@Override
public AtomicNumericFieldData loadDirect(AtomicReaderContext context) throws Exception {
AtomicReader reader = context.reader();
Terms terms = reader.terms(getFieldNames().indexName());
PackedArrayAtomicFieldData data = null;
PackedArrayEstimator estimator =
new PackedArrayEstimator(breakerService.getBreaker(), getNumericType());
if (terms == null) {
data = PackedArrayAtomicFieldData.empty(reader.maxDoc());
estimator.adjustForNoTerms(data.getMemorySizeInBytes());
return data;
}
// TODO: how can we guess the number of terms? numerics end up creating more terms per value...
// Lucene encodes numeric data so that the lexicographical (encoded) order matches the integer
// order so we know the sequence of
// longs is going to be monotonically increasing
final MonotonicAppendingLongBuffer values = new MonotonicAppendingLongBuffer();
final float acceptableTransientOverheadRatio =
fieldDataType
.getSettings()
.getAsFloat(
"acceptable_transient_overhead_ratio",
OrdinalsBuilder.DEFAULT_ACCEPTABLE_OVERHEAD_RATIO);
TermsEnum termsEnum = estimator.beforeLoad(terms);
boolean success = false;
try (OrdinalsBuilder builder =
new OrdinalsBuilder(-1, reader.maxDoc(), acceptableTransientOverheadRatio)) {
BytesRefIterator iter = builder.buildFromTerms(termsEnum);
BytesRef term;
assert !getNumericType().isFloatingPoint();
final boolean indexedAsLong = getNumericType().requiredBits() > 32;
while ((term = iter.next()) != null) {
final long value =
indexedAsLong
? NumericUtils.prefixCodedToLong(term)
: NumericUtils.prefixCodedToInt(term);
assert values.size() == 0 || value > values.get(values.size() - 1);
values.add(value);
}
Ordinals build = builder.build(fieldDataType.getSettings());
if (!build.isMultiValued() && CommonSettings.removeOrdsOnSingleValue(fieldDataType)) {
Docs ordinals = build.ordinals();
final FixedBitSet set = builder.buildDocsWithValuesSet();
long minValue, maxValue;
minValue = maxValue = 0;
if (values.size() > 0) {
minValue = values.get(0);
maxValue = values.get(values.size() - 1);
}
// Encode document without a value with a special value
long missingValue = 0;
if (set != null) {
if ((maxValue - minValue + 1) == values.size()) {
// values are dense
if (minValue > Long.MIN_VALUE) {
missingValue = --minValue;
} else {
assert maxValue != Long.MAX_VALUE;
missingValue = ++maxValue;
}
} else {
for (long i = 1; i < values.size(); ++i) {
if (values.get(i) > values.get(i - 1) + 1) {
missingValue = values.get(i - 1) + 1;
break;
}
}
}
missingValue -= minValue; // delta
}
final long delta = maxValue - minValue;
final int bitsRequired = delta < 0 ? 64 : PackedInts.bitsRequired(delta);
final float acceptableOverheadRatio =
fieldDataType.getSettings().getAsFloat("acceptable_overhead_ratio", PackedInts.DEFAULT);
final PackedInts.FormatAndBits formatAndBits =
PackedInts.fastestFormatAndBits(reader.maxDoc(), bitsRequired, acceptableOverheadRatio);
// there's sweet spot where due to low unique value count, using ordinals will consume less
// memory
final long singleValuesSize =
formatAndBits.format.longCount(
PackedInts.VERSION_CURRENT, reader.maxDoc(), formatAndBits.bitsPerValue)
* 8L;
final long uniqueValuesSize = values.ramBytesUsed();
final long ordinalsSize = build.getMemorySizeInBytes();
if (uniqueValuesSize + ordinalsSize < singleValuesSize) {
data = new PackedArrayAtomicFieldData.WithOrdinals(values, reader.maxDoc(), build);
} else {
final PackedInts.Mutable sValues =
PackedInts.getMutable(reader.maxDoc(), bitsRequired, acceptableOverheadRatio);
if (missingValue != 0) {
sValues.fill(0, sValues.size(), missingValue);
}
for (int i = 0; i < reader.maxDoc(); i++) {
final long ord = ordinals.getOrd(i);
if (ord != Ordinals.MISSING_ORDINAL) {
sValues.set(i, values.get(ord - 1) - minValue);
