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/**
* Copyright (C) 2020-present MongoDB, Inc.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the Server Side Public License, version 1,
* as published by MongoDB, Inc.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* Server Side Public License for more details.
*
* You should have received a copy of the Server Side Public License
* along with this program. If not, see
* <http://www.mongodb.com/licensing/server-side-public-license>.
*
* As a special exception, the copyright holders give permission to link the
* code of portions of this program with the OpenSSL library under certain
* conditions as described in each individual source file and distribute
* linked combinations including the program with the OpenSSL library. You
* must comply with the Server Side Public License in all respects for
* all of the code used other than as permitted herein. If you modify file(s)
* with this exception, you may extend this exception to your version of the
* file(s), but you are not obligated to do so. If you do not wish to do so,
* delete this exception statement from your version. If you delete this
* exception statement from all source files in the program, then also delete
* it in the license file.
*/
#define MONGO_LOGV2_DEFAULT_COMPONENT ::mongo::logv2::LogComponent::kQuery
#include "mongo/platform/basic.h"
#include "mongo/db/pipeline/document_source_internal_unpack_bucket.h"
#include "mongo/bson/bsonobj.h"
#include "mongo/db/exec/document_value/document.h"
#include "mongo/db/matcher/expression.h"
#include "mongo/db/matcher/expression_algo.h"
#include "mongo/db/matcher/expression_internal_expr_comparison.h"
#include "mongo/db/pipeline/document_source_group.h"
#include "mongo/db/pipeline/document_source_match.h"
#include "mongo/db/pipeline/document_source_project.h"
#include "mongo/db/pipeline/document_source_sample.h"
#include "mongo/db/pipeline/document_source_single_document_transformation.h"
#include "mongo/db/pipeline/document_source_sort.h"
#include "mongo/db/pipeline/expression_context.h"
#include "mongo/db/pipeline/lite_parsed_document_source.h"
#include "mongo/db/timeseries/timeseries_field_names.h"
#include "mongo/logv2/log.h"
namespace mongo {
REGISTER_DOCUMENT_SOURCE(_internalUnpackBucket,
LiteParsedDocumentSourceDefault::parse,
DocumentSourceInternalUnpackBucket::createFromBson,
LiteParsedDocumentSource::AllowedWithApiStrict::kInternal);
namespace {
/**
* Removes metaField from the field set and returns a boolean indicating whether metaField should be
* included in the materialized measurements. Always returns false if metaField does not exist.
*/
auto eraseMetaFromFieldSetAndDetermineIncludeMeta(BucketUnpacker::Behavior unpackerBehavior,
BucketSpec* bucketSpec) {
if (!bucketSpec->metaField) {
return false;
} else if (auto itr = bucketSpec->fieldSet.find(*bucketSpec->metaField);
itr != bucketSpec->fieldSet.end()) {
bucketSpec->fieldSet.erase(itr);
return unpackerBehavior == BucketUnpacker::Behavior::kInclude;
} else {
return unpackerBehavior == BucketUnpacker::Behavior::kExclude;
}
}
/**
* Determine if timestamp values should be included in the materialized measurements.
*/
auto determineIncludeTimeField(BucketUnpacker::Behavior unpackerBehavior, BucketSpec* bucketSpec) {
return (unpackerBehavior == BucketUnpacker::Behavior::kInclude) ==
(bucketSpec->fieldSet.find(bucketSpec->timeField) != bucketSpec->fieldSet.end());
}
/**
* Determine if an arbitrary field should be included in the materialized measurements.
*/
auto determineIncludeField(StringData fieldName,
BucketUnpacker::Behavior unpackerBehavior,
const BucketSpec& bucketSpec) {
return (unpackerBehavior == BucketUnpacker::Behavior::kInclude) ==
(bucketSpec.fieldSet.find(fieldName.toString()) != bucketSpec.fieldSet.end());
}
/**
* A projection can be internalized if every field corresponds to a boolean value. Note that this
* correctly rejects dotted fieldnames, which are mapped to objects internally.
