Does anyone know how do the options 'Copy data from one or more tables or view' and 'Write a query to specify the data to transfer' in Import & Export Wizard function differently?
During testing, I tried using both options to transfer a table from a source to destination but I am getting different datatypes mapping.
For 'Copy data from one or more tables or view' option, all the datatypes mapping are correct. However, if I use 'Write a query to specify the data to transfer' option, some dataypes would appear as numbers instead of its appropriate datatype. Eg: Under type column, it shows 1 instead of Char.
I think I can rule out Mapping files as the cause because I would be getting the same error for both options if that's the case. What I would like to ask is if anyone knows whether the query is being parsed differently with those options? If so, how is it different?
Any advice is appreciated. Thanks for your help.
Related
I've got two tables (8/~150 columns). The first one gets filled with personal data, while the second one is a "checklist" which is filled with one character.
I created a query, which concatenates both tables, to export it as a .csv file. When I try to do so (with the export wizard) I get this exception:
The Microsoft Access database engine could not find the object 'filename.csv'. Make sure the object exists and that you spell its name and the path correctly.
I double checked, tried to do it with VBA, but nothing worked.
I don't know what I should try to do.
I'm hoping that someone can help me
Paul
I have to import a CSV file into MySQL table. The file and the table have the same structure (columns and types of values). The import should happen with following algo:
read a line from the file,
compare values from column X (file) with column X (db table),
import line, if the value in the file is higher, than the value in the db table.
The question is, slightly off-topic: how is it possible to automate this kind of import? Are there tools doing such? Or is PhpMyAdmin enough - create temporal table, put the file into it, compare and import?
For everybody, who is looking for same or similar solutions:
The tool, which helps to accomplish such tasks, is calles webyog (no link - its not an advertising, search for it),
The tool has possibility to specify SQL query, which will rule the import.
An answer about this solutions is provided by the tool's support - should work as expected. For me, it will be the accepted solution.
Actually i need Your help in datastage 11.7 tool. i am reading a AES encrypted column from my source and type of column is nvarchar so when we start our job and read data from source. The job run Successfully and exactly same data is moved to my target data base with same column type.
And the Problem Actually occur is that when i query the data to check whether the my source and target values are same, the query does not show any result and visually if we look source,target value they are same value but sql statement return nothing and the database is Vertica.
Column value are special Alpha numeric and special characters like �D�&7��x��d$�Q
I'm not at all sure this is even properly possible via datastage - treated encrypted data and a varchar. Some DB's have internal keys that go with the data that require decrypting before extracting. I'm assuming that decrypting, transporting, landing and then encrypting is not an option.
But if I had to take a stab in the dark.
The very first thing I'd check is that the character set and collation is the same on both databases on a table level. A difference can result in blank results on the target side.
Also check that the NLS map in the datastage (map for stages and collation locale) is set accordingly. What that settings is, I don't know but making it the same in DataSTage and the DBs would be ideal ; Google. You need to comment on what is already set in the DB's. And run tests. I'm not sure the DataStage default of ISO-8859-1 will work.
Please post your solution if you find one.
I've been searching for a quick way to do this after my first few thoughts have failed me, but I haven't found anything.
My Issue
I'm importing raw client data into an Access database where the flat file they provide is parsed and converted into a standardized format for our organization. I do this for all of our clients, but this particular client's software gives us a file that puts "(NULL)" in every field that should be NULL. lol as a result, I have a ton of strings rather than a null field!
My goal is to do a data cleanse of the entire TABLE, rather than perform the cleanse at the FIELD level (as I do in my temporary solution below).
Data Cleanse
Temporary Solution:
I can't add those strings to our datawarehouse, so for now, I just have a query with an IIF statement check that replaces "(NULL)" with "" for each field (which took awhile to setup since the client file has roughly 96 fields). This works. However, we work with hundreds of clients, so I'd like to make a scale-able solution that doesn't require many changes if another client has a similar file; not to mention that if this client changes something in their file, I might have to redo my field specific statements.
Long-term Solution:
My first thought was an UPDATE query. I was hoping I could do something like:
UPDATE [ImportedRaw_T]
SET [ImportedRaw_T].* = ""
WHERE ((([ImportedRaw_T].* = "(NULL)"));
This would be easily scale-able, since for further clients I'd only need to change the table name and replace "(NULL)" with their particular default. Unfortunately, you can't use SELECT * with an update query.
Can anyone think of a work-around to the SELECT * issue for the update query, or have a better solution for cleansing an entire table, rather doing the cleanse at the field level?
SIDE NOTES
This conversion is 100% automated currently (Access is called via a watch folder batch), so anything requiring manual data manipulation / human intervention is out.
I've tried using a batch script to just cleanse the data in the .txt file before importing to Access - however, this caused an issue with the fixed-width format of the .txt, which has caused even larger issues with the automatic import of the file to Access. So I'd prefer to do this in Access if possible.
Any thoughts and suggestions are greatly appreciated. Thanks!
Unfortunately it's impossible to implement this in SQL using wildcards instead of column names, there is no such kind syntax.
I would suggest VBA solution, where you need to cycle thru all table fields and if field data type is string, generate and execute SQL UPDATE command for updating current field.
Also use Null instead of "", if you really need Nulls in the field instead of empty strings, they may work differently in calculations.
I have a simple DataFlow with two objects the source which is a mdb file and the destination which is an MSSQL database.
The idea is to migrate the data from one to another.
The problem is that the data is extracted from an Access query, and one column has ~1000 characters, and in SSIS in advanced properties the external column has the default 255 length so when i execute the task it tries to truncate it. To disable the throw error on truncate is not an option, and modifying the Length of the external column cannot be done, it throws and error regarding the metadata.
First of all can anyone explain WHY?
Second of all i need a resolution and i need it fast because it's kinda driving me crazy.
This kind of problem occours, because the ssis task "guesses" the length of the column by inspecting the first 100(afaik) rows. So if all rows from 1 to 100 have a length of 10 and the row 101 has the legnth of 11, the task will fail, because the length was "guessed" to 10.
Modifying throws an error, because you have validateExternalMetadata set to true. To solve this problem, go to advanced options of your import task (access) and set the value to false.
This means, the task will accept modified values you entered without checking it.
Did you try to SSIS Import and Export Wizard to import the data, from within the BI development environment? That is the easiest way with MsAccess as this not only imports the data but also saves the package. If you get an error during the import ( using the wizard), please post it, as this helps in further investigation. Also, as #stb suggested, try having the first record over 1000 characters.
Access supports queries which are the equivalent to views in MSSQL.
The column size is defined not by looking at a few results but by the default column length of the column data type.
I created another table with the desired data types and before the data flow i've put in the package 2 sql scripts: one to delete all the data in the table and one to execute the query against the table, as to treat it as a temporary table.
Then the actual data flow is executed against this pseudo-temporary table.
This solved my problem.