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SQL is the language which forms the basis for most database management systems. Over the recent years, NoSQL has gained popularity because of its ability to handle and process multiple data types. Built using NoSQL, MongoDB is the most popular database management system. MongoDB is and open source software and has the ability to handle unstructured data. It has also been expanding its user base. A lot of organizations are moving to NoSQL database management systems. The major cause is the increasing number of collections and documents in their data. For an organization, better database performance means better output and increased efficiency. So let’s analyze some major MongoDB performance features. 1. MongoDB Performance monitoring MongoDB released a free monitoring tool in the cloud offering support to replica sets and standalone instances. The process of setting up MongoDB performance monitoring is easy to enable and user-friendly. When used, it uploads the data periodically to the cloud. Post successful enabling, the user is provided with a URL. This opens the entire MongoDB performance statistics uploaded over the last 24 hours. Performance Metrics display several parameters. These include: 1. Operation execution time 2. Disk utilization 3. Memory 4. Network 5. Opcounters 6. System CPU Usage 7. Queues and Query targeting. 2. Database Logging Another feature which affects the MongoDB performance is its ability to upload information to the cloud. MongoDB server and clients are proactive in uploading data to the server log file, provided the feature has been enabled. The log information is built of many components. Its main aim is to categorize the messages sent to the log file. This optimizes the process of performance tuning, the verbosity for which can be decided. 3. Database Profiling (Capturing Query) By default, the database profiling capability is disabled. A MongoDB database profiler is used to collect data for those specific operations that function against a mongodb instance. The choice of data to be collected stays with the user. One can collect the entire data set or specific instance parameters’ data. One such instance would be operations taking more time than the value of slowms. Database profiler plays a major role in improving the MongoDB performance. 4. Measuring replication lag performance Replication lag is the measure of the distance between the secondary and primary node, the latter being behind. A best-case scenario brings this distance as close to zero as possible. In technical terms, replication lag is the delay between the operation (primary) and the application of the operation (secondary). This affects the MongoDB performance and most common issue that arises is when secondary storage runs out of memory to attend to oplogs and build indexes. An optimized MongoDB system will have a minimal unintended delay which can be monitored. 5. Plan Explanation In simple terms, Explain Plan offers a flow of operations to understand how the process was executed. Like other database systems, MongoDB also offers the ability to explain the operations. The results appear in the form of a tree, each branch specifying a specific stage. Further, all the events of a specific stage (documents and indexes) are forwarded to the parent node while the leaf nodes are responsible for the collections (or indices). This feature helps analyze and work on the performance tuning of the database. The process of getting an explanation is as simple as adding ‘explain’ to the query. Some common keys to look for in such a scenario are ‘totalKeysExamined’, ’totalDocsExamined’, and ‘executionTimeMillis’. There are a number of factors, each contributing to performance tuning MongoDB. All the features discussed above need the user to maintain a good hold over MongoDB performance monitoring while tweaking its properties to get the best output over time. We at OptimizDBA can help you improve the performance of your MongoDB by providing actionable steps tailored to suit your application needs. Contact us to know more.
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