What is Gleam? A Quick Guide for Beginners
Are you looking for a type-safe programming language to build scalable software? Gleam can be a great choice. The number of Gleam programmers has grown significantly in recent months. Let us explore what sets Gleam apart from Rust and Java. Gleam Overview Initially released in 2019, Gleam is a type-safe programming language. Its latest version v1.0.0 was rolled out in March 2024. Designed and developed by Louis Pilfold, Gleam is both user-friendly and powerful. Gleam operates on the BEAM virtual machine, which also powers Elixir. It makes Gleam highly scalable and offers a seamless developer experience. Let us get to know some interesting features of Gleam. Features of Gleam Beginner-friendly Gleam language is easy to learn. Its algebraic data types let you write clear and powerful codes. It uses readable syntaxes that naturally reduce cognitive overhead. You save time by typing fewer characters in place of entire words. For example, you can use fn instead of function. Similarly, for the public, you can write pub. The programming language also provides clear and actionable error messages. Therefore, developers detect and resolve errors quickly. Additionally, Gleam has various tools for building, testing, and deploying web applications. You do not need to buy third-party tools for these jobs. Cross Platform Deployment Cross-platform deployment is a revolutionary feature. It allows you to build highly concurrent apps running across multiple platforms. Gleam lets you employ the same code on different platforms. You can use the same code for the Erlang VM, JavaScript, and native applications. Language Server The Gleam language server makes coding exceptionally easy by suggesting how to finish a code. It also points out code errors and provides quick fixes for them. You also get errors for style issues and unused bits of code. Additionally, the language server automatically handles the code formatting. Since Gleam automates many tasks, you can concentrate on solving problems. Developer-friendly Gleam is a developer-friendly language in many ways. If you have used Rust or JavaScript before, you can easily use its syntax because they are similar. Besides this, catching errors is straightforward in Gleam. Its static type system helps you detect errors while compiling code. Gleam also has tools like todo and @deprecated that significantly enhance the developer experience. Todo helps you define unfinished parts of code, whereas @deprecated annotation makes you aware of outdated features/functions. Gleam also has a standard library covering numerous use cases. It has ready-to-use functions for various programs. It also has packages for databases like MongoDB, Kafka, PostgreSQL, etc. Powerful Type System The Gleam has a robust type system. You can write and edit codes with the help of this static-type framework. As you write codes, it gives you smart tips. Moreover, it eliminates the entire class of runtime errors by enforcing type safety at compile time. You can also use a type system to analyze data concisely. Gleam Type System also supports the building of custom types. You can make domain-specific programs. Scope of Gleam Gleam is a versatile programming language. It can build different web applications, including large-scale distributed systems. Developers can use Gleam for both client-side and server-side development. Web developers also use Gleam to build microservices, thanks to the concurrency model of BEAM VM. In addition to this, Gleam can also perform data transformation and analytical jobs. Community Support The Gleam community has been continuously growing. Regardless of your skill level, you can find a wealth of resources to support your development effort. The gleam community gives you access to numerous tutorials and forums. Also, you can explore its official guides and community-authored blogs. Its active forums and chats allow developers to ask questions and share knowledge. Conclusion Considering everything, it would be right to mention that Gleam is more than just a programming language. It is a powerful tool that helps developers to build, scale, and maintain applications. Its cross-platform capabilities, powerful type system, and user-friendliness make it suitable for modern web development. All in all, this functional programming language is an excellent choice for building reliable and scalable apps. So, whether you are planning to build an application or just an API, you should give Gleam a try.
