in my case, i have an expression transformation which uses the default function ERROR('transformation') to skip the records in which date value coming inside is not in the correct format. In this, the skipped rows are not written to the reject files, so that we are getting the reconcilation problem. I need the skipped rows to be written to the bad files.Please help me how can i achieve this.
Put the Update Strategy transformation in your mapping and flag these rows for reject (use the DD_REJECT constant).
More information: Update Strategy Transformation
Well, don't use the abort() function then. Use a router to write the bad formated dates to a different target then.
Related
I have a dataset with fields targeted and opens and I need to add calculated field opens per targeted which essentially means doing simple devision of those 2 values.
My calculated field is as follows
{opens}/{targeted}
but then displaying simple table with values they are completely incorrect
If I try any other operator like + * etc calculations are correct.
I'm completely out of ideas on how to debug this. I've simplified the dataset to just columns of targeted and opens, can't get any simpler.
Had the same problem, I fixed it by wrapping the columns with the sum() function. Like this:
sum({opens})/sum({targeted})
I think you need to make AWS understand that you are working with float numbers.
1.0*{opens}/{targeted}
if still not working try also
(1.0*{opens})/({targeted}*1.0)
it should give you the desired output (not tested, let me know if it doesnt work)
I have a transformation with several steps that run by batch script using Windows Task Scheduler.
Sometimes the first step or the n steps fail and it stops the entire transformation.
I want to transformation to run from start to end regardless of any errors, any way of doing this?
1)One way is to “error handling”, however it is not available for all the steps. You can right click on the step and check whether error handling option is available or not.
2) if you are getting errors because of incorrect datatype, for example: you are expecting a integer value and for some specific record you may get string value so it may fail , for handling such situation you can use data validation step.
Basically you can implement logic based on the transformation you have created. Above are some of the General methods.
This is what you called "Error Handling". Though your transformation runs with some Errors, you still want your transformation to continue to run.
Situations:
- Data type issues in the data stream.
Ex: say you have a column X of data type integer but by mistake you got string value. then you can define Error handling to capture all these records.
- while Processing json data.
Ex: the path you mentioned to retrieve a value of json field and for some data node the path can't identify or missing it. you can define error handling to capture all missing path details.
- while Update table
- If you are updating a table with some key, and if the key was not available as it is coming from input stream then an error will occur. you can define error handling here also.
I'm trying to create a transformation read csv files and check data types for each field in that csv.
Like this : the standard field A should string(1) character and field B is integer/number.
And what I want is to check/validate: If A not string(1) then set Status = Not Valid also if B not a integer/number to. Then all file with status Not Valid will be moved to error folder.
I know I can use Data Validator to do it, but how to move the file with that status? I can't find any step to do it.
You can read files in loop, and
add step as below,
after data validation, you can filter rows with the negative result(not matched) -> add constant values step and with error = 1 -> add set variable step for error field with default values 0.
after transformation finishes, you can do add simple evaluation step in parent job to check value of ERROR variable.
If it has value 1 then move files else ....
I hope this can help.
You can do same as in this question. Once read use the Group by to have one flag per file. However, this time you cannot do it in one transform, you should use a job.
Your use case is in the samples that was shipped with your PDI distribution. The sample is in the folder your-PDI/samples/jobs/run_all. Open the Run all sample transformations.kjb and replace the Filter 2 of the Get Files - Get all transformations.ktr by your logic which includes a Group by to have one status per file and not one status per row.
In case you wonder why you need such a complex logic for such a task, remember that the PDI starts all the steps of a transformation at the same time. That's its great power, but you do not know if you have to move the file before every row has been processed.
Alternatively, you have the quick and dirty solution of your similar question. Change the filter row by a type check, and the final Synchronize after merge by a Process File/Move
And a final advice: instead of checking the type with a Data validator, which is a good solution in itself, you may use a Javascript like
there. It is more flexible if you need maintenance on the long run.
After going through the documentations of Utplsql 3.0.2 , I couldn't find any references the assertion api as available in the older versions. Please let me know whether is there a equivalent assertion like utassert.eqtable available in newer versions.