}
}
if (set == null) {
data =
new PackedArrayAtomicFieldData.Single(
sValues, minValue, reader.maxDoc(), ordinals.getNumOrds());
} else {
data =
new PackedArrayAtomicFieldData.SingleSparse(
sValues, minValue, reader.maxDoc(), missingValue, ordinals.getNumOrds());
}
}
} else {
data = new PackedArrayAtomicFieldData.WithOrdinals(values, reader.maxDoc(), build);
}
success = true;
return data;
} finally {
if (!success) {
// If something went wrong, unwind any current estimations we've made
estimator.afterLoad(termsEnum, 0);
} else {
// Adjust as usual, based on the actual size of the field data
estimator.afterLoad(termsEnum, data.getMemorySizeInBytes());
}
}
}
@Override
public AtomicNumericFieldData loadDirect(LeafReaderContext context) throws Exception {
final LeafReader reader = context.reader();
Terms terms = reader.terms(getFieldNames().indexName());
AtomicNumericFieldData data = null;
PackedArrayEstimator estimator =
new PackedArrayEstimator(
breakerService.getBreaker(CircuitBreaker.FIELDDATA),
getNumericType(),
getFieldNames().fullName());
if (terms == null) {
data = AtomicLongFieldData.empty(reader.maxDoc());
estimator.adjustForNoTerms(data.ramBytesUsed());
return data;
}
// TODO: how can we guess the number of terms? numerics end up creating more terms per value...
// Lucene encodes numeric data so that the lexicographical (encoded) order matches the integer
// order so we know the sequence of
// longs is going to be monotonically increasing
final PackedLongValues.Builder valuesBuilder =
PackedLongValues.monotonicBuilder(PackedInts.COMPACT);
final float acceptableTransientOverheadRatio =
fieldDataType
.getSettings()
.getAsFloat(
"acceptable_transient_overhead_ratio",
OrdinalsBuilder.DEFAULT_ACCEPTABLE_OVERHEAD_RATIO);
TermsEnum termsEnum = estimator.beforeLoad(terms);
assert !getNumericType().isFloatingPoint();
boolean success = false;
try (OrdinalsBuilder builder =
new OrdinalsBuilder(-1, reader.maxDoc(), acceptableTransientOverheadRatio)) {
BytesRefIterator iter = builder.buildFromTerms(termsEnum);
BytesRef term;
while ((term = iter.next()) != null) {
final long value = numericType.toLong(term);
valuesBuilder.add(value);
}
final PackedLongValues values = valuesBuilder.build();
final Ordinals build = builder.build(fieldDataType.getSettings());
CommonSettings.MemoryStorageFormat formatHint =
CommonSettings.getMemoryStorageHint(fieldDataType);
RandomAccessOrds ordinals = build.ordinals();
if (FieldData.isMultiValued(ordinals)
|| formatHint == CommonSettings.MemoryStorageFormat.ORDINALS) {
final long ramBytesUsed = build.ramBytesUsed() + values.ramBytesUsed();
data =
new AtomicLongFieldData(ramBytesUsed) {
@Override
public SortedNumericDocValues getLongValues() {
return withOrdinals(build, values, reader.maxDoc());
}
@Override
public Collection<Accountable> getChildResources() {
List<Accountable> resources = new ArrayList<>();
resources.add(Accountables.namedAccountable("ordinals", build));
resources.add(Accountables.namedAccountable("values", values));
return Collections.unmodifiableList(resources);
}
};
} else {
final BitSet docsWithValues = builder.buildDocsWithValuesSet();
long minV, maxV;
minV = maxV = 0;
if (values.size() > 0) {
minV = values.get(0);
maxV = values.get(values.size() - 1);
}
final float acceptableOverheadRatio =
fieldDataType.getSettings().getAsFloat("acceptable_overhead_ratio", PackedInts.DEFAULT);
final int pageSize = fieldDataType.getSettings().getAsInt("single_value_page_size", 1024);
if (formatHint == null) {
formatHint =
chooseStorageFormat(
reader, values, build, ordinals, minV, maxV, acceptableOverheadRatio, pageSize);
}
logger.trace(
"single value format for field [{}] set to [{}]",
getFieldNames().fullName(),
formatHint);
