use of java.nio.IntBuffer in project druid by druid-io.
the class IndexMerger method makeIndexFiles.
protected File makeIndexFiles(final List<IndexableAdapter> indexes, final AggregatorFactory[] metricAggs, final File outDir, final ProgressIndicator progress, final List<String> mergedDimensions, final List<String> mergedMetrics, final Function<ArrayList<Iterable<Rowboat>>, Iterable<Rowboat>> rowMergerFn, final IndexSpec indexSpec) throws IOException {
List<Metadata> metadataList = Lists.transform(indexes, new Function<IndexableAdapter, Metadata>() {
@Nullable
@Override
public Metadata apply(IndexableAdapter input) {
return input.getMetadata();
}
});
Metadata segmentMetadata = null;
if (metricAggs != null) {
AggregatorFactory[] combiningMetricAggs = new AggregatorFactory[metricAggs.length];
for (int i = 0; i < metricAggs.length; i++) {
combiningMetricAggs[i] = metricAggs[i].getCombiningFactory();
}
segmentMetadata = Metadata.merge(metadataList, combiningMetricAggs);
} else {
segmentMetadata = Metadata.merge(metadataList, null);
}
final Map<String, ValueType> valueTypes = Maps.newTreeMap(Ordering.<String>natural().nullsFirst());
final Map<String, String> metricTypeNames = Maps.newTreeMap(Ordering.<String>natural().nullsFirst());
final Map<String, ColumnCapabilitiesImpl> columnCapabilities = Maps.newHashMap();
final List<ColumnCapabilitiesImpl> dimCapabilities = new ArrayList<>();
for (IndexableAdapter adapter : indexes) {
for (String dimension : adapter.getDimensionNames()) {
ColumnCapabilitiesImpl mergedCapabilities = columnCapabilities.get(dimension);
ColumnCapabilities capabilities = adapter.getCapabilities(dimension);
if (mergedCapabilities == null) {
mergedCapabilities = new ColumnCapabilitiesImpl();
}
columnCapabilities.put(dimension, mergedCapabilities.merge(capabilities));
}
for (String metric : adapter.getMetricNames()) {
ColumnCapabilitiesImpl mergedCapabilities = columnCapabilities.get(metric);
ColumnCapabilities capabilities = adapter.getCapabilities(metric);
if (mergedCapabilities == null) {
mergedCapabilities = new ColumnCapabilitiesImpl();
}
columnCapabilities.put(metric, mergedCapabilities.merge(capabilities));
valueTypes.put(metric, capabilities.getType());
metricTypeNames.put(metric, adapter.getMetricType(metric));
}
}
for (String dimension : mergedDimensions) {
dimCapabilities.add(columnCapabilities.get(dimension));
}
Closer closer = Closer.create();
try {
final Interval dataInterval;
final File v8OutDir = new File(outDir, "v8-tmp");
FileUtils.forceMkdir(v8OutDir);
registerDeleteDirectory(closer, v8OutDir);
File tmpPeonFilesDir = new File(v8OutDir, "tmpPeonFiles");
FileUtils.forceMkdir(tmpPeonFilesDir);
registerDeleteDirectory(closer, tmpPeonFilesDir);
final IOPeon ioPeon = new TmpFileIOPeon(tmpPeonFilesDir, true);
closer.register(ioPeon);
/************* Main index.drd file **************/
progress.progress();
long startTime = System.currentTimeMillis();
File indexFile = new File(v8OutDir, "index.drd");
try (FileOutputStream fileOutputStream = new FileOutputStream(indexFile);
FileChannel channel = fileOutputStream.getChannel()) {
channel.write(ByteBuffer.wrap(new byte[] { IndexIO.V8_VERSION }));
GenericIndexed.fromIterable(mergedDimensions, GenericIndexed.STRING_STRATEGY).writeToChannel(channel);
GenericIndexed.fromIterable(mergedMetrics, GenericIndexed.STRING_STRATEGY).writeToChannel(channel);
DateTime minTime = new DateTime(JodaUtils.MAX_INSTANT);
DateTime maxTime = new DateTime(JodaUtils.MIN_INSTANT);
for (IndexableAdapter index : indexes) {
minTime = JodaUtils.minDateTime(minTime, index.getDataInterval().getStart());
maxTime = JodaUtils.maxDateTime(maxTime, index.getDataInterval().getEnd());
}
dataInterval = new Interval(minTime, maxTime);
