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/**
* Copyright (C) 2014 MongoDB Inc.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License, version 3,
* as published by the Free Software Foundation.
*
* 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
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
* 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 GNU Affero General 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.
*/
/**
* This file tests db/query/plan_ranker.cpp and db/query/multi_plan_runner.cpp.
*/
#include "mongo/client/dbclientcursor.h"
#include "mongo/db/catalog/collection.h"
#include "mongo/db/catalog/database.h"
#include "mongo/db/exec/multi_plan.h"
#include "mongo/db/index/index_descriptor.h"
#include "mongo/db/instance.h"
#include "mongo/db/json.h"
#include "mongo/db/operation_context_impl.h"
#include "mongo/db/query/get_executor.h"
#include "mongo/db/query/qlog.h"
#include "mongo/db/query/query_knobs.h"
#include "mongo/db/query/query_planner.h"
#include "mongo/db/query/query_planner_test_lib.h"
#include "mongo/db/query/stage_builder.h"
#include "mongo/dbtests/dbtests.h"
namespace mongo {
// How we access the external setParameter testing bool.
extern bool internalQueryForceIntersectionPlans;
} // namespace mongo
namespace PlanRankingTests {
static const char* ns = "unittests.PlanRankingTests";
class PlanRankingTestBase {
public:
PlanRankingTestBase()
: _internalQueryForceIntersectionPlans(internalQueryForceIntersectionPlans),
_client(&_txn) {
Client::WriteContext ctx(&_txn, ns);
_client.dropCollection(ns);
}
virtual ~PlanRankingTestBase() {
// Restore external setParameter testing bool.
internalQueryForceIntersectionPlans = _internalQueryForceIntersectionPlans;
}
void insert(const BSONObj& obj) {
Client::WriteContext ctx(&_txn, ns);
_client.insert(ns, obj);
}
void addIndex(const BSONObj& obj) {
Client::WriteContext ctx(&_txn, ns);
_client.ensureIndex(ns, obj);
}
/**
* Use the MultiPlanRunner to pick the best plan for the query 'cq'. Goes through
* normal planning to generate solutions and feeds them to the MPR.
*
* Takes ownership of 'cq'. Caller DOES NOT own the returned QuerySolution*.
*/
QuerySolution* pickBestPlan(CanonicalQuery* cq) {
Client::ReadContext ctx(&_txn, ns);
Collection* collection = ctx.ctx().db()->getCollection(&_txn, ns);
QueryPlannerParams plannerParams;
fillOutPlannerParams(collection, cq, &plannerParams);
// Turn this off otherwise it pops up in some plans.
plannerParams.options &= ~QueryPlannerParams::KEEP_MUTATIONS;
// Plan.
vector<QuerySolution*> solutions;
Status status = QueryPlanner::plan(*cq, plannerParams, &solutions);
ASSERT(status.isOK());
ASSERT_GREATER_THAN_OR_EQUALS(solutions.size(), 1U);
// Fill out the MPR.
_mps.reset(new MultiPlanStage(collection, cq));
WorkingSet* ws = new WorkingSet();
// Put each solution from the planner into the MPR.
for (size_t i = 0; i < solutions.size(); ++i) {
PlanStage* root;
ASSERT(StageBuilder::build(collection, *solutions[i], ws, &root));
// Takes ownership of all arguments.
_mps->addPlan(solutions[i], root, ws);
}
_mps->pickBestPlan(); // This is what sets a backup plan, should we test for it.
ASSERT(_mps->bestPlanChosen());
size_t bestPlanIdx = _mps->bestPlanIdx();
ASSERT_LESS_THAN(bestPlanIdx, solutions.size());
// And return a pointer to the best solution.
return _mps->bestSolution();
}
/**
* Was a backup plan picked during the ranking process?
*/
bool hasBackupPlan() const {
ASSERT(NULL != _mps.get());
return _mps->hasBackupPlan();
}
protected:
// A large number, which must be larger than the number of times
// candidate plans are worked by the multi plan runner. Used for
// determining the number of documents in the tests below.
static const int N;
OperationContextImpl _txn;
private:
// Holds the value of global "internalQueryForceIntersectionPlans" setParameter flag.
// Restored at end of test invocation regardless of test result.
bool _internalQueryForceIntersectionPlans;
scoped_ptr<MultiPlanStage> _mps;
DBDirectClient _client;
};
// static
const int PlanRankingTestBase::N = internalQueryPlanEvaluationWorks + 1000;
/**
* Test that the "prefer ixisect" parameter works.
