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'use strict';
/**
* map_reduce_inline.js
*
* Generates some random data and inserts it into a collection. Runs a
* map-reduce command over the collection that computes the frequency
* counts of the 'value' field in memory.
*
* Used as the base workload for the other map-reduce workloads.
*/
var $config = (function() {
function mapper() {
if (this.hasOwnProperty('key') && this.hasOwnProperty('value')) {
var obj = {};
obj[this.value] = 1;
emit(this.key, obj);
}
}
function reducer(key, values) {
var res = {};
values.forEach(function(obj) {
Object.keys(obj).forEach(function(value) {
if (!res.hasOwnProperty(value)) {
res[value] = 0;
}
res[value] += obj[value];
});
});
return res;
}
function finalizer(key, reducedValue) {
return reducedValue;
}
var data = {
numDocs: 2000,
mapper: mapper,
reducer: reducer,
finalizer: finalizer
};
var states = (function() {
function init(db, collName) {
// no-op
// other workloads that extend this workload use this method
}
function mapReduce(db, collName) {
var options = {
finalize: this.finalizer,
out: { inline: 1 }
};
var res = db[collName].mapReduce(this.mapper, this.reducer, options);
assertAlways.commandWorked(res);
}
return {
init: init,
mapReduce: mapReduce
};
})();
var transitions = {
init: { mapReduce: 1 },
mapReduce: { mapReduce: 1 }
};
function makeDoc(keyLimit, valueLimit) {
return {
_id: new ObjectId(),
key: Random.randInt(keyLimit),
value: Random.randInt(valueLimit)
};
}
function setup(db, collName, cluster) {
var bulk = db[collName].initializeUnorderedBulkOp();
for (var i = 0; i < this.numDocs; ++i) {
// TODO: this actually does assume that there are no unique indexes
var doc = makeDoc(this.numDocs / 100, this.numDocs / 10);
bulk.insert(doc);
}
var res = bulk.execute();
assertAlways.writeOK(res);
assertAlways.eq(this.numDocs, res.nInserted);
}
return {
threadCount: 5,
iterations: 10,
data: data,
states: states,
transitions: transitions,
setup: setup
};
})();
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