I have just recently gone through the same pain. Most utPLSQL examples out there are for utPLSQL v2. It transpires appears that the assertions have been deprecated, and have been replaced by "Expects". I found a great blog post by Jacek Gebal that describes this. I've tried to put this and other useful links a page about how unit testing fits into Redgate's Oracle DevOps pipeline (I work for Redgate and we often get asked how to best implement automated unit testing for Oracle).
I don't think you can compare tables straight away, but you can compare cursors, which is quite flexible, because you can, for instance, set-up a cursor with test data based on a dual query, and then check that against the actual data in the table, something like this:
procedure TestCursorExample is
v_Expected sys_refcursor;
v_Actual sys_refcursor;
begin
-- Arrange (Nothing really to arrange, except setting the expectation).
open v_Expected for
select 'me#example.com' as Email
from dual;
-- Act
SomeUpsertProc('me', 'me#example.com');
-- Assert
open v_Actual for
select Email
from Tbl_User
where UserName = 'me';
ut.expect(v_Actual).to_equal(v_Expected);
end;
Also, the example above works in Oracle 11, but if you're in 12c, apparently things got even easier, because you can use the table operator with locally defined types.
I've used a similar solution to verify that certain columns of a row were updated, while others were not. You can easily open a cursor for the original data, with some columns replaces by the new fixed values. Then do the update. Then open a cursor with the new actual data of all columns. You still have to write the queries, but it's way more compact than querying everything into variables and comparing those individually.
And, because you can open the 'expected' cursor before doing the actual 'act' step of the test, you can be sure that the query with 'expected' data is not affected by the test itself, and can even base that cursor on the data you are going to modify.
For comparing the data, the cursors are serialized to XML. This may have some side effects. In the test example above, my act step didn't actually do anything, so I got this difference, showing the count as well as showing the missing data.
If your cursors have more columns, and multiple difference, it can sometimes take a seconds to spot the differences between the XML tags. Also, there are currently some edge-case issues with this, I think because of how trimming works in XML.
1) testcursorexample
Actual: refcursor [ count = 0 ] was expected to equal: refcursor [ count = 1 ]
Diff:
Rows: [ 1 differences ]
Row No. 1 - Missing: <EMAIL>me#example.com</EMAIL>
at "MySchema.MyTestPackage", line 410 ut.expect(v_Actual).to_equal(v_Expected);
See also: 'comparing cursors' from utPLSQL 3 concepts
When we fire a SQL query like
SELECT * FROM SOME_TABLE_NAME under ORACLE
What exactly happens internally? Is there any parser at work? Is it in C/C++ ?
Can any body please explain ?
Thanks in advance to all.
Short answer is yes, of course there is a parser module inside Oracle that interprets the statement text. My understanding is that the bulk of Oracle's source code is in C.
For general reference:
Any SQL statement potentially goes through three steps when Oracle is asked to execute it. Often, control is returned to the client between each of these steps, although the details can depend on the specific client being used and the manner in which calls are made.
(1) Parse -- I believe the first action is actually to check whether Oracle has a cached copy of the exact statement text. If so, it can save the work of parsing your statement again. If not, it must of course parse the text, then determine an execution plan that Oracle thinks is optimal for the statement. So conceptually at least there are two entities at work in this phase -- the parser and the optimizer.
(2) Execute -- For a SELECT statement this step would generally run just enough of the execution plan to be ready to return some rows to the client. Depending on the details of the plan, that might mean running the whole thing, or might mean doing just a very small fraction of the work. For any other kind of statement, the execute phase is when all of the work is actually done.
(3) Fetch -- This is when rows are actually returned to the client. Generally the client has a predetermined fetch array size which sets the maximum number of rows that will be returned by a single fetch call. So there may be many fetches made for a single statement. Of course if the statement is one that cannot return rows, then there is no fetch step necessary.
Manasi,
I think internally Oracle would have its own parser, which does parsing and tries compiling the query. Think its not related to C or C++.
But need to confirm.
-Justin Samuel.