If we collect blocks to one table during blocking_mapred(), locality will be provided and more faster.
row Key column:A column:B c(0, 0) += a(0, 0) * b(0, 0) c(0, 0) += a(0, 1) * b(1, 0) c(0, 0) += a(0, 2) * b(2, 0) c(0, 0) += a(0, 3) * b(3, 0) c(0, 1) += a(0, 0) * b(0, 1) c(0, 1) += a(0, 1) * b(1, 1) ... What do you think? On Mon, Jan 5, 2009 at 10:30 AM, Edward J. Yoon <[email protected]> wrote: > Hama Trunk doesn't work for large matrices multiplication with > mapred.task.timeout and scanner.timeout exception. I tried 1,000,000 * > 1,000,000 matrix multiplication on 100 node. (Rests are good) > > To reduce read operation of duplicated block, I thought as describe > below. But, each map processing seems too large. > > ---- > // c[i][k] += a[i][j] * b[j][k]; > > map() { > SubMatrix a = value.get(); > > for (RowResult row : scan) { > collect : c[i][k] = a * b[j][k]; > } > } > > reduce() { > c[i][k] += c[i][k]; > } > ---- > > Should we increase {mapred.task.timeout and scanner.timeout}? > or any good idea? > > -- > Best Regards, Edward J. Yoon @ NHN, corp. > [email protected] > http://blog.udanax.org > -- Best Regards, Edward J. Yoon @ NHN, corp. [email protected] http://blog.udanax.org
