Paging through your data is one of the most common operations with MongoDB. A typical scenario is the need to display your results in chunks in your UI. If you’re batch processing your data, it’s also important to get your paging strategy correct so your data processing can scale. Let’s walk through an example to see the different ways to page through data in MongoDB. In this example, we have a CRM database of user data that we need to page through and display 10 users at a time. So in effect, our page size is 10. Here is the structure of our user document: { _id, name, company, state } Approach 1: Using skip() and limit() MongoDB natively supports the paging operation using the skip() and limit() commands. The skip(n) directive tells MongoDB that it should skip ‘n’ results, and the limit(n) directive instructs MongoDB that it should limit the result length to ‘n’ results. Typically, you’ll be using the skip() and limit() directives with your cursor - but to illustrate the scenario, we provide console commands that would achieve the same results. Also, for brevity of code, the limits-checking code is also excluded: //Page 1 db.users.find().limit (10) //Page 2 db.users.find().skip(10).limit(10) //Page 3 db.users.find().skip(20).limit(10) ........ You get the idea. In general, to retrieve page ‘n’ the code looks like this: db.users.find().skip(pagesize*(n-1)).limit(pagesize) However, as the size of your data increases, this approach has serious performance problems. The reason is that every time the query is executed, the full result set is built up, then the server has to walk from the beginning of the collection to the specified offset. As your offset increases, this process gets slower and slower. Also, this process does not make efficient use of the indexes. So typically the ‘skip()’ and ‘limit()’ approach is useful when you have small data sets, and if you’re working with large data sets, you’ll want to consider other approaches. Approach 2: Using find() and limit() The reason the previous approach does not scale very well is the skip() command, and the goal in this section is to implement paging without using the ‘skip()’ command. For this, we’re going to leverage the natural order in the stored data like a timestamp or an id stored in the document. In this example, we’re going to use the ‘_id’ stored in each document. ‘_id’ is a MongoDB ObjectID structure which is a 12-byte structure containing a timestamp, machined, processid, counter, etc. The overall idea is as follows: Read the full article: https://scalegrid.io/blog/fast-paging-with-mongodb/ Learn more about MongoDB hosting: https://scalegrid.io/mongodb/products.html

1. Fast Paging with MongoDB
How to perform one of the most common operations with MongoDB
Read the Blog Post | Dharshan Rangegowda

2. Paging through your data is one of the
most common operations with MongoDB.
Read the Fast Paging with MongoDB Blog Database-as-a-Service |

3. A t ic c a is:
The need to display your results in chunks in your UI. If you’re batch
processing your data, it’s also important to get your paging strategy
correct so your data processing can scale.
Database-as-a-Service |Read the Fast Paging with MongoDB Blog

4. Let’s a k ro n e p .
We’ll cover the two different ways to page through data
in MongoDB. For these examples, we have a CRM
database of user data that we need to page through and
display 10 users at a time. So in effect, our page size is 10.
Here is the structure of our user document:
Database-as-a-Service |
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{
_id,
name,
company,
state
}
Read the Fast Paging with MongoDB Blog

5. Approach 1:
Using skip() and limit()
Read the Fast Paging with MongoDB Blog Database-as-a-Service |

6. Usi s () an m ()
MongoDB natively supports the paging operation using the command directives:
skip(n) tells MongoDB that it should skip ‘n’ results
limit(n) instructs MongoDB that it should limit the result length to ‘n’ results.
Database-as-a-Service |
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//Page 1
db.users.find().limit (10)
//Page 2
db.users.find().skip(10).limit(10)
//Page 3
db.users.find().skip(20).limit(10)
........
Typically, you’ll be using the skip() and limit()
directives with your cursor - but to illustrate the
scenario, we provide console commands that
would achieve the same results.
Also, for brevity of code, the limits-checking code
is also excluded:
Read the Fast Paging with MongoDB Blog

7. Yo g he a.
In general, to retrieve page ‘n’ the code looks like this:
Database-as-a-Service |
1 db.users.find().skip(pagesize*(n-1)).limit(pagesize)
Read the Fast Paging with MongoDB Blog

8. However, as the size of your data
increases, this approach has serious
performance problems.
Read the Fast Paging with MongoDB Blog Database-as-a-Service |

9. The on h :
Every time the query is executed, the full result set is built up, then the server has to
walk from the beginning of the collection to the specified offset. As your offset
increases, this process gets slower and slower. Also, this process does not make
efficient use of the indexes. So typically the ‘skip()’ and ‘limit()’ approach is useful
when you have small data sets, and if you’re working with large data sets, you’ll want
to consider other approaches.
Database-as-a-Service |Read the Fast Paging with MongoDB Blog

10. Approach 2:
Using find() and limit()
Read the Fast Paging with MongoDB Blog Database-as-a-Service |

11. Usi f () an m ()
The reason the previous approach does not scale very well is the skip() command,
and the goal in this section is to implement paging without using the ‘skip()’
command. For this, we’re going to leverage the natural order in the stored data like a
timestamp or an id stored in the document. In this example, we’re going to use the
‘_id’ stored in each document. ‘_id’ is a MongoDB ObjectID structure which is a
12-byte structure containing a timestamp, machined, processid, counter, etc.
Database-as-a-Service |Read the Fast Paging with MongoDB Blog

12. The al a s ol s:
Database-as-a-Service |
skip(n) tells MongoDB that it should skip ‘n’ results.
limit(n) instructs MongoDB that it should limit the result length to ‘n’ results.
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//Page 1
db.users.find().limit(pageSize);
//Find the id of the last document in this page
last_id = ...
//Page 2
users = db.users.find({'_id'> last_id}). limit(10);
//Update the last id with the id of the last document in this page
last_id = ...
Read the Fast Paging with MongoDB Blog

13. Thi p a h ra :
The inherent order that exists in the “_id” field. Also, since the “_id” field is indexed
by default, the performance of the find operation is very good. If the field you’re using
is not indexed, your performance will suffer – so it’s important to make sure that
field is indexed.
Database-as-a-Service |Read the Fast Paging with MongoDB Blog

14. Ad i na y,
if you’d like your data sorted in a particular order for your paging, then you can also
use the sort() clause with the above technique. It’s important to ensure that the sort
process is leveraging an index for best performance. You can use the .explain() suffix
to your query to determine this:
Database-as-a-Service |
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users = db.users.find({'_id'> last_id}). sort(..).limit(10);
//Update the last id with the id of the last document in this page
last_id = ...
Read the Fast Paging with MongoDB Blog

15. Tha s r a g
Fast Paging with MongoDB
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