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Mongodb Match

Definition of Mongodb Match

MongoDB provides different functionality to the user, in which that match is one of the functions provided by MongoDB. Basically, it is called the Mongodb operator and it is used to filter the MongoDB document as per our requirement. In other words, The MongoDB $match administrator channels the reports to pass just those records that match the predetermined condition(s) to the upcoming pipeline stage. Basically, MongoDB provides the different match operators such as $match and $count, etc, to the user and we can utilize them as per our requirement. We can also use a match operator for the aggregation pipeline.

Syntax:

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{$match: {specified required query statement}}

Explanation

In the above syntax, we use the $match Mongodb operator as shown. Here $ match is used to specify the match operator and inside the bracket, we need to write a specified required query statement that matches the condition. Basically, the query statement depends on the user’s requirement.

How match works in Mongodb?

Now let’s see how the match operator works in Mongodb as follows. It is particularly viable in the event that you place the $match as right on time as conceivable in the total pipeline that restricts the complete number of records in the total pipeline. When $match is set at the absolute starting point of a pipeline, the question can exploit records.

The $where cannot be utilized in $match questions as a component of the accumulation pipeline.

At the point when you start with Mongodb, you will utilize the discover() order for questioning information and it will presumably be adequate, however, when you begin doing much else progress than information recovery, you should find out about the Mongodb total pipeline.

  • $match() stage – channels those archives we need to work with, those that fit our necessities
  • $group() stage – does the total work
  • $sort() stage – sorts the subsequent reports the manner in which we require (climbing or diving)

The contribution of the pipeline can be one or a few assortments.

The pipeline then, at that point performs progressive changes on the information until our objective is accomplished.

Thus, we can separate a mind-boggling inquiry into simpler stages, in every one of which we complete an alternate procedure on the information. In this way, before the finish of the inquiry pipeline, we will have accomplished all that we needed.
This methodology permits us to check whether our question is working appropriately at each stage by inspecting the two its information and the yield. The yield of each stage will be the contribution of the next. There is no restriction to the number of stages utilized in the inquiry, or how we join them.
Now let’s see what the restrictions for matches in Mongodb are as follows.
The $match inquiry grammar is indistinguishable from the perused activity question punctuation; for example, $match doesn’t acknowledge crude collection articulations. To remember accumulation articulation for $match, utilize a $specifed expr question articulation:

{ $match: { $specifed expr: { <required indicated total articulation inquiry statement> }

You can’t utilize $where in $match questions as a feature of the collection pipeline.

You can’t utilize $near or $nearSphere in $match inquiries as a component of the accumulation pipeline. As another option, you can buy the same token:

Use the $geoNear stage rather than the $match stage.

Use $geoWithin inquiry administrator with $center or $centerSphere in the $match stage.

To utilize $text in the $match stage, the $match stage must be the main phase of the pipeline. Perspectives don’t uphold text search.

Examples

Now let’s see different examples of Mongodb match for better understanding as follows. First, we need to create the collection by using the following statement as follows. Before the creation of the collection, we need to create the database as follows.

Explanation

Here we created a sample database by using the above statement and now create a collection inside the database by using the following statement as follows.

db.stusent( document )

Explanation

By using the above statement we created a student collection and we have the following document as follows,

{"_id":{"$oid":"60e88f66694de57586da756e"},"name":"jenny","result":"pass","detp":"comp"}
{"_id":{"$oid":"60e8900f694de57586da756f"},"name":"Rohit","result":"pass","dept":"comp"}
{"_id":{"$oid":"60e8903f694de57586da7570"},"name":"Pooja","result":"faile","dept":"mech"}
{"_id":{"$oid":"60e89068694de57586da7571"},"name":"Sameer","result":"pass","dept":"comp"}
{"_id":{"$oid":"60e89094694de57586da7572"},"name":"Rohit","result":"pass","dept":"comp"}

Now we can perform the match operator as follows.

db.student.aggregate([{ $match : { name : "jenny" } } ] );

Explanation

Suppose we need to find those student names that have jenny at that time we can use the above statement. In this example first, we need to specify the collection name followed by the aggregate keyword and inside the bracket, we need to specify the required condition or we can say that query statement. In this example, we need to find student names whose names start with jenny as shown. This final output of the above statement we illustrated by using the following screenshot as follows.

mongodb match 1

Now let’s see another example of the Mongodb match as follows.
Suppose we need to find those student studies in the comp department at that time we need to use the following statement as follows.

db.student.aggregate([{ $match : { dept : "comp" } } ] );

Explanation

By using the above statement we try to find those student studies in comp. In this example first, we need to specify the collection name followed by the aggregate keyword and inside the bracket, we need to specify the required condition or we can say that query statement. Here we try to match the department with the department name that dept = comp as shown in the above statement. This final output of the above statement we illustrated by using the following screenshot as follows.

mongodb match 2

Now let’s see the same example as follows.

In this example, we need to find out those students studying in the mech department as follows.

db.student.aggregate([{ $match : { dept : "mech" } } ] );

Explanation

This final output of the above statement we illustrated by using the following screenshot as follows.

mongodb match 3

So in this way, we can implement match in Mongodb, here we can also use groups as per user requirements.

Conclusion

We hope from this article you learn the Mongodb match. From the above article, we have learned the basic syntax of the match and we also see different examples of the match. From this article, we learned how and when we use Mongodb match.

Recommended Articles

This is a guide to Mongodb Match. Here we discuss the definition, syntax, How match works in Mongodb? Examples, and code implementation. You may also have a look at the following articles to learn more –

  1. MongoDB Join
  2. MongoDB findOne()
  3. MongoDB group by
  4. MongoDB Database
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