I've an SSIS package which has source as a Oracle view.
Select * From VwWrkf
When I execute it , I get only 3rd of the data. There is about 1.5mil rows. But there is about 450K that Tabular loads.
Any reason why thay could be?
Use fast load at destination OLEDB task which clears buffer faster and allow all records to process. May be as the buffer getting filled and the records not processed it might not getting the rest of records and might be the connection timedout.
The issue was the date format of a particular section of the report. It did something which Microsoft did not like.
Related document could be found here
It is nothing about "SSIS does not pull the whole source data rows".
If you preview the table data ,it shows only sample data right?.Likewise in the case with
select count(*) as well.If you can run the data flow,it would pick all the data form the source and will be loading it into target table.
If you still doubt,Instead of checking the ssis preview ,can you/is it possible to load data into a destination temp table,and check whether all the data being loaded into destination temp table
Related
I am loading a csv file into my database using SQL Loader. My requirement is to create an error file combining the error records from .bad file and their individual errors from the log file. Meaning if a record has failed because the date is invalid, against that record in a separate column of error description , Invalid date should be written. Is there any way that SQL loader provides to combine the too. I am a newbie to SQL loader.
Database being used Oracle 19.c
You might be expecting a little bit too much of SQL*Loader.
How about switching to external table? In the background, it still uses SQL*Loader, but source data (which resides in a CSV file) is accessible to you by the means of a table.
What does it mean to you? You'd write some (PL/)SQL code to fetch data from it. Therefore, if you wrote a stored procedure, there are numerous options you can use - perform various validations, store valid data into one table and invalid data into another, decide what to do with invalid values (discard? Modify to something else? ...), handle exceptions - basically, everything PL/SQL offers.
Note that this option (generally speaking) requires the file to reside on the database server, in a directory which is a target of Oracle directory object. User which will be manipulating CSV data (i.e. the external table) will have to acquire privileges on that directory from the owner - SYS user.
SQL*Loader, on the other hand, runs on a local PC so you don't have to have access to the server itself but - as I said - doesn't provide that much flexibility.
it is hard to give you a code answer without the example.
If you want to do your task I can suggest two ways.
From Linux.
If you loaded data and skipped the errors, you must do two executions.
That is not an easy way and not effective.
From Oracle.
Create a table with VARCHAR2 columns with the same length as in the original.
Load data from bad_file. Convert your CTL adapted to everything. And try to load in
the second table.
Finally MERGE the columns to original.
I have a requirement in the project I am currently working on to compare the most recent version of a record with the previous historical record to detect changes.
I am using the Azure Offline data sync framework to transfer data from a client device to the server which causes records in the synced table to update based on user changes. I then have a trigger copying each update into a history table and a SQL query which runs when building a list of changes to compare the current record vs the most recent historical by doing column comparisons - mainly string but some integer and date values.
Is this the most efficient way of achieving this? Would it be quicker to load the data into memory and perform a code based comparison with rules?
Also, if I continually store all the historical data in a SQL table, will this affect the performance over time and would I be better storing this data in something like Azure Table Storage? I am also thinking along the lines of cost as SQL usage is much more expensive that Table Storage but obviously I cannot use a trigger and would need to insert each synced row into Table Storage manually.
You could avoid querying and comparing the historical data altogether, because the most recent version is already in the main table (and if it's not, it will certainly be new/changed data).
Consider a main table with 50.000 records and 1.000.000 records of historical data (and growing every day).
Instead of updating the main table directly and then querying the 1.000.000 records (and extracting the most recent record), you could query the smaller main table for that one record (probably an ID), compare the fields, and only if there is a change (or no data yet) update those fields and add the record to the historical data (or use a trigger / stored procedure for that).
That way you don't even need a database (probably containing multiple indexes) for the historical data, you could even store it in a flat file if you wanted, depending on what you want to do with that data.
The sync framework I am using deals with the actual data changes, so i only get new history records when there is an actual change. Given a batch of updates to a number of records, i need to compare all the changes with their previous state and produce an output list of whats changed.
I'm importing data from a text file using Bulk Insert in the script component in SSIS package.
Package Ran successfully and data imported into SQL
Now how do I validate the completeness of the data?
1. I can get the row count from source and destination and compare.
but my manager wants to know how we can verify all the data has come a cross as it is without any issues.
If we are comparing 2 tables then probably a joining them on all fields and see anything missing out.
I’m not sure how to compare a text file and a sql table.
One way I could is write code to ready the file line by line and query the database for that record and compare each and every field. We have millions of records so this is not going to be a simple task.
Any other way to validate all of the data ??
Any suggestions would be much appreciated
Thanks
Ned
Well you could take the same file and do a look-up to the SQL source and if any of the columns don't match move to a row count.
Here's a generic example of how you can do this.
We have a TDBGrid that connected to TClientDataSet via TDataSetProvider in Delphi 7 with Oracle database.
It goes fine to show content of small tables, but the program hangs when you try to open a table with many rows (for ex 2 million rows) because TClientDataSet tries to load the whole table in memory.
I tried to set "FetchOnDemand" to True for our TClientDataSet and "poFetchDetailsOnDemand" to True in Options for TDataSetProvider, but it does not help to solve the problem. Any ides?
Update:
My solution is:
TClientDataSet.FetchOnDemand = T
TDataSetProvider.Options.poFetchDetailsOnDemand = T
TClientDataSet.PacketRecords = 500
I succeeded to solve the problem by setting the "PacketRecords" property for TCustomClientDataSet. This property indicates the number or type of records in a single data packet. PacketRecords is automatically set to -1, meaning that a single packet should contain all records in the dataset, but I changed it to 500 rows.
When working with RDBMS, and especially with large datasets, trying to access a whole table is exactly what you shouldn't do. That's a typical newbie mistake, or a borrowing from old file based small database engines.
When working with RDBMS, you should load the rows you're interested in only, display/modify/update/insert, and send back changes to the database. That means a SELECT with a proper WHERE clause and also an ORDER BY - remember row ordering is never assured when you issue a SELECT without an OREDER BY, a database engine is free to retrieve rows in the order it sees fit for a given query.
If you have to perform bulk changes, you need to do them in SQL and have them processed on the server, not load a whole table client side, modify it, and send changes row by row to the database.
Loading large datasets client side may fali for several reasons, lack of memory (especially 32 bit applications), memory fragmentation, etc. etc., you will flood the network probably with data you don't need, force the database to perform a full scan, maybe flloding the database cache as well, and so on.
Thereby client datasets are not designed to handle millions of billions of rows. They are designed to cache the rows you need client side, and then apply changes to the remote data. You need to change your application logic.
I am trying to load a large amount of data into my Oracle database, and until now i have been using normal insert statements, but over time the number of rows to insert is increased to over 15mil and it takes to long time.
I have been looking at SQL*loader to bulk load, but have not been able to find out if they support User Defined Types.
So the bottom line of my question is, is it possible to load UDT in SQL*loader and if, how?
The data i load comes from a script so I'm able to transform if before exporting to data files, if there is a need for that!
It's possible to use SQL*Loader for loading User Defined Object Types. See these docs for it.
http://docs.oracle.com/cd/E11882_01/server.112/e22490/ldr_concepts.htm#i1005027
http://docs.oracle.com/cd/E11882_01/server.112/e22490/ldr_loading.htm#i1006457
http://docs.oracle.com/cd/E11882_01/server.112/e22490/ldr_loading.htm#i1009398