@Override
public Value lazyArrayChunk(final Key key) {
final Key arykey = ValueArray.getArrayKey(key); // From the base file key
final long off = (_iceRoot != null) ? 0 : ValueArray.getChunkOffset(key); // The offset
final Path p =
(_iceRoot != null)
? new Path(_iceRoot, getIceName(key, (byte) 'V'))
: new Path(arykey.toString());
final Size sz = new Size();
run(
new Callable() {
@Override
public Object call() throws Exception {
FileSystem fs = FileSystem.get(p.toUri(), CONF);
long rem = fs.getFileStatus(p).getLen() - off;
sz._value = (rem > ValueArray.CHUNK_SZ * 2) ? (int) ValueArray.CHUNK_SZ : (int) rem;
return null;
}
},
true,
0);
Value val = new Value(key, sz._value, Value.HDFS);
val.setdsk(); // But its already on disk.
return val;
}
public static Response redirect(JsonObject fromPageResponse, Key rfModelKey) {
RFModel rfModel = DKV.get(rfModelKey).get();
ValueArray data = DKV.get(rfModel._dataKey).get();
return redirect(
fromPageResponse,
null,
rfModelKey,
rfModel._dataKey,
rfModel._totalTrees,
data.numCols() - 1,
null,
true,
false);
}
@Override
public byte[] load(final Value v) {
final byte[] b = MemoryManager.malloc1(v._max);
long skip = 0;
Key k = v._key;
final Path p;
if (_iceRoot != null) {
p = new Path(_iceRoot, getIceName(v));
} else {
// Convert an arraylet chunk into a long-offset from the base file.
if (k._kb[0] == Key.ARRAYLET_CHUNK) {
skip = ValueArray.getChunkOffset(k); // The offset
k = ValueArray.getArrayKey(k); // From the base file key
if (k.toString().endsWith(Extensions.HEX)) { // Hex file?
int value_len = DKV.get(k).memOrLoad().length; // How long is the ValueArray header?
skip += value_len;
}
}
p = new Path(k.toString());
}
final long skip_ = skip;
run(
new Callable() {
@Override
public Object call() throws Exception {
FileSystem fs = FileSystem.get(p.toUri(), CONF);
FSDataInputStream s = null;
try {
s = fs.open(p);
// NOTE:
// The following line degrades performance of HDFS load from S3 API:
// s.readFully(skip,b,0,b.length);
// Google API's simple seek has better performance
// Load of 300MB file via Google API ~ 14sec, via s.readFully ~ 5min (under the same
// condition)
ByteStreams.skipFully(s, skip_);
ByteStreams.readFully(s, b);
assert v.isPersisted();
} finally {
Utils.close(s);
}
return null;
}
},
true,
v._max);
return b;
}
public static KMeansScore score(KMeansModel model, ValueArray ary) {
KMeansScore kms = new KMeansScore();
kms._arykey = ary._key;
kms._cols = model.columnMapping(ary.colNames());
kms._clusters = model._clusters;
kms._normalized = model._normalized;
kms.invoke(ary._key);
return kms;
}
@Override
public void map(Key key) {
_rows = new long[_clusters.length];
_dist = new double[_clusters.length];
assert key.home();
ValueArray va = DKV.get(_arykey).get();
AutoBuffer bits = va.getChunk(key);
int rows = va.rpc(ValueArray.getChunkIndex(key));
double[] values = new double[_cols.length - 1];
ClusterDist cd = new ClusterDist();
for (int row = 0; row < rows; row++) {
KMeans.datad(va, bits, row, _cols, _normalized, values);
KMeans.closest(_clusters, values, cd);
_rows[cd._cluster]++;
_dist[cd._cluster] += cd._dist;
}
_arykey = null;
_cols = null;
_clusters = null;
}
@Override
public byte[] load(final Value v) {
final byte[] b = MemoryManager.malloc1(v._max);
long skip = 0;
Key k = v._key;
if (k._kb[0] == Key.ARRAYLET_CHUNK) {
skip = ValueArray.getChunkOffset(k); // The offset
k = ValueArray.getArrayKey(k); // From the base file key
} else if (k._kb[0] == Key.DVEC) {
skip = water.fvec.NFSFileVec.chunkOffset(k); // The offset
}
final Path p =
_iceRoot == null ? new Path(getPathForKey(k)) : new Path(_iceRoot, getIceName(v));
final long skip_ = skip;
run(
new Callable() {
@Override
public Object call() throws Exception {
