If the data is in 1 machine then there's probably no need to move the data.
So the question is more:
* Do you need more than one machine to do your ETL?
* Would you ever need more than one machine?
So if you need more than 1 machine then chukwa could be the right answer.
I have a tool that I could publish to transform any input file to Chukwa compressed dataSink file. This could be a first step.
Also hadoop has a JDBC InputReader/Writer so you may want to take a look.
Could you give more info on your data(size and ETL)?
On 8/24/10 12:39 PM, "hdev ml" <[EMAIL PROTECTED]> wrote:
This question is related partly to hadoop and partly to chukwa.
We have huge number of logged information sitting in one machine. I am not sure whether the storage is in multiple files or in a database.
But what we want to do is get that log information, transform it and store it into the some database for data mining/ data warehousing/ reporting purposes.
1. Since it is on one machine, is Chukwa the right kind of frame work to do this ETL process?
2. I understand that generally Hadoop works on large files. But assuming that the data sits in a database, what if we somehow partition data for Hadoop/Chukwa? Is that the right strategy?
Any help will be appreciated.