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On Error Messages

Here’s a pet peeve of mine: Customers who don’t read the error messages. The usual symptom is a belief that there is just on error: “Doesn’t work”, and that all forms of “doesn’t work” are the same. So if you tried something, got an error, your changed something and you are still getting an error, nothing changed.

I hope everyone who reads this blog understand why this behavior makes any troubleshooting nearly impossible. So I won’t bother to explain why I find this so annoying and so self defeating. Instead, I’ll explain what can we, as developers, can do to improve the situation a bit. (OMG, did I just refer to myself as a developer? I do write code that is then used by customers, so I may as well take responsibility for it)

Here’s what I see as main reasons people don’t read error messages:

Kafka or Flume?

A question that keeps popping up is “Should we use Kafka or Flume to load data to Hadoop clusters?”

This question implies that Kafka and Flume are interchangeable components. It makes as much sense to me as “Should we use cars or umbrellas?”. Sure, you can hide from the rain in your car and you can use your umbrella when moving from place to place. But in general, these are different tools intended for different use-cases.

Flume’s main use-case is to ingest data into Hadoop. It is tightly integrated with Hadoop’s monitoring system, file system, file formats, and utilities such a Morphlines. A lot of the Flume development effort goes into maintaining compatibility with Hadoop. Sure, Flume’s design of sources, sinks and channels mean that it can be used to move data between other systems flexibly, but the important feature is its Hadoop integration.

Beginnings

“A beginning is the time for taking the most delicate care that the balances are correct.”

It is spring. Time for planting new seeds. I started on a new job last week, and it seems that few of my friends and former colleagues are on their way to new adventures as well. I’m especially excited because I’m starting not just a new job – I will be working on a new product, far younger than Oracle and even MySQL. I am also making first tiny steps in the open-source community, something I’ve been looking to do for a while.

I’m itching to share lessons I’ve learned in my previous job, three challenging and rewarding years as a consultant. The time will arrive for those, but now is the time to share what I know about starting new jobs. Lessons that I need to recall, and that my friends who are also in the process of starting a new job may want to hear.

Environment Variables in Grid Control User Defined Metrics

This post originally appeared at the Pythian blog.

Emerson wrote: “Foolish consistency is the hobgoblin of small minds”. I love this quote, because it allows me to announce a presentation titled “7 Sins of Concurrency” and then show up with only 5. There are places where consistency is indeed foolish, while other times I wish for more consistency.

Here is a nice story that illustrates both types of consistency, or lack of.

This customer Grid Control installed in their environment. We were asked to configure all kinds of metrics and monitors for several databases, and we decided to use the Grid Control for this. One of the things we decided to monitor is the success of the backup jobs.