1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
|
// This test runs map reduce from a sharded input collection and outputs it to a sharded
// collection. The test is done in 2 passes - the first pass runs the map reduce and
// outputs it to a non-existing collection. The second pass runs map reduce with the
// collection input twice the size of the first and outputs it to the new sharded
// collection created in the first pass.
var st = new ShardingTest({shards: 2, other: {chunkSize: 1}});
var config = st.getDB("config");
st.adminCommand({enablesharding: "test"});
st.ensurePrimaryShard("test", "shard0001");
st.adminCommand({shardcollection: "test.foo", key: {"a": 1}});
var testDB = st.getDB("test");
function map2() {
emit(this.i, {count: 1, y: this.y});
}
function reduce2(key, values) {
return values[0];
}
var numDocs = 0;
var numBatch = 5000;
var str = new Array(1024).join('a');
// Pre split now so we don't have to balance the chunks later.
// M/R is strange in that it chooses the output shards based on currently sharded
// collections in the database. The upshot is that we need a sharded collection on
// both shards in order to ensure M/R will output to two shards.
st.adminCommand({split: 'test.foo', middle: {a: numDocs + numBatch / 2}});
st.adminCommand({moveChunk: 'test.foo', find: {a: numDocs}, to: 'shard0000'});
// Add some more data for input so that chunks will get split further
for (var splitPoint = 0; splitPoint < numBatch; splitPoint += 400) {
testDB.adminCommand({split: 'test.foo', middle: {a: splitPoint}});
}
var bulk = testDB.foo.initializeUnorderedBulkOp();
for (var i = 0; i < numBatch; ++i) {
bulk.insert({a: numDocs + i, y: str, i: numDocs + i});
}
assert.writeOK(bulk.execute());
numDocs += numBatch;
// Do the MapReduce step
jsTest.log("Setup OK: count matches (" + numDocs + ") -- Starting MapReduce");
var res = testDB.foo.mapReduce(map2, reduce2, {out: {replace: "mrShardedOut", sharded: true}});
jsTest.log("MapReduce results:" + tojson(res));
var reduceOutputCount = res.counts.output;
assert.eq(numDocs,
reduceOutputCount,
"MapReduce FAILED: res.counts.output = " + reduceOutputCount + ", should be " + numDocs);
jsTest.log("Checking that all MapReduce output documents are in output collection");
var outColl = testDB["mrShardedOut"];
var outCollCount = outColl.find().itcount();
assert.eq(numDocs,
outCollCount,
"MapReduce FAILED: outColl.find().itcount() = " + outCollCount + ", should be " +
numDocs + ": this may happen intermittently until resolution of SERVER-3627");
// Make sure it's sharded and split
var newNumChunks = config.chunks.count({ns: testDB.mrShardedOut._fullName});
assert.gt(
newNumChunks, 1, "Sharding FAILURE: " + testDB.mrShardedOut._fullName + " has only 1 chunk");
// Check that there are no "jumbo" chunks.
var objSize = Object.bsonsize(testDB.mrShardedOut.findOne());
var docsPerChunk = 1024 * 1024 / objSize * 1.1; // 1MB chunk size + allowance
st.printShardingStatus(true);
config.chunks.find({ns: testDB.mrShardedOut.getFullName()}).forEach(function(chunkDoc) {
var count =
testDB.mrShardedOut.find({_id: {$gte: chunkDoc.min._id, $lt: chunkDoc.max._id}}).itcount();
assert.lte(count, docsPerChunk, 'Chunk has too many docs: ' + tojson(chunkDoc));
});
// Check that chunks for the newly created sharded output collection are well distributed.
var shard0Chunks =
config.chunks.find({ns: testDB.mrShardedOut._fullName, shard: 'shard0000'}).count();
var shard1Chunks =
config.chunks.find({ns: testDB.mrShardedOut._fullName, shard: 'shard0001'}).count();
assert.lte(Math.abs(shard0Chunks - shard1Chunks), 1);
jsTest.log('Starting second pass');
st.adminCommand({split: 'test.foo', middle: {a: numDocs + numBatch / 2}});
st.adminCommand({moveChunk: 'test.foo', find: {a: numDocs}, to: 'shard0000'});
// Add some more data for input so that chunks will get split further
for (splitPoint = 0; splitPoint < numBatch; splitPoint += 400) {
testDB.adminCommand({split: 'test.foo', middle: {a: numDocs + splitPoint}});
}
bulk = testDB.foo.initializeUnorderedBulkOp();
for (var i = 0; i < numBatch; ++i) {
bulk.insert({a: numDocs + i, y: str, i: numDocs + i});
}
assert.writeOK(bulk.execute());
jsTest.log("No errors on insert batch.");
numDocs += numBatch;
// Do the MapReduce step
jsTest.log("Setup OK: count matches (" + numDocs + ") -- Starting MapReduce");
res = testDB.foo.mapReduce(map2, reduce2, {out: {replace: "mrShardedOut", sharded: true}});
jsTest.log("MapReduce results:" + tojson(res));
reduceOutputCount = res.counts.output;
assert.eq(numDocs,
reduceOutputCount,
"MapReduce FAILED: res.counts.output = " + reduceOutputCount + ", should be " + numDocs);
jsTest.log("Checking that all MapReduce output documents are in output collection");
outColl = testDB["mrShardedOut"];
outCollCount = outColl.find().itcount();
assert.eq(numDocs,
outCollCount,
"MapReduce FAILED: outColl.find().itcount() = " + outCollCount + ", should be " +
numDocs + ": this may happen intermittently until resolution of SERVER-3627");
// Make sure it's sharded and split
newNumChunks = config.chunks.count({ns: testDB.mrShardedOut._fullName});
assert.gt(
newNumChunks, 1, "Sharding FAILURE: " + testDB.mrShardedOut._fullName + " has only 1 chunk");
st.printShardingStatus(true);
// TODO: fix SERVER-12581
/*
config.chunks.find({ ns: testDB.mrShardedOut.getFullName() }).forEach(function(chunkDoc) {
var count = testDB.mrShardedOut.find({ _id: { $gte: chunkDoc.min._id,
$lt: chunkDoc.max._id }}).itcount();
assert.lte(count, docsPerChunk, 'Chunk has too many docs: ' + tojson(chunkDoc));
});
*/
// Note: No need to check if chunk is balanced. It is the job of the balancer
// to balance chunks.
st.stop();
|