*/
bool canInternalizeProjectObj(const BSONObj& projObj) {
return std::all_of(projObj.begin(), projObj.end(), [](auto&& e) { return e.isBoolean(); });
}
/**
* If 'src' represents an inclusion or exclusion $project, return a BSONObj representing it and a
* bool indicating its type (true for inclusion, false for exclusion). Else return an empty BSONObj.
*/
auto getIncludeExcludeProjectAndType(DocumentSource* src) {
if (const auto proj = dynamic_cast<DocumentSourceSingleDocumentTransformation*>(src); proj &&
(proj->getType() == TransformerInterface::TransformerType::kInclusionProjection ||
proj->getType() == TransformerInterface::TransformerType::kExclusionProjection)) {
return std::pair{proj->getTransformer().serializeTransformation(boost::none).toBson(),
proj->getType() ==
TransformerInterface::TransformerType::kInclusionProjection};
}
return std::pair{BSONObj{}, false};
}
// Optimize the given pipeline after the $_internalUnpackBucket stage pointed to by 'itr'.
void optimizeEndOfPipeline(Pipeline::SourceContainer::iterator itr,
Pipeline::SourceContainer* container) {
// We must create a new SourceContainer representing the subsection of the pipeline we wish to
// optimize, since otherwise calls to optimizeAt() will overrun these limits.
auto endOfPipeline = Pipeline::SourceContainer(std::next(itr), container->end());
Pipeline::optimizeContainer(&endOfPipeline);
container->erase(std::next(itr), container->end());
container->splice(std::next(itr), endOfPipeline);
}
/**
* Creates an ObjectId initialized with an appropriate timestamp corresponding to 'matchExpr' and
* returns it as a Value.
*/
Value constructObjectIdValue(const ComparisonMatchExpression* matchExpr) {
// An ObjectId consists of a 4-byte timestamp, as well as a unique value and a counter, thus
// two ObjectIds initialized with the same date will have different values. To ensure that we
// do not incorrectly include or exclude any buckets, depending on the operator we will
// construct either the largest or the smallest ObjectId possible with the corresponding date.
OID oid;
if (matchExpr->getData().type() == BSONType::Date) {
switch (matchExpr->matchType()) {
case MatchExpression::LT: {
oid.init(matchExpr->getData().date(), false /* min */);
break;
}
case MatchExpression::LTE:
case MatchExpression::EQ: {
oid.init(matchExpr->getData().date(), true /* max */);
break;
}
default:
// We will only perform this optimization with query operators $lt, $lte and $eq.
MONGO_UNREACHABLE_TASSERT(5375801);
}
}
// If the query operand is not of type Date, the original query will not match on any documents
// because documents in a time-series collection must have a timeField of type Date. We will
// make this case faster by keeping the ObjectId as the lowest possible value so as to
// eliminate all buckets.
return Value(oid);
}
/**
* Checks if a sort stage's pattern following our internal unpack bucket is suitable to be reordered
* before us. The sort stage must refer exclusively to the meta field or any subfields.
*/
bool checkMetadataSortReorder(const SortPattern& sortPattern, const StringData& metaFieldStr) {
for (const auto& sortKey : sortPattern) {
if (!sortKey.fieldPath.has_value()) {
return false;
}
if (sortKey.fieldPath->getPathLength() < 1) {
return false;
}
if (sortKey.fieldPath->getFieldName(0) != metaFieldStr) {
return false;
}
}
return true;
}
/**
* Returns a new DocumentSort to reorder before current unpack bucket document.
*/
boost::intrusive_ptr<DocumentSourceSort> createMetadataSortForReorder(
const DocumentSourceSort& sort) {
std::vector<SortPattern::SortPatternPart> updatedPattern;
for (const auto& entry : sort.getSortKeyPattern()) {
// Repoint sort to use metadata field before renaming.
auto updatedFieldPath = FieldPath(timeseries::kBucketMetaFieldName);
if (entry.fieldPath->getPathLength() > 1) {
updatedFieldPath = updatedFieldPath.concat(entry.fieldPath->tail());
}
updatedPattern.push_back(entry);
updatedPattern.back().fieldPath = updatedFieldPath;
}
boost::optional<uint64_t> maxMemoryUsageBytes;
if (auto sortStatsPtr = dynamic_cast<const SortStats*>(sort.getSpecificStats())) {
maxMemoryUsageBytes = sortStatsPtr->maxMemoryUsageBytes;
}
return DocumentSourceSort::create(sort.getContext(),
SortPattern{updatedPattern},
sort.getLimit().get_value_or(0),
maxMemoryUsageBytes);
}
// Optimize the section of the pipeline before the $_internalUnpackBucket stage.
