You can use custom mapper and reducer scripts using TRANSFORM/MAP/REDUCE facilities. Check the wiki on how to use them. Or do you want something different?
________________________________ From: Min Zhou <coderp...@gmail.com> Reply-To: <hive-user@hadoop.apache.org> Date: Sun, 22 Feb 2009 19:42:50 -0800 To: <hive-user@hadoop.apache.org> Subject: How to simplify our development flow under the means of using Hive? Hi list, I'm goint to take Hive into production to analyze our web logs, which are hundreds of giga-bytes per day. Previously, we did this job by using Apache hadoop, running our raw mapreduce code. It did work, but it also decreased our productivity directly. We were suffering from writting code with similar logic again and again. It could be worse, when the format of our logs being changed. For example, when we want to insert one more field in each line of the log, the previous work would be useless, then we have to redo it. Hence we are thinking about using Hive as a persistent layer, to store and retrieve the schemes of the data easily. But we found that sometimes Hive could not do some sort of complex analysis, because of the limitation of the ideographic ability of SQL. We have to write our own UDFs, even though, some difficulties Hive still cannot go through. Thus we also need to write raw mapreduces code, which let us come up against another problem. Since one is a set of SQL scripts, the other is pieces of java or hybrid code, How to coordinate Hive and raw mapreduce code and how to shedule them? How does Facebook use Hive? And what is your solution when you come across the similar problems? In the end, we are considering about using Hive as our data warehouse. Any suggestions? Thanks in advance! Min -- My research interests are distributed systems, parallel computing and bytecode based virtual machine. http://coderplay.javaeye.com