look like the above output when it's read in. I would really like for there to be a way to update the input file to include things like errors on the values and publication hyperlinks in comments. I would also like a kind of version control ability to return the state of this large file today; or in 5 months after 20 more lines are updated with new values.
Any suggestions on how best to accomplish this? Should I store everything in some kind of database?
Databases are deeply tied to identity. If a database can't identify a row by the data that's in it, a database isn't going to help you.
If I were you, I'd start by storing the base file in a version control system, not a database. At 20 changes per 5 months, I'd probably make those changes manually and commit each batch of changes. (I don't know what might constitute a batch for you. Could be a single change every time.)
Since the format of the existing file is both crucial and brittle, I'm not sure whether modifying it is a good idea. I think I'd feel better about storing error ranges and publication hyperlinks in a separate file, and using a script to put the pieces together for applications that can use error ranges and hyperlinks.
A database sounds sensible, SQL Server Express is free and widely used.
You can read in the text file including all comments and output the edited data in the same format. You can use a number of front ends including Access, for rapid development, or something you create yourself in VB.Net, or even Excel, at a pinch.
You will need to consider the structure of the table(s) but it should not be too difficult, and you can get help here.
For updating the information in the file introducing errors and links, you don't need any database; just open the file, iterate through the lines and update each one.
If you want to be able to restore a line state, you definetively need some kind of database. You can create a database in Sql Server or Firebird for example, and store in it a row for each line historical state (with date of creation off course); your file itself would be the repository for current values and you would be able to restore the file with a date and some simple fetcing of the database information.
If you can't use a database like Firebird or SQL Server, you can store the historical data in a simple text file, it's up to you. Just remember that you necesarely will need, like #CatCall commented, a way to identify each line in order to create a relation between the line in the file and the historical data stored in your repository.

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