MongoDB MapReduce Combat <2>

Millions of of the data in the database, processing may be slow, so it is simple to build a smaller structure of similar tables, test data

/* 0 */
{
  "_id": ObjectId ("54fe73e36e26d21dc4391bdb"),
  "Create_date": Isodate ("2014-07-26t13:57:18z"),
  "Rfid_no": "010101000120140322000173"
}

/* 1 */
{
  "_id": ObjectId ("54FE74076E26D21DC4391BDC"),
  "Create_date": Isodate ("2014-07-24t11:57:18z"),
  "Rfid_no": "010101000120140322000173"
}

/* 2 */
{
  "_id": ObjectId ("54FE74136E26D21DC4391BDD"),
  "Create_date": Isodate ("2014-07-27t09:27:18z "),
  " Rfid_no ":" 010101000120140322000173 "
}

/* 3
*
  /{" _id ": ObjectId (" 54fe742a6e26d21dc4391bde "),
  " Create_date ": Isodate (" 2014-07-26t13:57:18z "),
  " Rfid_no ":" 010101000120140322000883 "
}

It is important to note that the join statement for the time type is:

Db.test.save ({rfid_no: ' 1 ', create_date:new DATE (' 6/26/2014 13:57:18 ')});

Writing a map

function Map () {
	//Remove the same time record as RFID in the log record
	emit (this
		. Rfid_no, this
		. Create_date
	); 
}

Write reduce

function Reduce (key, values) {
	//combine the same RFID payback time into a record of
	var ret = {rfid:key, times:[{}]};
	for (var i = 0;i < values.length;i++) {
		ret.times[i] = values[i];
	}
	return ret;
}

Configure in & Out
To run and produce the result: