1 00:00:02,700 --> 00:00:04,830 Now we did insert some data. 2 00:00:04,830 --> 00:00:07,939 So that's the C of the Crowd Operations. 3 00:00:07,939 --> 00:00:10,110 Now, how can we get that data? 4 00:00:10,110 --> 00:00:13,040 How can we read that data? 5 00:00:13,040 --> 00:00:17,653 Well, that is thankfully also rather straight forward. 6 00:00:18,500 --> 00:00:19,960 To read our data. 7 00:00:19,960 --> 00:00:24,950 So to do something on the R of the Crowd Operations. 8 00:00:24,950 --> 00:00:28,170 We can simply, again, type DB. 9 00:00:28,170 --> 00:00:29,820 Then the name of our collection, 10 00:00:29,820 --> 00:00:32,780 which was created automatically, as I told you, 11 00:00:32,780 --> 00:00:35,390 as soon as we started inserting data. 12 00:00:35,390 --> 00:00:38,380 And then to get all the documents in this collection, 13 00:00:38,380 --> 00:00:41,193 you can just execute, find like this. 14 00:00:42,290 --> 00:00:45,900 And this will then find you all the data in there. 15 00:00:45,900 --> 00:00:46,910 And as you can see, 16 00:00:46,910 --> 00:00:49,330 here we've got the two documents we inserted 17 00:00:49,330 --> 00:00:54,123 with that automatically generated ID and the data we added. 18 00:00:55,860 --> 00:00:57,230 Now, of course, you don't always wanna 19 00:00:57,230 --> 00:01:01,340 find all the documents and therefore you can also filter. 20 00:01:01,340 --> 00:01:04,370 You filter by passing a JavaScript object. 21 00:01:04,370 --> 00:01:06,430 So to say, to find 22 00:01:06,430 --> 00:01:09,140 which now does not define a document 23 00:01:09,140 --> 00:01:11,550 you wanna insert of course, but instead, 24 00:01:11,550 --> 00:01:15,040 which simply is used to group the different options 25 00:01:15,040 --> 00:01:18,260 or conditions for finding. 26 00:01:18,260 --> 00:01:20,550 And here you can simply reference 27 00:01:20,550 --> 00:01:23,490 the different keys you have in your documents. 28 00:01:23,490 --> 00:01:27,670 For example, you could point at name year. 29 00:01:27,670 --> 00:01:29,050 And then after a colon, 30 00:01:29,050 --> 00:01:32,530 you specify the value you wanna look for. 31 00:01:32,530 --> 00:01:36,730 For example, if I look for a Munich Schnitzelhouse here 32 00:01:36,730 --> 00:01:40,280 and I now hit enter, I only find one document, of course, 33 00:01:40,280 --> 00:01:43,113 because I only have one document with this name. 34 00:01:44,080 --> 00:01:47,350 And of course you can also not just look for equality, 35 00:01:47,350 --> 00:01:50,010 but in stat, if you're working with numbers, 36 00:01:50,010 --> 00:01:51,480 you can also look for a greater 37 00:01:51,480 --> 00:01:54,530 or smaller than numbers and so on. 38 00:01:54,530 --> 00:01:56,543 So there's a lot you can do here. 39 00:01:58,000 --> 00:02:01,740 Now, when you find documents, you also don't have to include 40 00:02:01,740 --> 00:02:06,330 all the key value pairs of the documents in the results set. 41 00:02:06,330 --> 00:02:11,330 Instead, if you wanna let's say, find all your documents. 42 00:02:11,700 --> 00:02:15,520 So I switched us back to find without any argument, 43 00:02:15,520 --> 00:02:18,700 but then I'm only interested in the name of the restaurants, 44 00:02:18,700 --> 00:02:20,490 but not in the address. 45 00:02:20,490 --> 00:02:23,470 Then you can simply pass an empty object 46 00:02:23,470 --> 00:02:27,040 as a value for the conditions parameter. 47 00:02:27,040 --> 00:02:31,320 And then add a comma to pass an optional second parameter. 48 00:02:31,320 --> 00:02:34,330 Which is another object where you now control 49 00:02:34,330 --> 00:02:39,330 the so-called protection of the documents that are found. 50 00:02:39,390 --> 00:02:42,030 For example, here you can type name one. 51 00:02:42,030 --> 00:02:44,923 Which means that you want to include the Name Field. 52 00:02:46,320 --> 00:02:49,100 If you hit enter, now we get back all the documents, 53 00:02:49,100 --> 00:02:51,680 but for every document, we only see the name. 54 00:02:51,680 --> 00:02:54,540 In the collection, we still have the extra data 55 00:02:54,540 --> 00:02:57,140 like the address, but here in the result, 56 00:02:57,140 --> 00:02:58,650 we only get back the name. 57 00:02:58,650 --> 00:03:00,753 And by default all the ID. 58 00:03:01,610 --> 00:03:04,980 If you don't want the ID, you can also add underscore ID. 59 00:03:04,980 --> 00:03:06,780 Since that's the name of the ID Field 60 00:03:06,780 --> 00:03:08,903 and type zero to exclude it. 61 00:03:09,850 --> 00:03:14,010 And in general, by typing zero for a field it's excluded. 