/**
* @param path
* @param job
* @param fs
* @param dest
* @param rlen
* @param clen
* @param brlen
* @param bclen
* @throws IOException
*/
@SuppressWarnings("deprecation")
private void readBinaryCellMatrixFromHDFS(
Path path,
JobConf job,
FileSystem fs,
MatrixBlock dest,
long rlen,
long clen,
int brlen,
int bclen)
throws IOException {
boolean sparse = dest.isInSparseFormat();
MatrixIndexes key = new MatrixIndexes();
MatrixCell value = new MatrixCell();
int row = -1;
int col = -1;
try {
for (Path lpath : getSequenceFilePaths(fs, path)) // 1..N files
{
// directly read from sequence files (individual partfiles)
SequenceFile.Reader reader = new SequenceFile.Reader(fs, lpath, job);
try {
if (sparse) {
while (reader.next(key, value)) {
row = (int) key.getRowIndex() - 1;
col = (int) key.getColumnIndex() - 1;
double lvalue = value.getValue();
dest.appendValue(row, col, lvalue);
}
} else {
while (reader.next(key, value)) {
row = (int) key.getRowIndex() - 1;
col = (int) key.getColumnIndex() - 1;
double lvalue = value.getValue();
dest.appendValue(row, col, lvalue);
}
}
} finally {
IOUtilFunctions.closeSilently(reader);
}
}
if (sparse) dest.sortSparseRows();
} catch (Exception ex) {
// post-mortem error handling and bounds checking
if (row < 0 || row + 1 > rlen || col < 0 || col + 1 > clen) {
throw new IOException(
"Matrix cell ["
+ (row + 1)
+ ","
+ (col + 1)
+ "] "
+ "out of overall matrix range [1:"
+ rlen
+ ",1:"
+ clen
+ "].");
} else {
throw new IOException("Unable to read matrix in binary cell format.", ex);
}
}
}
@SuppressWarnings("deprecation")
public void flushBuffer(Reporter reporter) throws RuntimeException {
try {
if (_mapBuffer != null) {
MatrixIndexes key = null; // new MatrixIndexes();
MatrixCell value = new MatrixCell();
for (Entry<Byte, CTableMap> ctable : _mapBuffer.entrySet()) {
ArrayList<Integer> resultIDs =
ReduceBase.getOutputIndexes(ctable.getKey(), _resultIndexes);
CTableMap resultMap = ctable.getValue();
// maintain result dims and nonzeros
for (Integer i : resultIDs) {
_resultNonZeros[i] += resultMap.size();
if (_resultDimsUnknown[i] == (byte) 1) {
_resultMaxRowDims[i] = Math.max(resultMap.getMaxRow(), _resultMaxRowDims[i]);
_resultMaxColDims[i] = Math.max(resultMap.getMaxColumn(), _resultMaxColDims[i]);
}
}
// output result data
for (LLDoubleEntry e : resultMap.entrySet()) {
key = new MatrixIndexes(e.key1, e.key2);
value.setValue(e.value);
for (Integer i : resultIDs) {
_collector.collectOutput(key, value, i, reporter);
}
}
}
} else if (_blockBuffer != null) {
MatrixIndexes key = new MatrixIndexes(1, 1);
// DataConverter.writeBinaryBlockMatrixToHDFS(path, job, mat, mc.get_rows(), mc.get_cols(),
// mc.get_rows_per_block(), mc.get_cols_per_block(), replication);
for (Entry<Byte, MatrixBlock> ctable : _blockBuffer.entrySet()) {
ArrayList<Integer> resultIDs =
ReduceBase.getOutputIndexes(ctable.getKey(), _resultIndexes);
MatrixBlock outBlock = ctable.getValue();
outBlock.recomputeNonZeros();
// TODO: change hard coding of 1000
int brlen = 1000, bclen = 1000;
int rlen = outBlock.getNumRows();
int clen = outBlock.getNumColumns();
// final output matrix is smaller than a single block
if (rlen <= brlen && clen <= brlen) {
key = new MatrixIndexes(1, 1);
for (Integer i : resultIDs) {
_collector.collectOutput(key, outBlock, i, reporter);
_resultNonZeros[i] += outBlock.getNonZeros();
}
} else {
// Following code is similar to that in
// DataConverter.DataConverter.writeBinaryBlockMatrixToHDFS
// initialize blocks for reuse (at most 4 different blocks required)
MatrixBlock[] blocks =
MatrixWriter.createMatrixBlocksForReuse(
rlen, clen, brlen, bclen, true, outBlock.getNonZeros());
// create and write subblocks of matrix
for (int blockRow = 0; blockRow < (int) Math.ceil(rlen / (double) brlen); blockRow++) {
for (int blockCol = 0;
blockCol < (int) Math.ceil(clen / (double) bclen);
blockCol++) {
int maxRow = (blockRow * brlen + brlen < rlen) ? brlen : rlen - blockRow * brlen;
int maxCol = (blockCol * bclen + bclen < clen) ? bclen : clen - blockCol * bclen;
int row_offset = blockRow * brlen;
int col_offset = blockCol * bclen;
// get reuse matrix block
MatrixBlock block =
MatrixWriter.getMatrixBlockForReuse(blocks, maxRow, maxCol, brlen, bclen);
// copy submatrix to block
outBlock.sliceOperations(
row_offset,
row_offset + maxRow - 1,
col_offset,
col_offset + maxCol - 1,
block);
// TODO: skip empty "block"
// append block to sequence file
key.setIndexes(blockRow + 1, blockCol + 1);
for (Integer i : resultIDs) {
_collector.collectOutput(key, block, i, reporter);
_resultNonZeros[i] += block.getNonZeros();
}
// reset block for later reuse
block.reset();
}
}
}
}
} else {
throw new DMLRuntimeException("Unexpected.. both ctable buffers are empty.");
}
} catch (Exception ex) {
throw new RuntimeException("Failed to flush ctable buffer.", ex);
}
// remove existing partial ctables
if (_mapBuffer != null) _mapBuffer.clear();
else _blockBuffer.clear();
}