void optimizePrefix(Pipeline::SourceContainer::iterator itr, Pipeline::SourceContainer* container) {
auto prefix = Pipeline::SourceContainer(container->begin(), itr);
Pipeline::optimizeContainer(&prefix);
container->erase(container->begin(), itr);
container->splice(itr, prefix);
}
} // namespace
// Calculates the number of measurements in a bucket given the 'targetTimestampObjSize' using the
// 'BucketUnpacker::kTimestampObjSizeTable' table. If the 'targetTimestampObjSize' hits a record in
// the table, this helper returns the measurement count corresponding to the table record.
// Otherwise, the 'targetTimestampObjSize' is used to probe the table for the smallest {b_i, S_i}
// pair such that 'targetTimestampObjSize' < S_i. Once the interval is found, the upper bound of the
// pair for the interval is computed and then linear interpolation is used to compute the
// measurement count corresponding to the 'targetTimestampObjSize' provided.
int BucketUnpacker::computeMeasurementCount(int targetTimestampObjSize) {
auto currentInterval =
std::find_if(std::begin(BucketUnpacker::kTimestampObjSizeTable),
std::end(BucketUnpacker::kTimestampObjSizeTable),
[&](const auto& entry) { return targetTimestampObjSize <= entry.second; });
if (currentInterval->second == targetTimestampObjSize) {
return currentInterval->first;
}
// This points to the first interval larger than the target 'targetTimestampObjSize', the actual
// interval that will cover the object size is the interval before the current one.
tassert(5422104,
"currentInterval should not point to the first table entry",
currentInterval > BucketUnpacker::kTimestampObjSizeTable.begin());
--currentInterval;
auto nDigitsInRowKey = 1 + (currentInterval - BucketUnpacker::kTimestampObjSizeTable.begin());
return currentInterval->first +
((targetTimestampObjSize - currentInterval->second) / (10 + nDigitsInRowKey));
}
void BucketUnpacker::reset(BSONObj&& bucket) {
_fieldIters.clear();
_timeFieldIter = boost::none;
_bucket = std::move(bucket);
uassert(5346510, "An empty bucket cannot be unpacked", !_bucket.isEmpty());
tassert(5346701,
"The $_internalUnpackBucket stage requires the bucket to be owned",
_bucket.isOwned());
auto&& dataRegion = _bucket.getField(timeseries::kBucketDataFieldName).Obj();
if (dataRegion.isEmpty()) {
// If the data field of a bucket is present but it holds an empty object, there's nothing to
// unpack.
return;
}
auto&& timeFieldElem = dataRegion.getField(_spec.timeField);
uassert(5346700,
"The $_internalUnpackBucket stage requires the data region to have a timeField object",
timeFieldElem);
_timeFieldIter = BSONObjIterator{timeFieldElem.Obj()};
_metaValue = _bucket[timeseries::kBucketMetaFieldName];
if (_spec.metaField) {
// The spec indicates that there might be a metadata region. Missing metadata in
// measurements is expressed with missing metadata in a bucket. But we disallow undefined
// since the undefined BSON type is deprecated.
uassert(5369600,
"The $_internalUnpackBucket stage allows metadata to be absent or otherwise, it "
"must not be the deprecated undefined bson type",
!_metaValue || _metaValue.type() != BSONType::Undefined);
} else {
// If the spec indicates that the time series collection has no metadata field, then we
// should not find a metadata region in the underlying bucket documents.
uassert(5369601,
"The $_internalUnpackBucket stage expects buckets to have missing metadata regions "
"if the metaField parameter is not provided",
!_metaValue);
}
// Walk the data region of the bucket, and decide if an iterator should be set up based on the
// include or exclude case.
for (auto&& elem : dataRegion) {
auto& colName = elem.fieldNameStringData();
if (colName == _spec.timeField) {
// Skip adding a FieldIterator for the timeField since the timestamp value from
// _timeFieldIter can be placed accordingly in the materialized measurement.
continue;
}
// Includes a field when '_unpackerBehavior' is 'kInclude' and it's found in 'fieldSet' or
// _unpackerBehavior is 'kExclude' and it's not found in 'fieldSet'.
if (determineIncludeField(colName, _unpackerBehavior, _spec)) {
_fieldIters.emplace_back(colName.toString(), BSONObjIterator{elem.Obj()});
}
}
// Save the measurement count for the owned bucket.