62 00:03:14,010 --> 00:03:15,950 By typing one it's included. 63 00:03:15,950 --> 00:03:18,450 And if you include at least one field, 64 00:03:18,450 --> 00:03:21,150 all other fields, except for the ID 65 00:03:21,150 --> 00:03:23,593 are automatically excluded. 66 00:03:25,070 --> 00:03:27,270 So that's how you can control which fields 67 00:03:27,270 --> 00:03:29,790 you wanna get for which documents. 68 00:03:29,790 --> 00:03:31,860 So the first parameter value 69 00:03:31,860 --> 00:03:33,540 allows you to define conditions, 70 00:03:33,540 --> 00:03:35,980 to control which documents are fetched. 71 00:03:35,980 --> 00:03:39,020 The second parameter value allows you to control 72 00:03:39,020 --> 00:03:43,020 which fields are shown for the fetched documents. 73 00:03:43,020 --> 00:03:44,970 And that's how you can query your data. 74 00:03:46,070 --> 00:03:49,220 Now, sometimes you'll also wanna 75 00:03:49,220 --> 00:03:52,190 get exactly one document and you know, 76 00:03:52,190 --> 00:03:54,940 that you wanna get only one document. 77 00:03:54,940 --> 00:03:59,050 For example, if I, again, filter for the documents 78 00:03:59,050 --> 00:04:01,500 where the name is Munich Schnitzelhouse. 79 00:04:01,500 --> 00:04:04,000 I know that there is only one document 80 00:04:04,000 --> 00:04:05,693 in there that has this name. 81 00:04:06,610 --> 00:04:08,570 It would even be clearer, if I would be looking 82 00:04:08,570 --> 00:04:13,180 for the specific ID of this document. 83 00:04:13,180 --> 00:04:17,640 Still, if you look closely, you see that the actual result 84 00:04:17,640 --> 00:04:20,120 I get back here is an array. 85 00:04:20,120 --> 00:04:21,793 It's a list of documents. 86 00:04:22,660 --> 00:04:26,750 The reason for that is, that if you're using Find MongoDB, 87 00:04:26,750 --> 00:04:30,440 doesn't know if there will only be one match. 88 00:04:30,440 --> 00:04:33,780 We know that there is only one restaurant with that name, 89 00:04:33,780 --> 00:04:35,600 but that's of course not guaranteed. 90 00:04:35,600 --> 00:04:39,070 We could have multiple restaurants with that name. 91 00:04:39,070 --> 00:04:42,870 And therefore, if you only wanna get one document, 92 00:04:42,870 --> 00:04:44,995 the first matching document in case 93 00:04:44,995 --> 00:04:47,220 you would have multiple matches. 94 00:04:47,220 --> 00:04:51,883 Then instead of using Find, you can use Find one. 95 00:04:53,060 --> 00:04:55,940 And then still pass, your filtering condition 96 00:04:55,940 --> 00:04:57,950 as a first parameter value. 97 00:04:57,950 --> 00:05:01,920 And you could still also set up projection here . 98 00:05:01,920 --> 00:05:05,220 With Find One, I also get only that one document, 99 00:05:05,220 --> 00:05:07,440 but now it's not inside of an array. 100 00:05:07,440 --> 00:05:08,400 It's not a list. 101 00:05:08,400 --> 00:05:11,010 Instead, it's the first matching document 102 00:05:11,010 --> 00:05:12,873 that met this condition. 103 00:05:14,350 --> 00:05:18,040 So find, and find one with the configurations I showed you. 104 00:05:18,040 --> 00:05:22,043 Here are your reference if you wanna find and query data. 105 00:05:22,880 --> 00:05:25,540 Now, of course there is way more you can do. 106 00:05:25,540 --> 00:05:29,090 Different ways of structuring your conditions and so on. 107 00:05:29,090 --> 00:05:32,770 And therefore, I do have a full MongoDB course, 108 00:05:32,770 --> 00:05:34,250 if you wanna dive deeper. 109 00:05:34,250 --> 00:05:38,650 Or you check out the official free MongoDB documentation. 110 00:05:38,650 --> 00:05:41,860 This course will only get you started with MongoDB. 111 00:05:41,860 --> 00:05:43,110 For a deep dive, 112 00:05:43,110 --> 00:05:46,230 definitely visit that official documentation. 113 00:05:46,230 --> 00:05:48,913 Or have a look at that full course I got. 114 00:05:49,840 --> 00:05:52,530 But now with that recovered the C and the R 115 00:05:52,530 --> 00:05:54,300 of the Crowd Operations. 116 00:05:54,300 --> 00:05:57,193 Now let's see how we can update data.