private void flushSolver() throws IOException { UpperTriangular r = qSolver.getRTilde(); double[][] qt = qSolver.getThinQtTilde(); rSubseq.add(r); value.setBlock(qt); getTempQw().append(tempKey, value); /* * this probably should be a sparse row matrix, but compressor should get it * for disk and in memory we want it dense anyway, sparse random * implementations would be a mostly a memory management disaster consisting * of rehashes and GC // thrashing. (IMHO) */ value.setBlock(null); qSolver.reset(); }
private void flushSolver() throws IOException { UpperTriangular r = qSolver.getRTilde(); double[][] qt = qSolver.getThinQtTilde(); rSubseq.add(r); value.setBlock(qt); getTempQw().append(tempKey, value); /* * this probably should be a sparse row matrix, but compressor should get it * for disk and in memory we want it dense anyway, sparse random * implementations would be a mostly a memory management disaster consisting * of rehashes and GC // thrashing. (IMHO) */ value.setBlock(null); qSolver.reset(); }
private void flushSolver() throws IOException { UpperTriangular r = qSolver.getRTilde(); double[][] qt = qSolver.getThinQtTilde(); rSubseq.add(r); value.setBlock(qt); getTempQw().append(tempKey, value); /* * this probably should be a sparse row matrix, but compressor should get it * for disk and in memory we want it dense anyway, sparse random * implementations would be a mostly a memory management disaster consisting * of rehashes and GC // thrashing. (IMHO) */ value.setBlock(null); qSolver.reset(); }