MongoDB intermediate ---- & gt; replace GroupBy with MapReduce in large data volumes

In fact, MapReduce in MongoDB is more similar to GroupBy in relational databases.

Just after doing this experiment, the GroupBy (MapReduce) for large data volumes is still ideal, generating million 3-bit random strings

1. For(VarI = 0; I <1000000; I ++)
2. {
3.  VarX ="0123456789";
4.  VarTmp ="";
5.  For(VarJ = 0; j <3; j ++)
6. {
7. Tmp + = x. charAt (Math. ceil (Math. random () * 100000000) % x. length); |
8. }
9.  VarU = {_ id: I, v1: tmp };
10. Db. RandomNum. insert (u );
11. }

Then perform the same random number to get the Count number, so it must be GroupBy

1. VarM =Function() {Emit (This. V1, {count: 1 });};// Map key is similar to group by of relational data. The second value is the field to be aggregated (sum ...)
3. VarR =Function(Key, values ){VarTotal = 0;For(VarI = 0; I <values. length; I ++) {total + = values [I]. count ;}Return{Count: total };};.// Reduce
5. VarRes = db. RandomNum. mapReduce (m, r, {out: {replace:'Result'}});
7. Db [res. result]. find ()

Tested:

1. VarStartTime =NewDate ();
3. VarM =Function() {Emit (This. V1, {count: 1 });};
5. VarR =Function(Key, values ){VarTotal = 0;For(VarI = 0; I <values. length; I ++) {total + = values [I]. count ;}Return{Count: total };};
7. VarRes = db. RandomNum. mapReduce (m, r, {out: {replace:'Result'}});
9. Db [res. result]. find ()
11. (NewDate (). getTime ()-startTime. getTime ()/1000

The result is as follows:

1. > Db [res. result]. find ()
2. {"_ Id":"000","Value":{"Count":1075}}
3. {"_ Id":"001","Value":{"Count":1045}}
4. {"_ Id":"002","Value":{"Count":1022}}
5. {"_ Id":"003","Value":{"Count":968}}
6. {"_ Id":"004","Value":{"Count":994}}
7. {"_ Id":"005","Value":{"Count":1009}}
8. {"_ Id":"006","Value":{"Count":948}}
9. {"_ Id":"007","Value":{"Count":1003}}
10. {"_ Id":"008","Value":{"Count":983}}
11. {"_ Id":"009","Value":{"Count":993}}
12. {"_ Id":"010","Value":{"Count":987}}
13. {"_ Id":"011","Value":{"Count":982}}
14. {"_ Id":"012","Value":{"Count":957}}
15. {"_ Id":"013","Value":{"Count":1031}}
16. {"_ Id":"014","Value":{"Count":971}}
17. {"_ Id":"015","Value":{"Count":1053}}
18. {"_ Id":"016","Value":{"Count":974}}
19. {"_ Id":"017","Value":{"Count":975}}
20. {"_ Id":"018","Value":{"Count":978}}
21. {"_ Id":"019","Value":{"Count":1010}}
22. Has more
23. >
24. > (New Date (). getTime ()-startTime. getTime ())/1000
25. 63.335 s
26. > Bye

Test Machine performance: