1
00:00:00,210 --> 00:00:05,400
In this video you're going to learn how to read documents from your Mongo DB database.

2
00:00:05,400 --> 00:00:10,580
This is going to bring us from C a four create to R for Reid.

3
00:00:10,650 --> 00:00:16,900
We're gonna be able to read individual documents by I.D. or by any other field and we're also gonna

4
00:00:16,920 --> 00:00:23,970
be able to fetch multiple documents limiting them to a specific subset like users whose age is twenty

5
00:00:23,970 --> 00:00:29,190
seven or tasks that have yet to be completed before we get started.

6
00:00:29,220 --> 00:00:33,600
Let's go ahead and remove these three lines related to the object I.D..

7
00:00:33,810 --> 00:00:39,540
Remember all of the stuff covered previously is always available in the PDA guide and you could always

8
00:00:39,540 --> 00:00:42,910
choose to leave that code around if you wanted to.

9
00:00:42,960 --> 00:00:49,740
And down below I'm going to remove all of the code we have in that callback for our 4 calls to insert

10
00:00:49,830 --> 00:00:55,890
one and insert many that's gonna leave us with an empty connect function we can use to explore how we

11
00:00:55,890 --> 00:00:57,860
can fetch data out of the database.

12
00:00:57,870 --> 00:01:05,310
Once again documentation for insert and insert many can also be found in a PD f guide for the class.

13
00:01:05,310 --> 00:01:10,420
So when it comes to fetching data out of the database there are two main methods we're gonna use.

14
00:01:10,500 --> 00:01:14,260
We can view both over in the documentation for collection.

15
00:01:14,280 --> 00:01:18,160
This is the same area where we found the insertion methods.

16
00:01:18,230 --> 00:01:25,620
We are looking for find and find one find is going to allow us to fetch multiple documents out of the

17
00:01:25,620 --> 00:01:31,650
database such as people who are twenty seven and find one is going to allow us to fetch an individual

18
00:01:31,680 --> 00:01:32,810
document.

19
00:01:32,820 --> 00:01:38,340
Now there are other methods that start with find but those are all related to other things like find

20
00:01:38,340 --> 00:01:44,700
and modify or changing the document or find and remove for removing a document and we'll talk about

21
00:01:44,760 --> 00:01:47,310
updating and deleting data a bit later.

22
00:01:47,310 --> 00:01:50,460
For now the focus is on find and find one.

23
00:01:50,820 --> 00:01:56,310
So let's go ahead and start the process of fetching some data out of the database and we'll start with

24
00:01:56,310 --> 00:01:59,250
find one to find an individual document.

25
00:01:59,370 --> 00:02:03,210
Let's pull up our users collection and pick a user we want to fetch.

26
00:02:03,210 --> 00:02:07,210
I'm gonna fetch this one right here with the name equal to Jen.

27
00:02:07,290 --> 00:02:13,260
So let's go ahead and do just that by first specifying the collection we're trying to use find one on.

28
00:02:13,590 --> 00:02:17,050
So D.B. dot collection.

29
00:02:17,050 --> 00:02:23,050
Right here we pass in the string users like we had before when we were using insert one and insert many

30
00:02:23,710 --> 00:02:29,830
and then right here we're gonna use find one now find one accepts two required arguments.

31
00:02:29,830 --> 00:02:33,970
The first is an object and the second is a function.

32
00:02:33,970 --> 00:02:41,590
So the object is used to specify our search criteria if we want to search for a user by their name.

33
00:02:41,590 --> 00:02:47,390
We specify a name field on this query object and we provide the value we're looking for.

34
00:02:47,530 --> 00:02:49,190
In this case capital J.

35
00:02:49,210 --> 00:02:52,090
Jenn is the name we're searching for.

36
00:02:52,090 --> 00:02:58,000
Now the callback gets called when the operation is complete and we either get back an error or we get

37
00:02:58,000 --> 00:03:00,070
back the actual document.

38
00:03:00,070 --> 00:03:05,040
So I could call this user which would be an appropriate name though you could call it whatever you like

39
00:03:05,040 --> 00:03:08,230
to since it's just a function argument down below.