FileSystem fs = FileSystem.get(p.toUri(), CONF);
FSDataInputStream s = null;
try {
s = fs.open(p);
// NOTE:
// The following line degrades performance of HDFS load from S3 API:
// s.readFully(skip,b,0,b.length);
// Google API's simple seek has better performance
// Load of 300MB file via Google API ~ 14sec, via s.readFully ~ 5min (under the same
// condition)
ByteStreams.skipFully(s, skip_);
ByteStreams.readFully(s, b);
assert v.isPersisted();
} finally {
Utils.close(s);
}
return null;
}
},
true,
v._max);
return b;
}
private void updateClusters(
int[] clusters, int count, long chunk, long numrows, int rpc, long updatedRow) {
final int offset = (int) (updatedRow - (rpc * chunk));
final Key chunkKey = ValueArray.getChunkKey(chunk, _job.dest());
final int[] message;
if (count == clusters.length) message = clusters;
else {
message = new int[count];
System.arraycopy(clusters, 0, message, 0, message.length);
}
final int rows = ValueArray.rpc(chunk, rpc, numrows);
new Atomic() {
@Override
public Value atomic(Value val) {
assert val == null || val._key.equals(chunkKey);
AutoBuffer b = new AutoBuffer(rows * ROW_SIZE);
if (val != null) b._bb.put(val.memOrLoad());
for (int i = 0; i < message.length; i++) b.put4((offset + i) * 4, message[i]);
b.position(b.limit());
return new Value(chunkKey, b.buf());
}
}.invoke(chunkKey);
}
public static Job run(final Key dest, final KMeansModel model, final ValueArray ary) {
final ChunkProgressJob job = new ChunkProgressJob(ary.chunks(), dest);
new ValueArray(dest, 0).delete_and_lock(job.self());
final H2OCountedCompleter fjtask =
new H2OCountedCompleter() {
@Override
public void compute2() {
KMeansApply kms = new KMeansApply();
kms._job = job;
kms._arykey = ary._key;
kms._cols = model.columnMapping(ary.colNames());
kms._clusters = model._clusters;
kms._normalized = model._normalized;
kms.invoke(ary._key);
Column c = new Column();
c._name = Constants.RESPONSE;
c._size = ROW_SIZE;
c._scale = 1;
c._min = 0;
c._max = model._clusters.length;
c._mean = Double.NaN;
c._sigma = Double.NaN;
c._domain = null;
c._n = ary.numRows();
ValueArray res = new ValueArray(dest, ary.numRows(), c._size, new Column[] {c});
res.unlock(job.self());
job.remove();
tryComplete();
}
@Override
public boolean onExceptionalCompletion(Throwable ex, CountedCompleter caller) {
job.onException(ex);
return super.onExceptionalCompletion(ex, caller);
}
};
job.start(fjtask);
H2O.submitTask(fjtask);
return job;
}
/**
* Creates a new ValueArray with classes. New ValueArray is not aligned with source one
* unfortunately so have to send results to each chunk owner using Atomic.
*/
@Override
public void map(Key key) {
assert key.home();
if (Job.isRunning(_job.self())) {
ValueArray va = DKV.get(_arykey).get();
AutoBuffer bits = va.getChunk(key);
long startRow = va.startRow(ValueArray.getChunkIndex(key));
int rows = va.rpc(ValueArray.getChunkIndex(key));
int rpc = (int) (ValueArray.CHUNK_SZ / ROW_SIZE);
long chunk = ValueArray.chknum(startRow, va.numRows(), ROW_SIZE);
long updatedChk = chunk;
long updatedRow = startRow;
double[] values = new double[_cols.length - 1];
ClusterDist cd = new ClusterDist();
int[] clusters = new int[rows];
int count = 0;
for (int row = 0; row < rows; row++) {
KMeans.datad(va, bits, row, _cols, _normalized, values);
KMeans.closest(_clusters, values, cd);
chunk = ValueArray.chknum(startRow + row, va.numRows(), ROW_SIZE);
if (chunk != updatedChk) {
updateClusters(clusters, count, updatedChk, va.numRows(), rpc, updatedRow);
updatedChk = chunk;
updatedRow = startRow + row;
count = 0;
}
clusters[count++] = cd._cluster;
}
if (count > 0) updateClusters(clusters, count, chunk, va.numRows(), rpc, updatedRow);
_job.updateProgress(1);
}
_job = null;
_arykey = null;
_cols = null;
_clusters = null;
}