_numberOfMeasurements = computeMeasurementCount(timeFieldElem.objsize());
}
void BucketUnpacker::setBucketSpecAndBehavior(BucketSpec&& bucketSpec, Behavior behavior) {
_includeMetaField = eraseMetaFromFieldSetAndDetermineIncludeMeta(behavior, &bucketSpec);
_includeTimeField = determineIncludeTimeField(behavior, &bucketSpec);
_unpackerBehavior = behavior;
_spec = std::move(bucketSpec);
}
Document BucketUnpacker::getNext() {
tassert(5422100, "'getNext()' was called after the bucket has been exhausted", hasNext());
auto measurement = MutableDocument{};
auto&& timeElem = _timeFieldIter->next();
if (_includeTimeField) {
measurement.addField(_spec.timeField, Value{timeElem});
}
// Includes metaField when we're instructed to do so and metaField value exists.
if (_includeMetaField && _metaValue) {
measurement.addField(*_spec.metaField, Value{_metaValue});
}
auto& currentIdx = timeElem.fieldNameStringData();
for (auto&& [colName, colIter] : _fieldIters) {
if (auto&& elem = *colIter; colIter.more() && elem.fieldNameStringData() == currentIdx) {
measurement.addField(colName, Value{elem});
colIter.advance(elem);
}
}
return measurement.freeze();
}
Document BucketUnpacker::extractSingleMeasurement(int j) {
tassert(5422101,
"'extractSingleMeasurment' expects j to be greater than or equal to zero and less than "
"or equal to the number of measurements in a bucket",
j >= 0 && j < _numberOfMeasurements);
auto measurement = MutableDocument{};
auto rowKey = std::to_string(j);
auto targetIdx = StringData{rowKey};
auto&& dataRegion = _bucket.getField(timeseries::kBucketDataFieldName).Obj();
if (_includeMetaField && !_metaValue.isNull()) {
measurement.addField(*_spec.metaField, Value{_metaValue});
}
for (auto&& dataElem : dataRegion) {
auto colName = dataElem.fieldNameStringData();
if (!determineIncludeField(colName, _unpackerBehavior, _spec)) {
continue;
}
auto value = dataElem[targetIdx];
if (value) {
measurement.addField(dataElem.fieldNameStringData(), Value{value});
}
}
return measurement.freeze();
}
DocumentSourceInternalUnpackBucket::DocumentSourceInternalUnpackBucket(
const boost::intrusive_ptr<ExpressionContext>& expCtx, BucketUnpacker bucketUnpacker)
: DocumentSource(kStageName, expCtx), _bucketUnpacker(std::move(bucketUnpacker)) {}
boost::intrusive_ptr<DocumentSource> DocumentSourceInternalUnpackBucket::createFromBson(
BSONElement specElem, const boost::intrusive_ptr<ExpressionContext>& expCtx) {
uassert(5346500,
"$_internalUnpackBucket specification must be an object",
specElem.type() == Object);
// If neither "include" nor "exclude" is specified, the default is "exclude": [] and
// if that's the case, no field will be added to 'bucketSpec.fieldSet' in the for-loop below.