serializerUtils.writeString(channel, String.format("%s/%s", minTime, maxTime));
serializerUtils.writeString(channel, mapper.writeValueAsString(indexSpec.getBitmapSerdeFactory()));
}
IndexIO.checkFileSize(indexFile);
log.info("outDir[%s] completed index.drd in %,d millis.", v8OutDir, System.currentTimeMillis() - startTime);
/************* Setup Dim Conversions **************/
progress.progress();
startTime = System.currentTimeMillis();
final ArrayList<FileOutputSupplier> dimOuts = Lists.newArrayListWithCapacity(mergedDimensions.size());
final DimensionHandler[] handlers = makeDimensionHandlers(mergedDimensions, dimCapabilities);
final List<DimensionMerger> mergers = new ArrayList<>();
for (int i = 0; i < mergedDimensions.size(); i++) {
DimensionMergerLegacy merger = handlers[i].makeLegacyMerger(indexSpec, v8OutDir, ioPeon, dimCapabilities.get(i), progress);
mergers.add(merger);
merger.writeMergedValueMetadata(indexes);
FileOutputSupplier dimOut = new FileOutputSupplier(merger.makeDimFile(), true);
merger.writeValueMetadataToFile(dimOut);
dimOuts.add(dimOut);
}
log.info("outDir[%s] completed dim conversions in %,d millis.", v8OutDir, System.currentTimeMillis() - startTime);
/************* Walk through data sets and merge them *************/
progress.progress();
startTime = System.currentTimeMillis();
Iterable<Rowboat> theRows = makeRowIterable(indexes, mergedDimensions, mergedMetrics, rowMergerFn, dimCapabilities, handlers, mergers);
LongSupplierSerializer timeWriter = CompressionFactory.getLongSerializer(ioPeon, "little_end_time", IndexIO.BYTE_ORDER, indexSpec.getLongEncoding(), CompressedObjectStrategy.DEFAULT_COMPRESSION_STRATEGY);
timeWriter.open();
ArrayList<MetricColumnSerializer> metWriters = Lists.newArrayListWithCapacity(mergedMetrics.size());
final CompressedObjectStrategy.CompressionStrategy metCompression = indexSpec.getMetricCompression();
final CompressionFactory.LongEncodingStrategy longEncoding = indexSpec.getLongEncoding();
for (String metric : mergedMetrics) {
ValueType type = valueTypes.get(metric);
switch(type) {
case LONG:
metWriters.add(new LongMetricColumnSerializer(metric, v8OutDir, ioPeon, metCompression, longEncoding));
break;
case FLOAT:
metWriters.add(new FloatMetricColumnSerializer(metric, v8OutDir, ioPeon, metCompression));
break;
case COMPLEX:
final String typeName = metricTypeNames.get(metric);
ComplexMetricSerde serde = ComplexMetrics.getSerdeForType(typeName);
if (serde == null) {
throw new ISE("Unknown type[%s]", typeName);
}
metWriters.add(new ComplexMetricColumnSerializer(metric, v8OutDir, ioPeon, serde));
break;
default:
throw new ISE("Unknown type[%s]", type);
}
}
for (MetricColumnSerializer metWriter : metWriters) {
metWriter.open();
}
int rowCount = 0;
long time = System.currentTimeMillis();
List<IntBuffer> rowNumConversions = Lists.newArrayListWithCapacity(indexes.size());
for (IndexableAdapter index : indexes) {
int[] arr = new int[index.getNumRows()];
Arrays.fill(arr, INVALID_ROW);
rowNumConversions.add(IntBuffer.wrap(arr));
}
for (Rowboat theRow : theRows) {
progress.progress();
timeWriter.add(theRow.getTimestamp());
final Object[] metrics = theRow.getMetrics();
for (int i = 0; i < metrics.length; ++i) {
metWriters.get(i).serialize(metrics[i]);
}
Object[] dims = theRow.getDims();
for (int i = 0; i < dims.length; ++i) {
mergers.get(i).processMergedRow(dims[i]);
}
for (Map.Entry<Integer, TreeSet<Integer>> comprisedRow : theRow.getComprisedRows().entrySet()) {
final IntBuffer conversionBuffer = rowNumConversions.get(comprisedRow.getKey());
for (Integer rowNum : comprisedRow.getValue()) {
while (conversionBuffer.position() < rowNum) {
conversionBuffer.put(INVALID_ROW);
}
conversionBuffer.put(rowCount);
}
}
if ((++rowCount % 500000) == 0) {