40
00:03:08,230 --> 00:03:10,450
We can now do something with the response.

41
00:03:10,450 --> 00:03:17,170
First up if there was an error we can go ahead and handle it by returning using console dot log some

42
00:03:17,170 --> 00:03:24,730
sort of message unable to fetch and then down below we can actually dump the user to the console to

43
00:03:24,730 --> 00:03:26,470
view that document.

44
00:03:26,470 --> 00:03:30,730
So console dot lug printing user to the screen.

45
00:03:30,730 --> 00:03:36,190
So with this in place I would expect that we're able to find our one document since there is a user

46
00:03:36,370 --> 00:03:37,790
with the name of Gen.

47
00:03:37,840 --> 00:03:43,380
Let's go ahead and save the program and run the script from the terminal that's node Mongo D.B. dot

48
00:03:43,390 --> 00:03:46,720
J s when I run it what do I get right here.

49
00:03:46,780 --> 00:03:48,680
I can see my one document printing.

50
00:03:48,700 --> 00:03:56,050
I have Jen's idea I have the name for Jan and I have the age 28 all matches up with the data stored

51
00:03:56,080 --> 00:03:57,710
in the database.

52
00:03:57,730 --> 00:04:01,020
Now in this case we're just searching by one field name.

53
00:04:01,120 --> 00:04:06,540
We could also choose to search by more fields by specifying those on the list.

54
00:04:06,540 --> 00:04:13,210
Now what happens if we do search for something else like age but we provide an age that would return

55
00:04:13,270 --> 00:04:20,300
no results like one for example there is no Gen inside of our database with the age of 1.

56
00:04:20,440 --> 00:04:23,200
Now what's going to happen is not an error.

57
00:04:23,200 --> 00:04:26,230
This is still a completely valid operation.

58
00:04:26,230 --> 00:04:30,380
If we save the program we can rerun things to see what we get down below.

59
00:04:30,400 --> 00:04:31,770
What do we get we get.

60
00:04:31,810 --> 00:04:32,690
No.

61
00:04:32,770 --> 00:04:36,910
So searching for a document and not finding one is not an error.

62
00:04:36,910 --> 00:04:38,340
Everything did go well.

63
00:04:38,500 --> 00:04:40,640
We gave you back what you asked for.

64
00:04:40,660 --> 00:04:42,790
There was just nothing to give back.

65
00:04:42,820 --> 00:04:48,040
It was able to correctly communicate with the database though and go through the process of searching

66
00:04:48,040 --> 00:04:49,630
for what you were looking for.

67
00:04:49,630 --> 00:04:52,660
Now find one always returns just a single document.

68
00:04:52,660 --> 00:04:56,770
If your query matches multiple documents it's just going to grab the first one.

69
00:04:56,770 --> 00:05:00,340
So for example there are two users with the name of Andrew.

70
00:05:00,490 --> 00:05:03,230
It's always going to return this first document.

71
00:05:03,280 --> 00:05:09,610
If we just searched for name Andrew and we have three users who have the age of twenty seven we're always

72
00:05:09,610 --> 00:05:12,010
going to get the first one back.

73
00:05:12,040 --> 00:05:17,680
Now if we wanted to search for a specific document we could always do that by its unique identifier.

74
00:05:17,680 --> 00:05:21,100
So let's go ahead and do that before moving on to find.

75
00:05:21,100 --> 00:05:26,940
To search for multiple documents right here we're gonna go ahead and grab an I.D. for one of our documents

76
00:05:26,950 --> 00:05:28,630
you can pick any one you like.

77
00:05:28,630 --> 00:05:32,540
I'm gonna grab the I.D. for Vikram to grab the I.D. text.

78
00:05:32,560 --> 00:05:38,930
We can just right click click edit document and we can grab right here what's inside of quotes.

79
00:05:39,010 --> 00:05:41,150
So I'm going to copy that to the clipboard.

80
00:05:41,470 --> 00:05:45,450
Click cancel and I'm gonna bring that over to Mongo DB dot J.

