Hi , Since you are saying billions of rows, why don't you try out the MapReduce route to speed up the process. You can take a look at how IndexTool.java( https://github.com/apache/phoenix/blob/359c255ba6c67d01a810d203825264907f580735/phoenix-core/src/main/java/org/apache/phoenix/mapreduce/index/IndexTool.java) was written as it does a similar task of reading from a Phoenix table and writes the data into the target table using bulk load.
Regards Ravi On Wed, Jul 22, 2015 at 6:23 AM, Riesland, Zack <[email protected]> wrote: > I want to play with some options for splitting a table to test > performance. > > > > If I were to create a new table and perform an upsert select * to the > table, with billions of rows in the source table, is that like an overnight > operation or should it be pretty quick? > > > > For reference, we have 6 (beefy) region servers in our cluster. > > > > Thanks! > > >