log.info("outDir[%s] walked 500,000/%,d rows in %,d millis.", v8OutDir, rowCount, System.currentTimeMillis() - time);
time = System.currentTimeMillis();
}
}
for (IntBuffer rowNumConversion : rowNumConversions) {
rowNumConversion.rewind();
}
final File timeFile = IndexIO.makeTimeFile(v8OutDir, IndexIO.BYTE_ORDER);
timeFile.delete();
ByteSink out = Files.asByteSink(timeFile, FileWriteMode.APPEND);
timeWriter.closeAndConsolidate(out);
IndexIO.checkFileSize(timeFile);
for (MetricColumnSerializer metWriter : metWriters) {
metWriter.close();
}
log.info("outDir[%s] completed walk through of %,d rows in %,d millis.", v8OutDir, rowCount, System.currentTimeMillis() - startTime);
/************ Create Inverted Indexes and Finalize Columns *************/
startTime = System.currentTimeMillis();
final File invertedFile = new File(v8OutDir, "inverted.drd");
Files.touch(invertedFile);
out = Files.asByteSink(invertedFile, FileWriteMode.APPEND);
final File geoFile = new File(v8OutDir, "spatial.drd");
Files.touch(geoFile);
OutputSupplier<FileOutputStream> spatialOut = Files.newOutputStreamSupplier(geoFile, true);
for (int i = 0; i < mergedDimensions.size(); i++) {
DimensionMergerLegacy legacyMerger = (DimensionMergerLegacy) mergers.get(i);
legacyMerger.writeIndexes(rowNumConversions, closer);
legacyMerger.writeIndexesToFiles(out, spatialOut);
legacyMerger.writeRowValuesToFile(dimOuts.get(i));
}
log.info("outDir[%s] completed inverted.drd and wrote dimensions in %,d millis.", v8OutDir, System.currentTimeMillis() - startTime);
final Function<String, String> dimFilenameFunction = new Function<String, String>() {
@Override
public String apply(@Nullable String input) {
String formatString;
if (columnCapabilities.get(input).isDictionaryEncoded()) {
formatString = "dim_%s.drd";
} else {
formatString = String.format("numeric_dim_%%s_%s.drd", IndexIO.BYTE_ORDER);
}
return GuavaUtils.formatFunction(formatString).apply(input);
}
};
final ArrayList<String> expectedFiles = Lists.newArrayList(Iterables.concat(Arrays.asList("index.drd", "inverted.drd", "spatial.drd", String.format("time_%s.drd", IndexIO.BYTE_ORDER)), Iterables.transform(mergedDimensions, dimFilenameFunction), Iterables.transform(mergedMetrics, GuavaUtils.formatFunction(String.format("met_%%s_%s.drd", IndexIO.BYTE_ORDER)))));
if (segmentMetadata != null) {
writeMetadataToFile(new File(v8OutDir, "metadata.drd"), segmentMetadata);
log.info("wrote metadata.drd in outDir[%s].", v8OutDir);
expectedFiles.add("metadata.drd");
}
Map<String, File> files = Maps.newLinkedHashMap();
for (String fileName : expectedFiles) {
files.put(fileName, new File(v8OutDir, fileName));
}
File smooshDir = new File(v8OutDir, "smoosher");
FileUtils.forceMkdir(smooshDir);
for (Map.Entry<String, File> entry : Smoosh.smoosh(v8OutDir, smooshDir, files).entrySet()) {
entry.getValue().delete();
}
for (File file : smooshDir.listFiles()) {
Files.move(file, new File(v8OutDir, file.getName()));
}
if (!smooshDir.delete()) {
log.info("Unable to delete temporary dir[%s], contains[%s]", smooshDir, Arrays.asList(smooshDir.listFiles()));
throw new IOException(String.format("Unable to delete temporary dir[%s]", smooshDir));
}
createIndexDrdFile(IndexIO.V8_VERSION, v8OutDir, GenericIndexed.fromIterable(mergedDimensions, GenericIndexed.STRING_STRATEGY), GenericIndexed.fromIterable(mergedMetrics, GenericIndexed.STRING_STRATEGY), dataInterval, indexSpec.getBitmapSerdeFactory());
indexIO.getDefaultIndexIOHandler().convertV8toV9(v8OutDir, outDir, indexSpec);
return outDir;
} catch (Throwable t) {
throw closer.rethrow(t);
} finally {
closer.close();
}
}
use of java.nio.IntBuffer in project druid by druid-io.
the class CompressedIntsIndexedSupplier method fromIntBuffer.
