DSXchange

That is not an error message, that is a command.

As Craig already pointed out, 80-90% utilization is great. It also means that your job is probably bottlenecked on CPU so if you wanted to make it run faster you would need to see if you could reduce computations. Any job will get as much system resources until it maxes out the system on CPU, I/O or...

What is your parameter datatype, it seems as if the parameter contents are not valid for the type of parameter

The substrings function is used for multivalue strings, you should use just the normal substring function.

If you add a constraint "1=2" to your job does it still abort? Does it abort at the same row number every time? If you drop a few columns from the source and don't write anything to the output, does it still fail and does it fail in the same place? Basically the goal is to make simple changes to the...

Jobs aborting
Crash dumps sigh
Director missing

The UNIX command you are looking for is mkdbfile ; you can always call that from a job or sequence using either the DS/BASIC "EXECUTE" command or the DSExecute function The command will not create a VOC entry for the file, and in order to create the DICTionary file you will have to call it again wit...

I don't quite understand what you've done, but it would help if you documented what failed with what message.

To get the last 3 lines do something like MessagesString = DSGetLogSummary (JobHandle, DSJ.LOGWARNING,StartTimestamp ,EndTimestamp,0) MessageCount = DCOUNT(MessagesString,@FM) Last3 = CONVERT(@FM,CHAR(10),MessagesString<MessageCount-2,3) Alternatively the last command might read Last3 = CONVERT(@FM,...

I would help all of us if you told us what error you are getting.

Your error is on the view data of DB2, not the sequential file, right? ... >**** Parallel startup failed **** > >This is usually due to a configuration error, such as >not having the Orchestrate install directory properly >mounted on all nodes, rsh permissions not correctly >set (via /etc/hosts.equi...

You have one stage var that checks to see if your group column has changed or not, and another that sums the current group values. Then have an output constraint on your goup change stage variable and output the sum when that group has changed.

Yes, you should use "Entire" partitioning in this case as well.

The "keys" on a stage are different and independent of your hashing algorithm; what matters is that both streams are partitioned with the same method and columns.

I might as well ask first, before someone else does : why not use the aggregator stage to do this? You can use stage variables in a transform stage to do this, checking for a group change in the column you are using as a key and totalling your value column until the group change, then outputting tha...

Use the same partitioning methods for the join, use "entire" for the reference unless you are certain of your lookup partitioning (usually that is highly unlikely to be the case, so most of the time the "entire" method needs to be used)