Hey Drew, This could be a very broad question, so I'll give a partial answer and encourage you to come back for more details.
Impala is a mechanism that sits on top of HBase or HDFS that is design to filter and process large quantities of data. People generally like Impala because it supports a subset of SQL and because it is optimized to reduce the latency that might be incurred by starting up a job in a bulk synchronous processing framework. Instead, it uses a series of daemon processes and a custom API to reduce overhead. With Accumulo, our approach to low-latency queries is generally to use a table structure that incorporates some type of index. With appropriate indexing techniques, Accumulo can achieve sub-second query latencies even over multi-petabyte sized corpuses. Some of these table designs are described in the manual: http://accumulo.apache.org/1.4/user_manual/Table_Design.html Regarding the SQL piece, Accumulo does not natively support an SQL interface. For that you would need to wrap it in a processing framework, like Hive (https://issues.apache.org/jira/browse/ACCUMULO-143). To make a shameless plug, Sqrrl (www.sqrrl.com) also offers that functionality. Cheers, Adam On Fri, May 3, 2013 at 12:39 PM, Drew Pierce <drewpie...@live.com> wrote: > does anyone have any anecdotal results (nothing formal) for queries to > speak to the likes of impala and near low-latency. > Sent from my Android > > Sorry if brief > >
