1
00:00:02,290 --> 00:00:05,050
So in the last lecture we had a look at the int 32,

2
00:00:05,140 --> 00:00:11,780
let's now clear our persons again and let's now consider an example for a long value.

3
00:00:11,860 --> 00:00:16,560
That's a bit hard to come up with such examples because it's such a very big value you have to store

4
00:00:16,780 --> 00:00:21,650
but let's say we're talking about company values.

5
00:00:21,800 --> 00:00:24,020
So I have my company's collection,

6
00:00:24,020 --> 00:00:27,230
let me quickly clear the screen to make it easier to read.

7
00:00:27,440 --> 00:00:32,060
So I have my company's collection and there, I insert one new company,

8
00:00:34,740 --> 00:00:39,530
again to keep this simple, I'll focus on the one field which is interesting to us here and that's the company

9
00:00:39,530 --> 00:00:41,120
valuation, let's say.

10
00:00:41,180 --> 00:00:43,880
So the company valuation might be a very big number

11
00:00:44,210 --> 00:00:52,370
and if you remember our slide, int 32 integers could only be used for values up to two billion

12
00:00:52,460 --> 00:00:53,780
and something.

13
00:00:53,780 --> 00:00:58,550
Now let's say we have a company which is worth more than that, which is certainly something that you'll

14
00:00:58,550 --> 00:01:00,970
find a lot in today's world,

15
00:01:00,980 --> 00:01:02,960
so we want to store such a big value,

16
00:01:02,960 --> 00:01:06,520
now let me first of all show what will not work.

17
00:01:06,520 --> 00:01:10,970
We could of course try storing a number int because maybe we forgot the maximum range

18
00:01:11,030 --> 00:01:15,590
and now let's say we have a company which is worth 5 billion dollars,

19
00:01:15,650 --> 00:01:23,330
so we need nine zeroes here and if I hit enter here, this gets stored.

20
00:01:23,350 --> 00:01:31,750
Now let me find that company and what we see is that actually a totally different value was stored here,

21
00:01:31,840 --> 00:01:35,340
so valuation is definitely not the value I entered.

22
00:01:35,470 --> 00:01:42,670
The reason for that is we don't get an error here but actually, we entered a too big value and therefore,

23
00:01:43,530 --> 00:01:50,080
it simply stored a different value because it basically exceeded the range of values we had available

24
00:01:50,380 --> 00:01:52,730
and therefore now, we end up with that value.

25
00:01:52,750 --> 00:01:54,960
Why do we get that value and not an error?

26
00:01:55,030 --> 00:02:01,150
Well that has to do with how numbers are handled technically by computers but this is in the end

27
00:02:01,150 --> 00:02:03,370
what we get here, a wrong result.

28
00:02:03,430 --> 00:02:06,520
Now just to demonstrate that my range was correct,

29
00:02:06,730 --> 00:02:14,440
if I take that maximum value you saw in the slide and I insert that, so let's say our valuation is exactly

30
00:02:14,440 --> 00:02:21,810
that biggest value which is 2147483647,

31
00:02:21,910 --> 00:02:30,880
so if I had to get in there and I find all my companies now because I have two in there, you see that value

32
00:02:30,890 --> 00:02:32,730
is exactly the value I stored

33
00:02:32,730 --> 00:02:35,130
but if I only increase it by one digit,

34
00:02:35,130 --> 00:02:37,860
so we have eight instead of a seven at the end

35
00:02:38,370 --> 00:02:40,270
and I find all the companies, now you see

36
00:02:40,320 --> 00:02:44,990
it's a negative value all of a sudden because it basically goes into the negative range here

37
00:02:45,060 --> 00:02:47,400
if we exceed our maximum value here.

38
00:02:47,430 --> 00:02:48,750
So this is what I'm talking about,

39
00:02:48,750 --> 00:02:54,720
this is what I mean, this is what will not work as you might expect if you enter a too big value here and

40
00:02:54,720 --> 00:02:57,700
that's why you have to be aware of the ranges you face.

41
00:02:57,780 --> 00:03:03,350
Now before we have a look at that long value which will help us, let's also try something else.

42
00:03:03,570 --> 00:03:05,290
What if I enter this number,

43
00:03:05,340 --> 00:03:10,660
so the number which was too big here, too big by only one but still too big,

44
00:03:10,770 --> 00:03:16,350
if I enter it like this, so without any special mongodb type and therefore keep in mind, the

45
00:03:16,350 --> 00:03:17,860
shell is based on Javascript,

46
00:03:17,880 --> 00:03:21,060
so we enter this as a 64 bit double.