BucketUnpacker::Behavior unpackerBehavior = BucketUnpacker::Behavior::kExclude;
BucketSpec bucketSpec;
auto hasIncludeExclude = false;
std::vector<std::string> fields;
for (auto&& elem : specElem.embeddedObject()) {
auto fieldName = elem.fieldNameStringData();
if (fieldName == "include" || fieldName == "exclude") {
uassert(5408000,
"The $_internalUnpackBucket stage expects at most one of include/exclude "
"parameters to be specified",
!hasIncludeExclude);
uassert(5346501,
"include or exclude field must be an array",
elem.type() == BSONType::Array);
for (auto&& elt : elem.embeddedObject()) {
uassert(5346502,
"include or exclude field element must be a string",
elt.type() == BSONType::String);
auto field = elt.valueStringData();
uassert(5346503,
"include or exclude field element must be a single-element field path",
field.find('.') == std::string::npos);
bucketSpec.fieldSet.emplace(field);
}
unpackerBehavior = fieldName == "include" ? BucketUnpacker::Behavior::kInclude
: BucketUnpacker::Behavior::kExclude;
hasIncludeExclude = true;
} else if (fieldName == timeseries::kTimeFieldName) {
uassert(5346504, "timeField field must be a string", elem.type() == BSONType::String);
bucketSpec.timeField = elem.str();
} else if (fieldName == timeseries::kMetaFieldName) {
uassert(5346505,
str::stream() << "metaField field must be a string, got: " << elem.type(),
elem.type() == BSONType::String);
bucketSpec.metaField = elem.str();
} else {
uasserted(5346506,
str::stream()
<< "unrecognized parameter to $_internalUnpackBucket: " << fieldName);
}
}
uassert(5346508,
"The $_internalUnpackBucket stage requires a timeField parameter",
specElem[timeseries::kTimeFieldName].ok());
auto includeTimeField = determineIncludeTimeField(unpackerBehavior, &bucketSpec);
auto includeMetaField =
eraseMetaFromFieldSetAndDetermineIncludeMeta(unpackerBehavior, &bucketSpec);
return make_intrusive<DocumentSourceInternalUnpackBucket>(
expCtx,
BucketUnpacker{
std::move(bucketSpec), unpackerBehavior, includeTimeField, includeMetaField});
}
void DocumentSourceInternalUnpackBucket::serializeToArray(
std::vector<Value>& array, boost::optional<ExplainOptions::Verbosity> explain) const {
MutableDocument out;
auto behavior =
_bucketUnpacker.behavior() == BucketUnpacker::Behavior::kInclude ? kInclude : kExclude;
auto&& spec = _bucketUnpacker.bucketSpec();
std::vector<Value> fields;
for (auto&& field : spec.fieldSet) {
fields.emplace_back(field);
}
out.addField(behavior, Value{fields});
out.addField(timeseries::kTimeFieldName, Value{spec.timeField});
if (spec.metaField) {
out.addField(timeseries::kMetaFieldName, Value{*spec.metaField});
}
if (!explain) {
array.push_back(Value(DOC(getSourceName() << out.freeze())));
if (_sampleSize) {
auto sampleSrc = DocumentSourceSample::create(pExpCtx, *_sampleSize);
sampleSrc->serializeToArray(array);
}
} else {
if (_sampleSize) {
out.addField("sample", Value{static_cast<long long>(*_sampleSize)});
out.addField("bucketMaxCount", Value{_bucketMaxCount});
}
array.push_back(Value(DOC(getSourceName() << out.freeze())));
}
}
DocumentSource::GetNextResult
DocumentSourceInternalUnpackBucket::sampleUniqueMeasurementFromBuckets() {
const auto kMaxAttempts = 100;
for (auto attempt = 0; attempt < kMaxAttempts; ++attempt) {
auto randResult = pSource->getNext();
switch (randResult.getStatus()) {
case GetNextResult::ReturnStatus::kAdvanced: {
auto bucket = randResult.getDocument().toBson();
_bucketUnpacker.reset(std::move(bucket));
auto& prng = pExpCtx->opCtx->getClient()->getPrng();
auto j = prng.nextInt64(_bucketMaxCount);
if (j < _bucketUnpacker.numberOfMeasurements()) {
auto sampledDocument = _bucketUnpacker.extractSingleMeasurement(j);
auto bucketId = _bucketUnpacker.bucket()[timeseries::kBucketIdFieldName];
auto bucketIdMeasurementIdxKey = SampledMeasurementKey{bucketId.OID(), j};
if (_seenSet.insert(std::move(bucketIdMeasurementIdxKey)).second) {
_nSampledSoFar++;
return sampledDocument;
} else {
LOGV2_DEBUG(
5422102,
1,
"$_internalUnpackBucket optimized for sample saw duplicate measurement",
"measurementIndex"_attr = j,
"bucketId"_attr = bucketId);
}
}
break;
}
case GetNextResult::ReturnStatus::kPauseExecution: {
// This state should never be reached since the input stage is a random cursor.
