I have a question about what "near real-time" means exactly, in a quantified way, when described this way on the ES-hadoop home page:
We are happy to report that es-hadoop is being used in multiple > data-intensive environments; in a recent example, a large financial > institute that stores all of their raw access logs in Hadoop – billions of > documents – has been using es-hadoop to index the data into Elasticsearch > and then visualize it using Kibana. This approach allowed the customer to > have near real-time visibility into their data through Kibana (http://www.elasticsearch.org/blog/es-hadoop-2-0-g/) I've been burned in the past by people throwing around the term "real-time" in sloppy ways when what they really meant was update lag of many minutes. (Coming from the hardware world we have a different way of using the term "real-time" =D) I'm not saying that's the case here, I'm just asking for numerical clarification. Naturally I assume it depends on the volume of data flow, the server equipment, and the configuratinon settings. I've done about half an hour of general searching without any definitive answers. Hopefully someone either knows or can point me to a good resource. -- Pierre -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/6f40a541-19b6-4a86-b02c-b07b1e3b17b3%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