47
00:03:21,390 --> 00:03:25,950
If I now have a look at all my companies, we see this was actually stored correctly

48
00:03:25,950 --> 00:03:32,130
and the reason for that is that a 64 bit double has a bigger range than a 32 bit int,

49
00:03:32,340 --> 00:03:40,650
so we could use that to store this value but a 64 bit double will still not have the same range of integers

50
00:03:40,650 --> 00:03:45,100
that as the 64 bit integer has.

51
00:03:45,120 --> 00:03:46,450
And the reason for that is obvious,

52
00:03:46,500 --> 00:03:49,560
the 64 bit double doesn't just store integers,

53
00:03:49,650 --> 00:03:51,780
it also has to handle decimal places.

54
00:03:51,870 --> 00:03:57,510
So it's not like the 64 bits are fully available for integer values and therefore if we have a big

55
00:03:57,510 --> 00:04:04,470
integer, the best way to really store it, to be guaranteed that we can store the biggest possible numbers that

56
00:04:04,530 --> 00:04:09,150
are supported by the int 64 range is that we use the number long

57
00:04:12,210 --> 00:04:17,550
wrapper here in the shell or as you saw with the mongodb python example

58
00:04:17,550 --> 00:04:23,040
in the last lecture, if you're using a driver which you will of course in the end, check out which programming

59
00:04:23,040 --> 00:04:26,450
language you are using, what your default values there are

60
00:04:26,730 --> 00:04:33,090
and then in the driver docs, find out which conversion tools, which types, which wrappers, which constructors

61
00:04:33,090 --> 00:04:38,850
you have to create long integers or 64 bit integers and so on.

62
00:04:38,850 --> 00:04:41,280
So here we could create the integer like this,

63
00:04:41,940 --> 00:04:47,650
well we'll face an issue with that but let's have a look at what got stored. Looks correct, right?

64
00:04:47,880 --> 00:04:49,700
Well let me show you what the issue is

65
00:04:49,710 --> 00:04:56,970
if I add more values here. Let's store the biggest possible number we can store in a long value and that

66
00:04:56,970 --> 00:04:59,660
is 9223, whoops 223,

67
00:04:59,730 --> 00:05:11,550
so 9223372036854775807,

68
00:05:11,550 --> 00:05:15,200
now if I try to store that, I get an error

69
00:05:15,450 --> 00:05:22,980
even though I am in the range of accepted values, so I am in the range of values that are supported.

70
00:05:23,010 --> 00:05:29,520
The problem is that this value which is still a number here is simply too big because it's a double

71
00:05:29,520 --> 00:05:34,320
64 which then well gets wrapped by a number long.

72
00:05:34,320 --> 00:05:36,650
So we should wrap this in quotation marks instead

73
00:05:36,660 --> 00:05:37,930
and now it works

74
00:05:38,070 --> 00:05:39,880
and this is really important to understand,

75
00:05:39,960 --> 00:05:45,390
number int and number long can be used with a number passed as a value and with quotation marks

76
00:05:45,390 --> 00:05:47,080
and you should always use quotation marks,

77
00:05:47,100 --> 00:05:52,290
so basically pass a string because mongodb will then internally kind of convert that string

78
00:05:52,290 --> 00:05:55,010
you could say or simply store it appropriately

79
00:05:55,080 --> 00:06:01,110
but if you pass a number, well the number you pass still faces the javascript limitations here in the

80
00:06:01,110 --> 00:06:03,180
shell which is based on Javascript.

81
00:06:03,240 --> 00:06:08,820
So this number which I try to pass originally simply was too big for the shell, for javascript and

82
00:06:08,820 --> 00:06:14,010
therefore couldn't be stored as a number long because we didn't even reach the mongodb handles it

83
00:06:14,100 --> 00:06:16,170
stage. With a string,

84
00:06:16,170 --> 00:06:18,800
a string is just a list of characters,

85
00:06:18,810 --> 00:06:24,780
it's not treated as a number internally and therefore, it doesn't face the limitations we have with numbers.

86
00:06:24,780 --> 00:06:28,370
So we can then store it like this or pass it to number long like this

87
00:06:28,380 --> 00:06:30,560
and then mongodb can take care about it.