*/
class PlanRankingIntersectOverride : public PlanRankingTestBase {
public:
void run() {
// 'a' is very selective, 'b' is not.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << i << "b" << 1));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Run the query {a:4, b:1}.
CanonicalQuery* cq;
verify(CanonicalQuery::canonicalize(ns, BSON("a" << 100 << "b" << 1), &cq).isOK());
ASSERT(NULL != cq);
// {a:100} is super selective so choose that.
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: {b:1}, node: {ixscan: {pattern: {a: 1}}}}}",
soln->root.get()));
// Turn on the "force intersect" option.
// This will be reverted by PlanRankingTestBase's destructor when the test completes.
internalQueryForceIntersectionPlans = true;
// And run the same query again.
ASSERT(CanonicalQuery::canonicalize(ns, BSON("a" << 100 << "b" << 1), &cq).isOK());
// With the "ranking picks ixisect always" option we pick an intersection plan that uses
// both the {a:1} and {b:1} indices even though it performs poorly.
// Takes ownership of cq.
soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: null, node: {andSorted: {nodes: ["
"{ixscan: {filter: null, pattern: {a:1}}},"
"{ixscan: {filter: null, pattern: {b:1}}}]}}}}",
soln->root.get()));
}
};
/**
* Test that a hashed AND solution plan is picked along with a non-blocking backup solution.
*/
class PlanRankingIntersectWithBackup : public PlanRankingTestBase {
public:
void run() {
// 'a' is very selective, 'b' is not.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << i << "b" << 1));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Run the query {a:1, b:{$gt:1}.
CanonicalQuery* cq;
verify(CanonicalQuery::canonicalize(ns, BSON("a" << 1 << "b" << BSON("$gt" << 1)),
&cq).isOK());
ASSERT(NULL != cq);
// Turn on the "force intersect" option.
// This will be reverted by PlanRankingTestBase's destructor when the test completes.
internalQueryForceIntersectionPlans = true;
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: null, node: {andHash: {nodes: ["
"{ixscan: {filter: null, pattern: {a:1}}},"
"{ixscan: {filter: null, pattern: {b:1}}}]}}}}",
soln->root.get()));
// Confirm that a backup plan is available.
ASSERT(hasBackupPlan());
}
};
/**
* Two plans hit EOF at the same time, but one is covered. Make sure that we prefer the covered
* plan.
*/
class PlanRankingPreferCovered : public PlanRankingTestBase {
public:
void run() {
// Insert data {a:i, b:i}. Index {a:1} and {a:1, b:1}, query on 'a', projection on 'a'
// and 'b'. Should prefer the second index as we can pull the 'b' data out.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << i << "b" << i));
}
addIndex(BSON("a" << 1));
addIndex(BSON("a" << 1 << "b" << 1));
// Query for a==27 with projection that wants 'a' and 'b'. BSONObj() is for sort.
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
BSON("a" << 27),
BSONObj(),
BSON("_id" << 0 << "a" << 1 << "b" << 1),
&cq).isOK());
ASSERT(NULL != cq);
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
// Prefer the fully covered plan.
ASSERT(QueryPlannerTestLib::solutionMatches(
"{proj: {spec: {_id:0, a:1, b:1}, node: {ixscan: {pattern: {a: 1, b:1}}}}}",
soln->root.get()));
}
};
/**
* No plan produces any results or hits EOF. In this case we should never choose an index
* intersection solution.
*/
class PlanRankingAvoidIntersectIfNoResults : public PlanRankingTestBase {
public:
void run() {
// We insert lots of copies of {a:1, b:1, c: 20}. We have the indices {a:1} and {b:1},
// and the query is {a:1, b:1, c: 999}. No data that matches the query but we won't
// know that during plan ranking. We don't want to choose an intersection plan here.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 1 << "b" << 1 << "c" << 20));
}
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// There is no data that matches this query but we don't know that until EOF.
CanonicalQuery* cq;
BSONObj queryObj = BSON("a" << 1 << "b" << 1 << "c" << 99);
ASSERT(CanonicalQuery::canonicalize(ns, queryObj, &cq).isOK());
ASSERT(NULL != cq);
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
// Anti-prefer the intersection plan.
bool bestIsScanOverA = QueryPlannerTestLib::solutionMatches(
"{fetch: {node: {ixscan: {pattern: {a: 1}}}}}",
soln->root.get());
bool bestIsScanOverB = QueryPlannerTestLib::solutionMatches(
"{fetch: {node: {ixscan: {pattern: {b: 1}}}}}",
soln->root.get());
ASSERT(bestIsScanOverA || bestIsScanOverB);
}
};
/**
* No plan produces any results or hits EOF. In this case we should prefer covered solutions to
* non-covered solutions.
