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// Test subtleties of batchSize and limit.
var t = db.jstests_batch_size;
t.drop();
for (var i = 0; i < 4; i++) {
t.save({_id: i, a: i});
}
function runIndexedTests() {
// With limit, indexed.
assert.eq(2, t.find().limit(2).itcount(), 'G');
assert.eq(2, t.find().sort({a: 1}).limit(2).itcount(), 'H');
// With batchSize, indexed.
// SERVER-12438: If there is an index that provides the sort,
// then a plan with an unindexed sort should never be used.
// Consequently, batchSize will NOT be a hard limit in this case.
// WARNING: the behavior described above may change in the future.
assert.eq(4, t.find().batchSize(2).itcount(), 'I');
assert.eq(4, t.find().sort({a: 1}).batchSize(2).itcount(), 'J');
}
// Without batch size or limit, unindexed.
assert.eq(4, t.find().itcount(), 'A');
assert.eq(4, t.find().sort({a: 1}).itcount(), 'B');
// With limit, unindexed.
assert.eq(2, t.find().limit(2).itcount(), 'C');
assert.eq(2, t.find().sort({a: 1}).limit(2).itcount(), 'D');
assert.eq(4, t.find().batchSize(2).itcount(), 'E');
assert.eq(4, t.find().sort({a: 1}).batchSize(2).itcount(), 'F');
// With negative batchSize. A negative batchSize value instructs the server
// to return just a single batch of results.
assert.eq(1, t.find().batchSize(-1).itcount(), 'G');
assert.eq(2, t.find().batchSize(-2).itcount(), 'H');
// Run the tests with the index twice in order to double check plan caching.
t.ensureIndex({a: 1});
for (var i = 0; i < 2; i++) {
runIndexedTests();
}
// The next tests make sure that we obey limit and batchSize properly when
// the sort could be either indexed or unindexed.
t.drop();
t.ensureIndex({a: 1});
t.ensureIndex({b: 1});
for (var i = 0; i < 100; i++) {
t.save({_id: i, a: i, b: 1});
}
// Without a hint. Do it twice to make sure caching is ok.
for (var i = 0; i < 2; i++) {
assert.eq(15, t.find({a: {$gte: 85}}).sort({b: 1}).batchSize(2).itcount(), 'K');
assert.eq(6, t.find({a: {$gte: 85}}).sort({b: 1}).limit(6).itcount(), 'L');
}
// Hinting 'a'.
assert.eq(15, t.find({a: {$gte: 85}}).sort({b: 1}).hint({a: 1}).batchSize(2).itcount(), 'M');
assert.eq(6, t.find({a: {$gte: 85}}).sort({b: 1}).hint({a: 1}).limit(6).itcount(), 'N');
// Hinting 'b'.
assert.eq(15, t.find({a: {$gte: 85}}).sort({b: 1}).hint({b: 1}).batchSize(2).itcount(), 'O');
assert.eq(6, t.find({a: {$gte: 85}}).sort({b: 1}).hint({b: 1}).limit(6).itcount(), 'P');
// With explain.
var explain = t.find({a: {$gte: 85}}).sort({b: 1}).batchSize(2).explain("executionStats");
assert.eq(15, explain.executionStats.nReturned, 'Q');
explain = t.find({a: {$gte: 85}}).sort({b: 1}).limit(6).explain("executionStats");
assert.eq(6, explain.executionStats.nReturned, 'R');
// Double check that we're not scanning more stuff than we have to.
// In order to get the sort using index 'a', we should need to scan
// about 50 keys and 50 documents.
var explain = t.find({a: {$gte: 50}}).sort({b: 1}).hint({a: 1}).limit(6).explain("executionStats");
assert.lte(explain.executionStats.totalKeysExamined, 60, 'S');
assert.lte(explain.executionStats.totalDocsExamined, 60, 'T');
assert.eq(explain.executionStats.nReturned, 6, 'U');
// -------
// During plan ranking, we treat ntoreturn as a limit. This prevents us from buffering
// too much data in a blocking sort stage during plan ranking.
t.drop();
// Generate big string to use in the object - 1MB+ String
var bigStr = "ABCDEFGHIJKLMNBOPQRSTUVWXYZ012345687890";
while (bigStr.length < 1000000) { bigStr = bigStr + "::" + bigStr; }
// Insert enough documents to exceed the 32 MB in-memory sort limit.
for (var i = 0; i < 40; i++) {
var doc = {x: 1, y: 1, z: i, big: bigStr};
t.insert(doc);
}
// Two indices needed in order to trigger plan ranking. Neither index provides
// the sort order.
t.ensureIndex({x: 1});
t.ensureIndex({y: 1});
// We should only buffer 3 docs in memory.
var cursor = t.find({x: 1, y: 1}).sort({z: -1}).limit(3);
assert.eq(39, cursor.next()["z"]);
assert.eq(38, cursor.next()["z"]);
assert.eq(37, cursor.next()["z"]);
assert(!cursor.hasNext());
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