public static CompressedIntsIndexedSupplier fromIntBuffer(final IntBuffer buffer, final int chunkFactor, final ByteOrder byteOrder, CompressedObjectStrategy.CompressionStrategy compression) {
Preconditions.checkArgument(chunkFactor <= MAX_INTS_IN_BUFFER, "Chunks must be <= 64k bytes. chunkFactor was[%s]", chunkFactor);
return new CompressedIntsIndexedSupplier(buffer.remaining(), chunkFactor, GenericIndexed.fromIterable(new Iterable<ResourceHolder<IntBuffer>>() {
@Override
public Iterator<ResourceHolder<IntBuffer>> iterator() {
return new Iterator<ResourceHolder<IntBuffer>>() {
IntBuffer myBuffer = buffer.asReadOnlyBuffer();
@Override
public boolean hasNext() {
return myBuffer.hasRemaining();
}
@Override
public ResourceHolder<IntBuffer> next() {
IntBuffer retVal = myBuffer.asReadOnlyBuffer();
if (chunkFactor < myBuffer.remaining()) {
retVal.limit(retVal.position() + chunkFactor);
}
myBuffer.position(myBuffer.position() + retVal.remaining());
return StupidResourceHolder.create(retVal);
}
@Override
public void remove() {
throw new UnsupportedOperationException();
}
};
}
}, CompressedIntBufferObjectStrategy.getBufferForOrder(byteOrder, compression, chunkFactor)), compression);
}
use of java.nio.IntBuffer in project deeplearning4j by deeplearning4j.
the class DoubleArrayTrie method write.
public void write(OutputStream output) throws IOException {
baseBuffer.rewind();
checkBuffer.rewind();
tailBuffer.rewind();
int baseCheckSize = Math.min(maxBaseCheckIndex + 64, baseBuffer.capacity());
int tailSize = Math.min(tailIndex - TAIL_OFFSET + 64, tailBuffer.capacity());
DataOutputStream dataOutput = new DataOutputStream(new BufferedOutputStream(output));
dataOutput.writeBoolean(compact);
dataOutput.writeInt(baseCheckSize);
dataOutput.writeInt(tailSize);
WritableByteChannel channel = Channels.newChannel(dataOutput);
ByteBuffer tmpBuffer = ByteBuffer.allocate(baseCheckSize * 4);
IntBuffer tmpIntBuffer = tmpBuffer.asIntBuffer();
tmpIntBuffer.put(baseBuffer.array(), 0, baseCheckSize);
tmpBuffer.rewind();
channel.write(tmpBuffer);
tmpBuffer = ByteBuffer.allocate(baseCheckSize * 4);
tmpIntBuffer = tmpBuffer.asIntBuffer();
tmpIntBuffer.put(checkBuffer.array(), 0, baseCheckSize);
tmpBuffer.rewind();
channel.write(tmpBuffer);
tmpBuffer = ByteBuffer.allocate(tailSize * 2);
CharBuffer tmpCharBuffer = tmpBuffer.asCharBuffer();
tmpCharBuffer.put(tailBuffer.array(), 0, tailSize);
tmpBuffer.rewind();
channel.write(tmpBuffer);
dataOutput.flush();
}
use of java.nio.IntBuffer in project deeplearning4j by deeplearning4j.
the class DoubleArrayTrie method extendBuffers.
private void extendBuffers(int nextIndex) {
int newLength = nextIndex + (int) (baseBuffer.capacity() * BUFFER_GROWTH_PERCENTAGE);
ProgressLog.println("Buffers extended to " + baseBuffer.capacity() + " entries");
IntBuffer newBaseBuffer = IntBuffer.allocate(newLength);
baseBuffer.rewind();
newBaseBuffer.put(baseBuffer);
baseBuffer = newBaseBuffer;
//ByteBuffer.allocate(newLength).asIntBuffer();
IntBuffer newCheckBuffer = IntBuffer.allocate(newLength);
checkBuffer.rewind();
newCheckBuffer.put(checkBuffer);
checkBuffer = newCheckBuffer;
}
use of java.nio.IntBuffer in project deeplearning4j by deeplearning4j.
the class IntegerArrayIO method writeArray.
public static void writeArray(OutputStream output, int[] array) throws IOException {
DataOutputStream dataOutput = new DataOutputStream(output);
int length = array.length;
dataOutput.writeInt(length);
ByteBuffer tmpBuffer = ByteBuffer.allocate(length * INT_BYTES);
IntBuffer intBuffer = tmpBuffer.asIntBuffer();
tmpBuffer.rewind();
intBuffer.put(array);
WritableByteChannel channel = Channels.newChannel(dataOutput);
channel.write(tmpBuffer);
}
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