*/
class PlanRankingPreferCoveredEvenIfNoResults : public PlanRankingTestBase {
public:
void run() {
// We insert lots of copies of {a:1, b:1}. We have the indices {a:1} and {a:1, b:1},
// the query is for a doc that doesn't exist, but there is a projection over 'a' and
// 'b'. We should prefer the index that provides a covered query.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 1 << "b" << 1));
}
addIndex(BSON("a" << 1));
addIndex(BSON("a" << 1 << "b" << 1));
// There is no data that matches this query ({a:2}). Both scans will hit EOF before
// returning any data.
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
BSON("a" << 2),
BSONObj(),
BSON("_id" << 0 << "a" << 1 << "b" << 1),
&cq).isOK());
ASSERT(NULL != cq);
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
// Prefer the fully covered plan.
ASSERT(QueryPlannerTestLib::solutionMatches(
"{proj: {spec: {_id:0, a:1, b:1}, node: {ixscan: {pattern: {a: 1, b:1}}}}}",
soln->root.get()));
}
};
/**
* We have an index on "a" which is somewhat selective and an index on "b" which is highly
* selective (will cause an immediate EOF). Make sure that a query with predicates on both "a"
* and "b" will use the index on "b".
*/
class PlanRankingPreferImmediateEOF : public PlanRankingTestBase {
public:
void run() {
// 'a' is very selective, 'b' is not.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << i << "b" << 1));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Run the query {a:N+1, b:1}. (No such document.)
CanonicalQuery* cq;
verify(CanonicalQuery::canonicalize(ns, BSON("a" << N + 1 << "b" << 1), &cq).isOK());
ASSERT(NULL != cq);
// {a: 100} is super selective so choose that.
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: {b:1}, node: {ixscan: {pattern: {a: 1}}}}}",
soln->root.get()));
}
};
/**
* We have an index on _id and a query over _id with a sort. Ensure that we don't pick a
* collscan as the best plan even though the _id-scanning solution doesn't produce any results.
*/
class PlanRankingNoCollscan : public PlanRankingTestBase {
public:
void run() {
for (int i = 0; i < N; ++i) {
insert(BSON("_id" << i));
}
addIndex(BSON("_id" << 1));
// Run a query with a sort. The blocking sort won't produce any data during the
// evaluation period.
CanonicalQuery* cq;
BSONObj queryObj = BSON("_id" << BSON("$gte" << 20 << "$lte" << 200));
BSONObj sortObj = BSON("c" << 1);
BSONObj projObj = BSONObj();
ASSERT(CanonicalQuery::canonicalize(ns,
queryObj,
sortObj,
projObj,
&cq).isOK());
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
// The best must not be a collscan.
ASSERT(QueryPlannerTestLib::solutionMatches(
"{sort: {pattern: {c: 1}, limit: 0, node: {"
"fetch: {filter: null, node: "
"{ixscan: {filter: null, pattern: {_id: 1}}}}}}}}",
soln->root.get()));
}
};
/**
* No indices are available, output a collscan.
*/
class PlanRankingCollscan : public PlanRankingTestBase {
public:
void run() {
// Insert data for which we have no index.
for (int i = 0; i < N; ++i) {
insert(BSON("foo" << i));
}
// Look for A Space Odyssey.
CanonicalQuery* cq;
verify(CanonicalQuery::canonicalize(ns, BSON("foo" << 2001), &cq).isOK());
ASSERT(NULL != cq);
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
// The best must be a collscan.
ASSERT(QueryPlannerTestLib::solutionMatches(
"{cscan: {dir: 1, filter: {foo: 2001}}}",
soln->root.get()));
}
};
/**
* Index intersection solutions can be covered when single-index solutions
* are not. If the single-index solutions need to do a lot of fetching,
* then ixisect should win.
*/
class PlanRankingIxisectCovered : public PlanRankingTestBase {
public:
void run() {
// Neither 'a' nor 'b' is selective.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 1 << "b" << 1));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Query {a:1, b:1}, and project out all fields other than 'a' and 'b'.
