#YOU'RE REALLY DOING IT WRONG SOFTWARE#
It’s too huge a topic to go into here, but our advice is to learn how your source control system works – Git is a fantastic bit of software once you know what it can do, and come up with a workable policy for versioning projects sources and artefacts. Without versioning, you’ll miss out on being able to clearly track changes across common artefacts, struggle to trace back through the history of part of a project, and maybe get into a pickle when rolling back deployed code.
#YOU'RE REALLY DOING IT WRONG CODE#
Talend, Git (and SVN) and Nexus all provide great methods to control, increment, freeze and roll back versions of code – so why don’t people use them! Too often we encounter a Talend project that uses just a single, master branch in source control, has all the jobs and metadata still on version 0.1 in Studio, and no clear policy on deployment to Nexus. You can pick out the line number of the first error in the list (sometimes it’s not the first, but it’ll be near the top), switch to the job’s code view and go to that line (ctrl-L).Įven if the resulting splodge of Java code doesn’t mean much, Eclipse (the technology that Talend Studio is built on) will helpfully point out where the problem is, and in the case of a tMap it’s then clear which mapping or variable is at fault. If you’ve worked with Talend for a while, or if you have Java experience, you will recognise the stack trace, the nested list of exceptions that are bubbled up through the job as it falls over. Inexperienced Talend engineers will often spend hours picking apart a job to find the source of this kind of bug, when a faster method is available.
“I’m not a coder, so I’m not looking at the code”Įver seen a NullPointerException? If you’re a Talend engineer, then of course you have! However, this kind of run-time error can be tricky to pin down, especially if it lives in the heart of a busy tMap. We have found that you can get the best from joblets when treating them as the equivalent of pure functions, limiting their score to only the inputs and outputs defined by the joblet’s connections and variables. This usage will require additional complexities when reusing joblets across different jobs and contexts, and can lead to unexpected side effects and uncertain testability. However, problems can arise when joblets are given tasks that operate outside the scope of the code itself, such as reading and writing files, databases, etc. Joblets are great! They provide a simple way to encapsulate standard routines and reuse code across jobs, whilst maintaining some transparency into their inner workings. Joblets that take on too much responsibility Our best advice is to break down big jobs into smaller, more manageable (and testable) units, which can then be combined together using your favourite orchestration technique.ĩ. This is a fundamental limitation of Java that limits the size of a method’s code, and Talend generates a method for each sub-job. Whilst it is often convenient to contain all similar logic and data in a single job, you can soon run into problems when building or deploying a huge job, not to mention trying to debug a niggling nasty in the midst of all those tMaps!Īlso, big jobs often contain big sub-jobs (those blue-shaded blocks that flows form into), and you will eventually come up against a Java error telling you some code is “exceeding the 65535 bytes limit”. Kicking off our list is a common problem – the size of individual Talend jobs. We’ve asked our team of Talend experts to compile this top ten list of their biggest bugbears when it comes to jobs they see in the wild – and here it is! 10.