switch (formatHint) {
case PACKED:
// Encode document without a value with a special value
long missingV = 0;
if (docsWithValues != null) {
if ((maxV - minV + 1) == values.size()) {
// values are dense
if (minV > Long.MIN_VALUE) {
missingV = --minV;
} else {
assert maxV != Long.MAX_VALUE;
missingV = ++maxV;
}
} else {
for (long i = 1; i < values.size(); ++i) {
if (values.get(i) > values.get(i - 1) + 1) {
missingV = values.get(i - 1) + 1;
break;
}
}
}
missingV -= minV;
}
final long missingValue = missingV;
final long minValue = minV;
final long maxValue = maxV;
final long valuesDelta = maxValue - minValue;
int bitsRequired = valuesDelta < 0 ? 64 : PackedInts.bitsRequired(valuesDelta);
final PackedInts.Mutable sValues =
PackedInts.getMutable(reader.maxDoc(), bitsRequired, acceptableOverheadRatio);
if (docsWithValues != null) {
sValues.fill(0, sValues.size(), missingV);
}
for (int i = 0; i < reader.maxDoc(); i++) {
ordinals.setDocument(i);
if (ordinals.cardinality() > 0) {
final long ord = ordinals.ordAt(0);
long value = values.get(ord);
sValues.set(i, value - minValue);
}
}
long ramBytesUsed =
values.ramBytesUsed()
+ (docsWithValues == null ? 0 : docsWithValues.ramBytesUsed());
data =
new AtomicLongFieldData(ramBytesUsed) {
@Override
public SortedNumericDocValues getLongValues() {
if (docsWithValues == null) {
return singles(sValues, minValue);
} else {
return sparseSingles(sValues, minValue, missingValue, reader.maxDoc());
}
}
@Override
public Collection<Accountable> getChildResources() {
List<Accountable> resources = new ArrayList<>();
resources.add(Accountables.namedAccountable("values", sValues));
if (docsWithValues != null) {
resources.add(
Accountables.namedAccountable("missing bitset", docsWithValues));
}
return Collections.unmodifiableList(resources);
}
};
break;
case PAGED:
final PackedLongValues.Builder dpValues =
PackedLongValues.deltaPackedBuilder(pageSize, acceptableOverheadRatio);
long lastValue = 0;
for (int i = 0; i < reader.maxDoc(); i++) {
ordinals.setDocument(i);
if (ordinals.cardinality() > 0) {
final long ord = ordinals.ordAt(i);
lastValue = values.get(ord);
}
dpValues.add(lastValue);
}
final PackedLongValues pagedValues = dpValues.build();
ramBytesUsed = pagedValues.ramBytesUsed();
if (docsWithValues != null) {
ramBytesUsed += docsWithValues.ramBytesUsed();
}
data =
new AtomicLongFieldData(ramBytesUsed) {
@Override
public SortedNumericDocValues getLongValues() {
return pagedSingles(pagedValues, docsWithValues);
}
@Override
public Collection<Accountable> getChildResources() {
List<Accountable> resources = new ArrayList<>();
resources.add(Accountables.namedAccountable("values", pagedValues));
if (docsWithValues != null) {
resources.add(
Accountables.namedAccountable("missing bitset", docsWithValues));
}
return Collections.unmodifiableList(resources);
}
};
break;
case ORDINALS:
ramBytesUsed = build.ramBytesUsed() + values.ramBytesUsed();
data =
new AtomicLongFieldData(ramBytesUsed) {
@Override
public SortedNumericDocValues getLongValues() {
return withOrdinals(build, values, reader.maxDoc());
}
@Override
public Collection<Accountable> getChildResources() {
List<Accountable> resources = new ArrayList<>();
resources.add(Accountables.namedAccountable("ordinals", build));
resources.add(Accountables.namedAccountable("values", values));
return Collections.unmodifiableList(resources);
}
};
break;
default:
throw new ElasticsearchException("unknown memory format: " + formatHint);
}
}
success = true;
return data;
} finally {
if (!success) {
// If something went wrong, unwind any current estimations we've made
estimator.afterLoad(termsEnum, 0);
} else {
// Adjust as usual, based on the actual size of the field data
estimator.afterLoad(termsEnum, data.ramBytesUsed());
}
}
}