81
00:05:45,470 --> 00:05:46,900
S right here.

82
00:05:46,900 --> 00:05:53,170
We can now swap out what we have inside of the query object instead of searching by name and age.

83
00:05:53,170 --> 00:06:00,040
I'm just going to search by I.D. Now it's not enough to provide a string I.D. so I can't just open and

84
00:06:00,040 --> 00:06:03,330
close a set of quotes and paste that I.D. in.

85
00:06:03,370 --> 00:06:09,550
Remember in the last video we learned that was actually stored is an object I.D. It's not a string it

86
00:06:09,550 --> 00:06:11,120
is binary data.

87
00:06:11,140 --> 00:06:15,730
So this search is going to return no results and it's a common error.

88
00:06:15,760 --> 00:06:19,990
So I do want to save it run it just to prove the point right here.

89
00:06:19,990 --> 00:06:21,150
File is saved.

90
00:06:21,250 --> 00:06:26,080
I will execute the program once again and we do not get any results back.

91
00:06:26,080 --> 00:06:30,460
If we want to search by I.D. We have to provide an object I.D..

92
00:06:30,610 --> 00:06:34,510
So we have to use that function and we talked about earlier right here.

93
00:06:34,510 --> 00:06:38,770
Let's go ahead and wrap this string in that function call.

94
00:06:38,830 --> 00:06:42,920
I'm going to cut this string out including the opening and closing quotes.

95
00:06:43,120 --> 00:06:49,860
I'll use new object I.D. then I'm going to pass to it the string that I just cut out.

96
00:06:49,930 --> 00:06:53,050
Now we are providing a valid object I.D..

97
00:06:53,140 --> 00:06:54,580
Any query object.

98
00:06:54,580 --> 00:06:58,900
And if we rerun the program we are indeed going to get the result expected.

99
00:06:58,900 --> 00:07:03,990
So right here I can see that we do have the document showing up for Vikram.

100
00:07:04,000 --> 00:07:06,670
Now you might be saying hey that's a lot of extra work.

101
00:07:06,670 --> 00:07:11,980
Why can't that just be done for us a little bit later in the course we will learn how we can avoid calling

102
00:07:11,980 --> 00:07:19,070
new object I.D. but for now that's the standard way to get things done when using the Mongo D.B. native

103
00:07:19,070 --> 00:07:20,010
driver.

104
00:07:20,240 --> 00:07:22,460
Now finding one document is a good start.

105
00:07:22,460 --> 00:07:30,050
We can also use find to find multiple documents so we could search for users by name or age or we could

106
00:07:30,050 --> 00:07:34,670
search for tasks by any criteria like whether or not it's been completed.

107
00:07:34,670 --> 00:07:40,520
Let's go ahead and set up a call to find that's D.B. dot collection.

108
00:07:40,520 --> 00:07:46,070
We're going to search in users once again and we'll try to find users who have the age of 27 and we

109
00:07:46,070 --> 00:07:48,980
know we have three users that fit that criteria.

110
00:07:49,190 --> 00:07:55,500
And we're gonna go ahead and call find to pass our query object in just like we did for find one.

111
00:07:55,550 --> 00:08:01,040
Now it doesn't make sense to search by I.D. when using Find since you would only ever get a single record

112
00:08:01,040 --> 00:08:03,270
back since the I.D. is unique.

113
00:08:03,350 --> 00:08:08,330
So typically when using find we're searching by a different field on the document.

114
00:08:08,330 --> 00:08:13,880
In this case I'm going to find users whose age has a value of twenty seven once again and that would

115
00:08:13,880 --> 00:08:15,680
return three documents.

116
00:08:15,680 --> 00:08:20,530
Now find is a bit different then find one insert one or insert many.

117
00:08:20,540 --> 00:08:26,840
And that's because find it doesn't take in a callback as that second argument with find what we get

118
00:08:26,840 --> 00:08:34,260
back as the return value is actually a cursor and the cursor is not the data you've asked for.

119
00:08:34,370 --> 00:08:37,730
It is a pointer to that data in the database.