MONGO_UNREACHABLE;
}
case GetNextResult::ReturnStatus::kEOF: {
return randResult;
}
}
}
uasserted(5422103,
str::stream()
<< "$_internalUnpackBucket stage could not find a non-duplicate document after "
<< kMaxAttempts
<< " attempts while using a random cursor. This is likely a "
"sporadic failure, please try again");
}
DocumentSource::GetNextResult DocumentSourceInternalUnpackBucket::doGetNext() {
// If the '_sampleSize' member is present, then the stage will produce randomly sampled
// documents from buckets.
if (_sampleSize) {
if (_nSampledSoFar >= _sampleSize) {
return GetNextResult::makeEOF();
}
return sampleUniqueMeasurementFromBuckets();
}
// Otherwise, fallback to unpacking every measurement in all buckets until the child stage is
// exhausted.
if (_bucketUnpacker.hasNext()) {
return _bucketUnpacker.getNext();
}
auto nextResult = pSource->getNext();
if (nextResult.isAdvanced()) {
auto bucket = nextResult.getDocument().toBson();
_bucketUnpacker.reset(std::move(bucket));
uassert(5346509,
str::stream() << "A bucket with _id "
<< _bucketUnpacker.bucket()[timeseries::kBucketIdFieldName].toString()
<< " contains an empty data region",
_bucketUnpacker.hasNext());
return _bucketUnpacker.getNext();
}
return nextResult;
}
void DocumentSourceInternalUnpackBucket::internalizeProject(const BSONObj& project,
bool isInclusion) {
// 'fields' are the top-level fields to be included/excluded by the unpacker. We handle the
// special case of _id, which may be excluded in an inclusion $project (or vice versa), here.
auto fields = project.getFieldNames<std::set<std::string>>();
if (auto elt = project.getField("_id"); (elt.isBoolean() && elt.Bool() != isInclusion) ||
(elt.isNumber() && (elt.Int() == 1) != isInclusion)) {
fields.erase("_id");
}
// Update '_bucketUnpacker' state with the new fields and behavior.
auto spec = _bucketUnpacker.bucketSpec();
spec.fieldSet = std::move(fields);
_bucketUnpacker.setBucketSpecAndBehavior(std::move(spec),
isInclusion ? BucketUnpacker::Behavior::kInclude
: BucketUnpacker::Behavior::kExclude);
}
std::pair<BSONObj, bool> DocumentSourceInternalUnpackBucket::extractOrBuildProjectToInternalize(
Pipeline::SourceContainer::iterator itr, Pipeline::SourceContainer* container) const {
if (std::next(itr) == container->end() || !_bucketUnpacker.bucketSpec().fieldSet.empty()) {
// There is no project to internalize or there are already fields being included/excluded.
return {BSONObj{}, false};
}
// Check for a viable inclusion $project after the $_internalUnpackBucket.
auto [existingProj, isInclusion] = getIncludeExcludeProjectAndType(std::next(itr)->get());
if (isInclusion && !existingProj.isEmpty() && canInternalizeProjectObj(existingProj)) {
container->erase(std::next(itr));
return {existingProj, isInclusion};
}
// Attempt to get an inclusion $project representing the root-level dependencies of the pipeline
// after the $_internalUnpackBucket. If this $project is not empty, then the dependency set was
// finite.