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
BSON("a" << 1 << "b" << 1),
BSONObj(),
BSON("_id" << 0 << "a" << 1 << "b" << 1),
&cq).isOK());
ASSERT(NULL != cq);
// We should choose an ixisect plan because it requires fewer fetches.
// Takes ownership of cq.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{proj: {spec: {_id:0,a:1,b:1}, node: {andSorted: {nodes: ["
"{ixscan: {filter: null, pattern: {a:1}}},"
"{ixscan: {filter: null, pattern: {b:1}}}]}}}}",
soln->root.get()));
}
};
/**
* Use the same data, same indices, and same query as the previous
* test case, except without the projection. The query is not covered
* by the index in this case, which means that there is no advantage
* to an index intersection solution.
*/
class PlanRankingIxisectNonCovered : public PlanRankingTestBase {
public:
void run() {
// Neither 'a' nor 'b' is selective.
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 1 << "b" << 1));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Query {a:1, b:1}.
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
BSON("a" << 1 << "b" << 1),
&cq).isOK());
ASSERT(NULL != cq);
// The intersection is large, and ixisect does not make the
// query covered. We should NOT choose an intersection plan.
QuerySolution* soln = pickBestPlan(cq);
bool bestIsScanOverA = QueryPlannerTestLib::solutionMatches(
"{fetch: {node: {ixscan: {pattern: {a: 1}}}}}",
soln->root.get());
bool bestIsScanOverB = QueryPlannerTestLib::solutionMatches(
"{fetch: {node: {ixscan: {pattern: {b: 1}}}}}",
soln->root.get());
ASSERT(bestIsScanOverA || bestIsScanOverB);
}
};
/**
* Index intersection solutions may require fewer fetches even if it does not make the
* query covered. The ixisect plan will scan as many index keys as the union of the two
* single index plans, but only needs to retrieve full documents for the intersection
* of the two plans---this could mean fewer fetches!
*/
class PlanRankingNonCoveredIxisectFetchesLess : public PlanRankingTestBase {
public:
void run() {
// Set up data so that the following conditions hold:
// 1) Documents matching {a: 1} are of high cardinality.
// 2) Documents matching {b: 1} are of high cardinality.
// 3) Documents matching {a: 1, b: 1} are of low cardinality---
// the intersection is small.
// 4) At least one of the documents in the intersection is
// returned during the trial period.
insert(BSON("a" << 1 << "b" << 1));
for (int i = 0; i < N/2; ++i) {
insert(BSON("a" << 1 << "b" << 2));
}
for (int i = 0; i < N/2; ++i) {
insert(BSON("a" << 2 << "b" << 1));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Neither the predicate on 'b' nor the predicate on 'a' is
// very selective: both retrieve about half the documents.
// However, the intersection is very small, which makes
// the intersection plan desirable.
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
fromjson("{a: 1, b: 1}"),
&cq).isOK());
ASSERT(NULL != cq);
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: null, node: {andSorted: {nodes: ["
"{ixscan: {filter: null, pattern: {a:1}}},"
"{ixscan: {filter: null, pattern: {b:1}}}]}}}}",
soln->root.get()));
}
};
/**
* If the intersection is small, an AND_SORTED plan may be able to
* hit EOF before the single index plans.
*/
class PlanRankingIxisectHitsEOFFirst : public PlanRankingTestBase {
public:
void run() {
// Set up the data so that for the query {a: 1, b: 1}, the
// intersection is empty. The single index plans have to do
// more fetching from disk in order to determine that the result
// set is empty. As a result, the intersection plan hits EOF first.
for (int i = 0; i < 30; ++i) {
insert(BSON("a" << 1 << "b" << 2));
}
for (int i = 0; i < 30; ++i) {
insert(BSON("a" << 2 << "b" << 1));
}
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 2 << "b" << 2));
}
// Add indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
fromjson("{a: 1, b: 1}"),
&cq).isOK());
ASSERT(NULL != cq);
// Choose the index intersection plan.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: null, node: {andSorted: {nodes: ["
"{ixscan: {filter: null, pattern: {a:1}}},"
"{ixscan: {filter: null, pattern: {b:1}}}]}}}}",
soln->root.get()));
}
};
/**
* If we query on 'a', 'b', and 'c' with indices on all three fields,
* then there are three possible size-2 index intersections to consider.
* Make sure we choose the right one.