120
00:08:37,820 --> 00:08:43,820
And the reason we're getting a cursor back is Mongo D.B. isn't going to assume that every time you use

121
00:08:43,820 --> 00:08:47,920
find you always want to get back an array of all of those documents.

122
00:08:47,930 --> 00:08:53,990
There are a lot of other things you might want to do like get just the first five documents or do something

123
00:08:54,020 --> 00:08:57,400
even different like just get the number of matching documents.

124
00:08:57,410 --> 00:09:00,630
You don't even want any document data themselves.

125
00:09:00,650 --> 00:09:04,650
So when we get a cursor back it opens up a lot more possibilities.

126
00:09:04,670 --> 00:09:08,280
Now we can explore all of this by heading over to the documentation.

127
00:09:08,360 --> 00:09:15,200
So if we go over to Google Chrome and we scroll down to our f methods for collection we have find one

128
00:09:15,260 --> 00:09:16,260
right here.

129
00:09:16,280 --> 00:09:18,770
We pass in the query which we did.

130
00:09:18,800 --> 00:09:24,350
We have our optional options which we did not specify and then down below we add the callback which

131
00:09:24,350 --> 00:09:30,830
we did specify if we go over to find though we can see that we still have the query and those optional

132
00:09:30,950 --> 00:09:31,760
options.

133
00:09:31,760 --> 00:09:35,120
But there is no callback as a third argument.

134
00:09:35,150 --> 00:09:41,540
Now we can see that we also get a return value right here of cursor and when we click that it's going

135
00:09:41,540 --> 00:09:44,190
to bring us over to something else in the docs.

136
00:09:44,270 --> 00:09:47,360
If we scroll down we have cursor sitting right here.

137
00:09:47,810 --> 00:09:53,030
So what we get back from find is indeed a cursor it is a pointer to data.

138
00:09:53,060 --> 00:09:55,780
There are all sorts of methods we can use with it.

139
00:09:55,850 --> 00:10:02,990
We can use things to limit the data like limit I can count the data up with count I can do other forms

140
00:10:02,990 --> 00:10:10,550
of aggregation or I can use one of the more popular methods to array to array is going to allow us to

141
00:10:10,550 --> 00:10:15,170
get back an array of documents which in this case is exactly what we want.

142
00:10:15,560 --> 00:10:16,200
So over here.

143
00:10:16,220 --> 00:10:17,870
What does that mean for us.

144
00:10:17,900 --> 00:10:22,610
It means that finder returns a cursor and the cursor has a 2 array method.

145
00:10:22,610 --> 00:10:27,170
So right here I'm going to call to array now to array.

146
00:10:27,170 --> 00:10:33,830
That is what takes the callback function where we either get the error or we get our matching documents.

147
00:10:33,890 --> 00:10:36,710
In this case we could call them users.

148
00:10:36,710 --> 00:10:41,360
Now let's go ahead and dump those to the council to see what we get since the error handling is going

149
00:10:41,360 --> 00:10:42,860
to be the same either way.

150
00:10:42,920 --> 00:10:45,160
I'm just going to temporarily ignore that.

151
00:10:45,350 --> 00:10:49,460
I'll use console log to just dump users to the console.

152
00:10:49,460 --> 00:10:52,640
We can save Mongo DB and test things out.

153
00:10:52,700 --> 00:10:59,150
Now I will comment out my call to find one just to clean up the output we see in the terminal down below

154
00:10:59,270 --> 00:11:02,140
and I'll restart the script I'll shut it down.

155
00:11:02,140 --> 00:11:04,450
Start it up once again and right here.

156
00:11:04,450 --> 00:11:05,380
What am I getting.

157
00:11:05,480 --> 00:11:12,380
I'm getting an array of three documents back where each document has an age of twenty seven.

158
00:11:12,530 --> 00:11:18,770
So using this simple call I was able to fetch multiple pieces of data from the database limiting them

159
00:11:18,830 --> 00:11:20,240
by some criteria.

160
00:11:20,240 --> 00:11:26,300
Now to further explain why cursors are being used we can take this call copy it and duplicate it down

161
00:11:26,300 --> 00:11:27,230
below.

