Why not run a map reduce job on the data in hdfs? what is was made for. On May 29, 2015 2:13 PM, "Zach Cox" <zcox...@gmail.com> wrote:
> Hi - > > Let's say one day a company wants to start doing all of this awesome data > integration/near-real-time stream processing stuff, so they start sending > their user activity events (e.g. pageviews, ad impressions, etc) to Kafka. > Then they hook up Camus to copy new events from Kafka to HDFS every hour. > They use the default Kafka log retention period of 7 days. So after a few > months, Kafka has the last 7 days of events, and HDFS has all events except > the newest events not yet transferred by Camus. > > Then the company wants to build out a system that uses Samza to process the > user activity events from Kafka and output it to some queryable data store. > If standard Samza reprocessing [1] is used, then only the last 7 days of > events in Kafka get processed and put into the data store. Of course, then > all future events also seamlessly get processed by the Samza jobs and put > into the data store, which is awesome. > > But let's say this company needs all of the historical events to be > processed by Samza and put into the data store (i.e. the events older than > 7 days that are in HDFS but no longer in Kafka). It's a Business Critical > thing and absolutely must happen. How should this company achieve this? > > I'm sure there are many potential solutions to this problem, but has anyone > actually done this? What approach did you take? > > Any experiences or thoughts would be hugely appreciated. > > Thanks, > Zach > > [1] http://samza.apache.org/learn/documentation/0.9/jobs/reprocessing.html >