*/
class PlanRankingChooseBetweenIxisectPlans : public PlanRankingTestBase {
public:
void run() {
// Set up the data so that for the query {a: 1, b: 1, c: 1}, the intersection
// between 'b' and 'c' is small, and the other intersections are larger.
for (int i = 0; i < 10; ++i) {
insert(BSON("a" << 1 << "b" << 1 << "c" << 1));
}
for (int i = 0; i < 10; ++i) {
insert(BSON("a" << 2 << "b" << 1 << "c" << 1));
}
for (int i = 0; i < N/2; ++i) {
insert(BSON("a" << 1 << "b" << 1 << "c" << 2));
insert(BSON("a" << 1 << "b" << 2 << "c" << 1));
}
// Add indices on 'a', 'b', and 'c'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
addIndex(BSON("c" << 1));
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
fromjson("{a: 1, b: 1, c: 1}"),
&cq).isOK());
ASSERT(NULL != cq);
// Intersection between 'b' and 'c' should hit EOF while the
// other plans are busy fetching documents.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: {a:1}, node: {andSorted: {nodes: ["
"{ixscan: {filter: null, pattern: {b:1}}},"
"{ixscan: {filter: null, pattern: {c:1}}}]}}}}",
soln->root.get()));
}
};
/**
* When no other information is available, prefer solutions without
* a blocking sort stage.
*/
class PlanRankingAvoidBlockingSort : public PlanRankingTestBase {
public:
void run() {
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 1 << "d" << i));
}
// The index {d: 1, e: 1} provides the desired sort order,
// while index {a: 1, b: 1} can be used to answer the
// query predicate, but does not provide the sort.
addIndex(BSON("a" << 1 << "b" << 1));
addIndex(BSON("d" << 1 << "e" << 1));
// Query: find({a: 1}).sort({d: 1})
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
BSON("a" << 1),
BSON("d" << 1), // sort
BSONObj(), // projection
&cq).isOK());
ASSERT(NULL != cq);
// No results will be returned during the trial period,
// so we expect to choose {d: 1, e: 1}, as it allows us
// to avoid the sort stage.
QuerySolution* soln = pickBestPlan(cq);
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {filter: {a:1}, node: "
"{ixscan: {filter: null, pattern: {d:1,e:1}}}}}",
soln->root.get()));
}
};
/**
* Make sure we run candidate plans for long enough when none of the
* plans are producing results.
*/
class PlanRankingWorkPlansLongEnough : public PlanRankingTestBase {
public:
void run() {
for (int i = 0; i < N; ++i) {
insert(BSON("a" << 1));
insert(BSON("a" << 1 << "b" << 1 << "c" << i));
}
// Indices on 'a' and 'b'.
addIndex(BSON("a" << 1));
addIndex(BSON("b" << 1));
// Solutions using either 'a' or 'b' will take a long time to start producing
// results. However, an index scan on 'b' will start producing results sooner
// than an index scan on 'a'.
CanonicalQuery* cq;
ASSERT(CanonicalQuery::canonicalize(ns,
fromjson("{a: 1, b: 1, c: {$gte: 5000}}"),
&cq).isOK());
ASSERT(NULL != cq);
// Use index on 'b'.
QuerySolution* soln = pickBestPlan(cq);
std::cerr << "PlanRankingWorkPlansLongEnough: soln=" << soln->toString() << std::endl;
ASSERT(QueryPlannerTestLib::solutionMatches(
"{fetch: {node: {ixscan: {pattern: {b: 1}}}}}",
soln->root.get()));
}
};
class All : public Suite {
public:
All() : Suite( "query_plan_ranking" ) {}
void setupTests() {
add<PlanRankingIntersectOverride>();
add<PlanRankingIntersectWithBackup>();
add<PlanRankingPreferCovered>();
add<PlanRankingAvoidIntersectIfNoResults>();
add<PlanRankingPreferCoveredEvenIfNoResults>();
add<PlanRankingPreferImmediateEOF>();
add<PlanRankingNoCollscan>();
add<PlanRankingCollscan>();
// TODO: These don't work without counting FETCH and FETCH is now gone.
// add<PlanRankingIxisectCovered>();
// add<PlanRankingIxisectNonCovered>();
// add<PlanRankingNonCoveredIxisectFetchesLess>();
// add<PlanRankingIxisectHitsEOFFirst>();
// add<PlanRankingChooseBetweenIxisectPlans>();
add<PlanRankingAvoidBlockingSort>();
add<PlanRankingWorkPlansLongEnough>();
}
} planRankingAll;
} // namespace PlanRankingTest
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