162
00:11:27,230 --> 00:11:31,980
We're gonna switch from using the to array cursor method over to using count.

163
00:11:32,060 --> 00:11:37,550
Now count still takes in a callback and we get an error potentially or the count.

164
00:11:37,550 --> 00:11:40,090
So right here I can just call that count.

165
00:11:40,130 --> 00:11:42,290
Then I'll just print count to the console.

166
00:11:42,560 --> 00:11:47,020
So it's very similar to what we had above with a few minor changes.

167
00:11:47,030 --> 00:11:50,630
Now if we rerun the program we can see the output we're gonna get.

168
00:11:50,630 --> 00:11:56,800
So right here I get my array for that first call to find and for the second I get the number three.

169
00:11:56,810 --> 00:11:58,850
So this is the advantage of the cursor.

170
00:11:58,940 --> 00:12:04,850
Sometimes I want to get the data I want to get all of the individual fields back and in that case to

171
00:12:04,850 --> 00:12:06,510
array gets the job done.

172
00:12:06,590 --> 00:12:12,140
But if I do want to do something simple like count there's no need to fetch all of those records store

173
00:12:12,140 --> 00:12:16,810
them in memory in node j s only to get a single number back.

174
00:12:16,950 --> 00:12:23,550
Mongo DB can handle that for us instead of needing to transfer all of the documents across the network.

175
00:12:23,550 --> 00:12:26,310
It can just transfer that single integer.

176
00:12:26,370 --> 00:12:28,440
In this case the number three.

177
00:12:28,440 --> 00:12:33,960
So the cursor is a nice tool for us to be able to use and hopefully this example illustrates why we

178
00:12:33,960 --> 00:12:36,960
might not always want to get all of the data back.

179
00:12:37,020 --> 00:12:42,600
While we might want to sometimes do something a little bit different now it is challenge time where

180
00:12:42,660 --> 00:12:50,310
you're going to use our search methods find one and find to find documents in the tasks collection and

181
00:12:50,310 --> 00:12:51,060
right here.

182
00:12:51,060 --> 00:12:53,510
I have some challenge comments right here.

183
00:12:53,520 --> 00:12:58,830
Your challenge is to use find and find one with the tasks collection.

184
00:12:58,830 --> 00:13:05,760
So step one you're gonna use find one to fetch the latest task in that collection by its I.D. and you'll

185
00:13:05,760 --> 00:13:12,510
print that document to the console then you're going to use a call to find to attach all tasks that

186
00:13:12,510 --> 00:13:16,710
are not completed and you're going to print those to the console as well.

187
00:13:16,710 --> 00:13:18,690
Finally you're going to test your work.

188
00:13:18,690 --> 00:13:21,750
So when you run the script you should see one document print.

189
00:13:21,780 --> 00:13:27,810
The last task then the next thing that prints should be an array of documents all of the tasks that

190
00:13:27,810 --> 00:13:29,590
have not been completed.

191
00:13:29,610 --> 00:13:33,570
Take some time to knock that out using the code disgust up above.

192
00:13:33,570 --> 00:13:36,900
Test your work and when you're done come back and click play

193
00:13:40,810 --> 00:13:41,480
how would you do.

194
00:13:41,540 --> 00:13:47,180
Let's go ahead and kick things off by pulling up the tasks collection and robo 3D so we can see the

195
00:13:47,180 --> 00:13:47,630
data.

196
00:13:47,630 --> 00:13:48,710
We're working with.

197
00:13:48,710 --> 00:13:50,440
I have that sitting right here.

198
00:13:50,540 --> 00:13:54,880
Now the first thing was to grab the document the last one and buy I.D..

199
00:13:55,040 --> 00:13:59,510
So I'm gonna edit that document just so I can copy it to the clipboard easily.

200
00:13:59,510 --> 00:14:02,940
I'll close the editor and I'll bring that over to mongo.

201
00:14:02,970 --> 00:14:05,110
Dot J S right here.