Pipeline::SourceContainer restOfPipeline(std::next(itr), container->end());
auto deps = Pipeline::getDependenciesForContainer(pExpCtx, restOfPipeline, boost::none);
if (auto dependencyProj =
deps.toProjectionWithoutMetadata(DepsTracker::TruncateToRootLevel::yes);
!dependencyProj.isEmpty()) {
return {dependencyProj, true};
}
// Check for a viable exclusion $project after the $_internalUnpackBucket.
if (!existingProj.isEmpty() && canInternalizeProjectObj(existingProj)) {
container->erase(std::next(itr));
return {existingProj, isInclusion};
}
return {BSONObj{}, false};
}
std::unique_ptr<MatchExpression> createComparisonPredicate(
const ComparisonMatchExpression* matchExpr, const BucketSpec& bucketSpec) {
auto path = matchExpr->path();
auto rhs = matchExpr->getData();
// The control field's min and max are chosen using a field-order insensitive comparator, while
// MatchExpressions use a comparator that treats field-order as significant. Because of this we
// will not perform this optimization on queries with operands of compound types.
if (rhs.type() == BSONType::Object || rhs.type() == BSONType::Array) {
return nullptr;
}
// MatchExpressions have special comparison semantics regarding null, in that {$eq: null} will
// match all documents where the field is either null or missing. Because this is different
// from both the comparison semantics that InternalExprComparison expressions and the control's
// min and max fields use, we will not perform this optimization on queries with null operands.
if (rhs.type() == BSONType::jstNULL) {
return nullptr;
}
// We must avoid mapping predicates on the meta field onto the control field.
if (bucketSpec.metaField &&
(path == bucketSpec.metaField.get() ||
expression::isPathPrefixOf(bucketSpec.metaField.get(), path))) {
return nullptr;
}
switch (matchExpr->matchType()) {
case MatchExpression::EQ: {
auto andMatchExpr = std::make_unique<AndMatchExpression>();
andMatchExpr->add(std::make_unique<InternalExprLTEMatchExpression>(
str::stream() << timeseries::kControlMinFieldNamePrefix << path, rhs));
andMatchExpr->add(std::make_unique<InternalExprGTEMatchExpression>(
str::stream() << timeseries::kControlMaxFieldNamePrefix << path, rhs));
if (path == bucketSpec.timeField) {
andMatchExpr->add(std::make_unique<LTEMatchExpression>(
timeseries::kBucketIdFieldName, constructObjectIdValue(matchExpr)));
}
return andMatchExpr;
}
case MatchExpression::GT: {
return std::make_unique<InternalExprGTMatchExpression>(
str::stream() << timeseries::kControlMaxFieldNamePrefix << path, rhs);
}
case MatchExpression::GTE: {
return std::make_unique<InternalExprGTEMatchExpression>(
str::stream() << timeseries::kControlMaxFieldNamePrefix << path, rhs);
}
case MatchExpression::LT: {
auto controlPred = std::make_unique<InternalExprLTMatchExpression>(
str::stream() << timeseries::kControlMinFieldNamePrefix << path, rhs);
if (path == bucketSpec.timeField) {
auto andMatchExpr = std::make_unique<AndMatchExpression>();
andMatchExpr->add(std::make_unique<LTMatchExpression>(
timeseries::kBucketIdFieldName, constructObjectIdValue(matchExpr)));
andMatchExpr->add(std::move(controlPred));
return andMatchExpr;
}
return controlPred;
}
case MatchExpression::LTE: {
auto controlPred = std::make_unique<InternalExprLTEMatchExpression>(
str::stream() << timeseries::kControlMinFieldNamePrefix << path, rhs);
if (path == bucketSpec.timeField) {
auto andMatchExpr = std::make_unique<AndMatchExpression>();
andMatchExpr->add(std::make_unique<LTEMatchExpression>(
timeseries::kBucketIdFieldName, constructObjectIdValue(matchExpr)));
andMatchExpr->add(std::move(controlPred));
return andMatchExpr;
}
return controlPred;
}
default:
MONGO_UNREACHABLE_TASSERT(5348302);
}
MONGO_UNREACHABLE_TASSERT(5348303);
}
std::unique_ptr<MatchExpression>
DocumentSourceInternalUnpackBucket::createPredicatesOnBucketLevelField(
const MatchExpression* matchExpr) const {
if (matchExpr->matchType() == MatchExpression::AND) {
auto nextAnd = static_cast<const AndMatchExpression*>(matchExpr);
