1
00:00:02,230 --> 00:00:09,160
That's it for this module, we had a very detailed look at indexes. Indexes allow us to retrieve our data

2
00:00:09,160 --> 00:00:10,420
more efficiently,

3
00:00:10,420 --> 00:00:16,800
mostly we saw some exceptions to this module but generally, they speed up our queries and also the sorting.

4
00:00:17,110 --> 00:00:20,710
We can use single field compound multikey and text indexes,

5
00:00:20,710 --> 00:00:26,500
now there are a couple of other indexes and for example geospatial indexes are something we'll see in

6
00:00:26,500 --> 00:00:28,000
the geospatial module

7
00:00:28,030 --> 00:00:33,880
but these are the most important indexes for now and it's also important to understand that indexes don't

8
00:00:33,880 --> 00:00:34,990
come for free,

9
00:00:34,990 --> 00:00:36,940
they will slow down your writes,

10
00:00:36,940 --> 00:00:38,590
that is something you always have

11
00:00:38,620 --> 00:00:40,610
but this still worth the effort

12
00:00:40,690 --> 00:00:45,670
but this is something you should keep in mind because it means that you should not create the index

13
00:00:45,730 --> 00:00:47,380
for every single field,

14
00:00:47,380 --> 00:00:54,790
this will be inefficient because all these indexes need to be updated with every insert, update or delete.

15
00:00:54,820 --> 00:01:02,110
We can use indexes for querying and sorting and compound indexes have this special behavior where you

16
00:01:02,110 --> 00:01:03,710
can use them left to right,

17
00:01:03,760 --> 00:01:09,460
if you have a compound index made up of name and age, you can either use that index to optimize your queries

18
00:01:09,460 --> 00:01:16,150
where you look for name and age with some criteria or also for queries that just use the name, just the

19
00:01:16,150 --> 00:01:20,380
age is not possible due to the way this is stored.

20
00:01:20,380 --> 00:01:24,820
To find out whether your queries and indexes do their job in a good way,

21
00:01:24,850 --> 00:01:29,110
you can diagnose your queries with the explain method,

22
00:01:29,200 --> 00:01:36,090
also remember the options you could pass to explain, query planner, execution stats and all plans execution.

23
00:01:36,250 --> 00:01:42,860
The output there gives you a detailed look into what mongodb did and how it derived

24
00:01:42,910 --> 00:01:48,790
this plan it used and it also gives you an idea of how you might optimize your indexes,

25
00:01:48,790 --> 00:01:54,070
for example if you have a large gap between the keys it had to look at and the documents it actually

26
00:01:54,070 --> 00:01:56,850
retrieved. When creating your indexes,

27
00:01:56,860 --> 00:01:58,640
you can also configure them,

28
00:01:58,660 --> 00:02:03,290
for example you can add a time to live if the index is placed on a date time

29
00:02:03,370 --> 00:02:07,570
or you can turn them into unique or partial indexes. For text indexes,

30
00:02:07,570 --> 00:02:11,210
you can also assign weights and a default language.

31
00:02:11,210 --> 00:02:17,770
Now this is what we covered in this module and this hopefully helps you create efficient databases with

32
00:02:17,770 --> 00:02:22,060
efficient indexes and then writing efficient queries for that.