202
00:14:05,120 --> 00:14:11,600
D.B. dot collection since we are trying to access the tasks collection and right here I'm gonna use

203
00:14:11,600 --> 00:14:18,800
find one to find a document by its I.D. so any query object we're searching by I.D. and I'm searching

204
00:14:18,800 --> 00:14:28,220
by an object I.D. So I use new object I.D. passing in inside of quotes the object I.D. value.

205
00:14:28,370 --> 00:14:34,590
Now from there we provide that second argument which is our callback function we get a potential error

206
00:14:35,310 --> 00:14:39,190
and we potentially get the document which I'll call a task.

207
00:14:39,420 --> 00:14:45,660
Right here we can go ahead and provide the arrow function body and in here all I'm gonna do is dump

208
00:14:45,840 --> 00:14:47,150
task to the console.

209
00:14:47,160 --> 00:14:51,960
So console dot plug printing task.

210
00:14:51,960 --> 00:14:54,870
Now we can go ahead and test our work one step at a time.

211
00:14:54,900 --> 00:14:59,470
So right here I'll go ahead and rerun things I'll shut the program down.

212
00:14:59,510 --> 00:15:06,270
Start it up once again and I am indeed seeing that last task with a description of pot plants and a

213
00:15:06,270 --> 00:15:11,140
completed value of false which matches up with what I have over here.

214
00:15:11,220 --> 00:15:16,530
Next up step two was to find all of the documents that have not been completed.

215
00:15:16,530 --> 00:15:20,250
So right here for that we'll use D.B. dot collection.

216
00:15:20,250 --> 00:15:28,110
Once again we're looking in tasks and we're using find to find documents where it completed is equal

217
00:15:28,140 --> 00:15:29,550
to False.

218
00:15:29,640 --> 00:15:36,150
Now from here we can't just provide a callback function since remember bind returns a cursor.

219
00:15:36,150 --> 00:15:39,440
Now we could use other cursor methods to do other things.

220
00:15:39,540 --> 00:15:42,500
In this case though we do indeed want to print all of those documents.

221
00:15:42,510 --> 00:15:45,680
So I'll use to array when we use to array.

222
00:15:45,710 --> 00:15:50,030
It actually goes off to the server and fetches all of those documents.

223
00:15:50,040 --> 00:15:55,250
Right here we either have an error or we have our list of tasks.

224
00:15:55,320 --> 00:15:56,220
Perfect.

225
00:15:56,220 --> 00:16:02,040
Let's go ahead and print them console dialogue printing tasks.

226
00:16:02,050 --> 00:16:06,300
Now we're gonna go ahead and run our program for the final time.

227
00:16:06,370 --> 00:16:09,040
Down below I'll shut down the script.

228
00:16:09,040 --> 00:16:10,410
I'll start it up again.

229
00:16:10,420 --> 00:16:16,030
We have as the first piece of output our last item which was fetched by I.D..

230
00:16:16,330 --> 00:16:21,670
Then we have our array with all of the documents all of the tasks that have not been completed.

231
00:16:22,000 --> 00:16:28,720
I have renew inspection and I have pot plants both which indeed have a completed value of false.

232
00:16:28,720 --> 00:16:31,420
I'm not seeing clean the house show up anywhere.

233
00:16:31,420 --> 00:16:33,960
Since that has already been completed.

234
00:16:34,010 --> 00:16:39,490
Now this example query is the kind of query you would use if you're trying to show someone all of these

235
00:16:39,490 --> 00:16:41,520
things they still need to do.

236
00:16:41,560 --> 00:16:48,790
Now that we know how to find our documents we have knocked out both C for create and R for read down

237
00:16:48,790 --> 00:16:49,240
below.

238
00:16:49,240 --> 00:16:53,820
I'm also going to remove the challenge comments since we're all done with that one.

239
00:16:53,890 --> 00:17:00,340
Now we do still have to cover you for update and D for delete but before we do we're going to take a

240
00:17:00,340 --> 00:17:05,800
quick break to talk about a very important asynchronous tool at our disposal.

241
00:17:05,800 --> 00:17:10,200
This is the promise and we're going to start talking about it in the next video.

242
00:17:10,330 --> 00:17:12,250
So let's go ahead and jump right in.