auto andMatchExpr = std::make_unique<AndMatchExpression>();
for (size_t i = 0; i < nextAnd->numChildren(); i++) {
if (auto child = createPredicatesOnBucketLevelField(nextAnd->getChild(i))) {
andMatchExpr->add(std::move(child));
}
}
if (andMatchExpr->numChildren() > 0) {
return andMatchExpr;
}
} else if (ComparisonMatchExpression::isComparisonMatchExpression(matchExpr)) {
return createComparisonPredicate(static_cast<const ComparisonMatchExpression*>(matchExpr),
_bucketUnpacker.bucketSpec());
}
return nullptr;
}
std::pair<boost::intrusive_ptr<DocumentSourceMatch>, boost::intrusive_ptr<DocumentSourceMatch>>
DocumentSourceInternalUnpackBucket::splitMatchOnMetaAndRename(
boost::intrusive_ptr<DocumentSourceMatch> match) {
if (auto&& metaField = _bucketUnpacker.bucketSpec().metaField) {
return std::move(*match).extractMatchOnFieldsAndRemainder(
{*metaField}, {{*metaField, timeseries::kBucketMetaFieldName.toString()}});
}
return {nullptr, match};
}
Pipeline::SourceContainer::iterator DocumentSourceInternalUnpackBucket::doOptimizeAt(
Pipeline::SourceContainer::iterator itr, Pipeline::SourceContainer* container) {
invariant(*itr == this);
if (std::next(itr) == container->end()) {
return container->end();
}
// Before any other rewrites for the current stage, consider reordering with $sort.
if (auto sortPtr = dynamic_cast<DocumentSourceSort*>(std::next(itr)->get())) {
if (auto metaField = _bucketUnpacker.bucketSpec().metaField) {
if (checkMetadataSortReorder(sortPtr->getSortKeyPattern(), metaField.get())) {
// We have a sort on metadata field following this stage. Reorder the two stages
// and return a pointer to the preceding stage.
auto sortForReorder = createMetadataSortForReorder(*sortPtr);
// Reorder sort and current doc.
*std::next(itr) = std::move(*itr);
*itr = std::move(sortForReorder);
if (itr == container->begin()) {
// Try to optimize the current stage again.
return std::next(itr);
} else {
// Try to optimize the previous stage against $sort.
return std::prev(itr);
}
}
}
}
// Optimize the pipeline after the $unpackBucket.
optimizeEndOfPipeline(itr, container);
{
// Check if the rest of the pipeline needs any fields. For example we might only be
// interested in $count.
auto deps = Pipeline::getDependenciesForContainer(
pExpCtx, Pipeline::SourceContainer{std::next(itr), container->end()}, boost::none);
if (deps.hasNoRequirements()) {
_bucketUnpacker.setBucketSpecAndBehavior({_bucketUnpacker.bucketSpec().timeField,
_bucketUnpacker.bucketSpec().metaField,
{}},
BucketUnpacker::Behavior::kInclude);
// Keep going for next optimization.
}
}
if (auto nextMatch = dynamic_cast<DocumentSourceMatch*>((*std::next(itr)).get())) {
// Attempt to push predicates on the metaField past $_internalUnpackBucket.
auto [metaMatch, remainingMatch] = splitMatchOnMetaAndRename(nextMatch);
// 'metaMatch' is safe to move before $_internalUnpackBucket.
if (metaMatch) {
container->insert(itr, metaMatch);
}
// The old $match can be removed and potentially replaced with 'remainingMatch'.
container->erase(std::next(itr));
if (remainingMatch) {
container->insert(std::next(itr), remainingMatch);
// Attempt to map predicates on bucketed fields to predicates on the control field.
if (auto match =
createPredicatesOnBucketLevelField(remainingMatch->getMatchExpression())) {
BSONObjBuilder bob;
match->serialize(&bob);
container->insert(itr, DocumentSourceMatch::create(bob.obj(), pExpCtx));
}
}
}
// Attempt to build a $project based on dependency analysis or extract one from the pipeline. We
// can internalize the result so we can handle projections during unpacking.
if (auto [project, isInclusion] = extractOrBuildProjectToInternalize(itr, container);
!project.isEmpty()) {
internalizeProject(project, isInclusion);
}
// Optimize the prefix of the pipeline, now that all optimizations have been completed.
optimizePrefix(itr, container);
return container->end();
}
} // namespace mongo
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