Cara menggunakan mongodb query benchmark

The massive volumes data generated by modern interconnected systems and devices has spawned a new kind of database known as NoSQL. Perhaps the best known of this new breed of non-relational database is MongoDB. Unlike traditional relational databases (RDBMSes), MongoDB does not contain tables. Instead, it stores data as collections of documents.

In the blog, we learned how to create a new database and collection using the Navicat for MongoDB database management & design tool. In today's follow-up, we'll learn about MongoDB documents and add some to our collection.

While MongoDB shares some of the same terms as those of traditional RDBMSes, others are unique to NoSQL databases. To help clarify, here's a table that compares RDBMS terminology to that of MongoDB:

MongoDB stores data as documents. BSON is a binary representation of JSON documents, though it contains additional data types, in addition to JSON. MongoDB documents are composed of field:value pairs and have the following structure:

{
   field1: value1,
   field2: value2,
   field3: value3,
   ...
   fieldN: valueN
}

The value of a field can be any valid BSON data type, including other documents, arrays, and arrays of documents. Here's and example of a document that contains information about an American city. Notice the different data types:

// 1
{
    "_id": "01005",
    "city": "BARRE",
    "loc": [
        -72.108354,
        42.409698
    ],
    "pop": NumberInt("4546"),
    "state": "MA"
}

// 2
{
    "_id": "01012",
    "city": "CHESTERFIELD",
    "loc": [
        -72.833309,
        42.38167
    ],
    "pop": NumberInt("177"),
    "state": "MA"
}

// 3
//etc...

In the last blog, we created a database named "my_mongo_db" and collection named "my_first_collection". Now, we'll add some data to the collection in the form of documents.

• The first step is to open the collection that we wish to add the document to. Select the "my_first_collection" object in the Object pane and click the Open Collection button on the Objects toolbar:
  
  
  
  That will open the collection in a new tab.


• You'll find the Document operations at the bottom of the tab. Click the Plus sign to add a document:
  
  


• In the Add Document dialog, enter the following fields, which are similar to those of the document samples above:

  {
      "_id": "01005",
      "city": "BARRE",
      "loc": [
          -72.108354,
          42.409698
      ],
      "pop": 4546,
      "state": "MA"
  }
  

  
  
  


• It's a good idea to validate the document before saving it. You can do that via the Validate button. The above data should produce a success message. Should errors be encountered, an error message will be presented with the first error in the document. The error will also include the line and column number in order to easily identify the error in the document:
  
  


• Click the Add button to close the dialog and save the new document. You should now see it in the Collection tab:
  
  

You can add more documents by following the same process as above:

Now that we've learned how to add documents to our collection, in the next blog, we'll cover how to view, delete, and edit documents in Navicat for MongoDB.

The Query Profiler diagnoses and monitors performance issues. This monitoring can expose slow-running queries and their key performance statistics in the Atlas UI. You can explore a sample of historical queries for up to the last 24 hours without additional cost or performance overhead.

Atlas collects and displays statistics from any of your

Note

Serverless instances

You access the Query Profiler for a serverless instances from the Monitoring tab.

The Profiler displays one aspect, such as Operation Execution Time or Server Execution Time (serverless instances), that could reveal slow database operations over a set time frame. It displays this data in both a chart and a table that each can filter on aspect and time frame.

Atlas manages the threshold for slow operations for each mongod host based on average operation execution time on that host.

Note

To opt out of the Atlas-managed slow operation threshold and instead use a fixed slow query threshold of 100 milliseconds, use the Atlas Administration API. See