MongoDB Sharding: Everything You Need to Know About it
Data sharding is the breakthrough technique of the modern data-driven era. It eliminates the limitation that a single database server can store and process only a certain amount of data. Data sharding enables users to store the data across different database servers. Therefore, it improves response time and supports scalability. This blog post gives you in-depth knowledge about MongoDB sharding. It also provides you guidance on setting up this sharding. MongoDB Overview Before we learn about MongoDB sharding, let’s get to know MongoDB. MongoDB is an open-source document-oriented NoSQL database. It has been used by several prominent companies, including Facebook, Google, and eBay. MongoDB lets users store data in flexible, JSON-like documents. Since this database features schema design, it can handle unstructured data. Consequently, it has become the first choice for most modern web applications. Unlike conventional relational database systems, MongoDB can manage a large amount of data. The best thing is that users can integrate MongoDB with all prominent programming languages, such as PHP, Python, Java, Node.js, C, C++, and more. What is MongoDB Sharding? Most companies use NoSQL databases to deal with storage and computing requirements of high-volume data. Sharding in MongoDB is a method that helps individuals distribute a database horizontally through different nodes. These nodes or servers are called “Shards”. Each shard can handle a portion of the data, creating a sharded cluster. It helps MongoDB manage the large volume of data and user concurrency efficiently. Each shard works as a unique database in a sharded cluster. They are accountable for storing and handling data. As soon as the data is added to the cluster, the balancer of MongoDB reallocates it across the shards. Thus it makes sure the workload is equally distributed. The architecture of sharding consists of the following elements: Shard Servers These servers are separate nodes within the sharded cluster. Each node collects a subset of the data and acts as an independent database. MongoDB circulates data across the shard servers to ensure even distribution. Config Servers These servers keep the metadata and configuration information for the sharded cluster. Query Routers Also referred to as “Mongos”, these routers work as the interface between the sharded cluster and applications. Query routers receive requests and queries to the suitable shards and combine results as required. As Mongos processes hide the underlying sharding complexity from the application, it looks like a single logical database. Shard key The shard key is a field that determines how data will be distributed in different shards. For even data distribution and efficient querying, it is necessary to choose the right shard key. Chunk A chunk constitutes a data range housed within a shard. It is decided by the shard key. Chunks are data migration units between shards. Balancer Balancer assures the uniform distribution of data amid the shards. Once data is added or eliminated, the balancer distributes data chunks between shards. Steps to Set up MongoDB Sharding You will require three servers to set up sharding in MongoDB. One for the config server and another for the Mongos instance. The last one is required for the shards. Here are step-by-step instructions to set up sharding in MongoDB. 1. Make a Directory Using Config Server First, you need to create a directory for the config server data. You can do this by running the below command on the 1st server. mkdir /data/configdb 2. Begin MongoDB in Config Mode Once you have created the directory, your next step will be starting MongoDB in config mode on the 1st server. Use this command in order to do it. mongod –configsvr –dbpath /data/configdb –port 27019 The command will begin the config server on port 27019 and store all the data in the /data/configdb directory. Note: We are employing the –configsvr flag to specify this server’s role as a config server. 3. Start Mongos Instance Next, start the process of Mongos instance. It will route queries to the accurate shards depending on the sharding key. Use the following command to begin this process. mongos –configdb <config server>:27019 Remember, you have to replace <config server> with the hostname/IP address of the machine where the config server is running. 4. Connect to Mongos Instance Use MongoDB shell to connect to Mongos instance. Below is the command to perform this. mongo –host <mongos-server> –port 27017 In the above command, replace <mongos-server> with the IP address or hostname of the server running the mongos instance. The command will open up the MongoDB shell and let you interact with Mongo’s instance, and add servers to the cluster. 5. Add Servers to Clusters Once you are connected to the mangos instance, add servers to the cluster. Use the following command: sh.addShard(“<shard-server>:27017”) In the above command, you need to replace <shard-server> with the hostname or IP address of the server running the shard. It will add the shard to the cluster so that it is available for utilization. Repeat this step for each shard you need to add to the cluster. 6. Permit Sharding for Database In the end, you need to enable sharding for a database. Here is the command for this process: sh.enableSharding(“<database>”) Replace <database> with the name of the database you want to shard. It will allow sharding for the particular database, enabling you to share its data across different shards. Congratulations! Now you have a fully functional MongoDB sharded cluster to handle high-traffic loads. Final Words Undoubtedly, MongoDB sharding is a robust technique supporting the horizontal scaling of databases. It allows a database to handle extensive data loads without compromising on performance. We hope this post gives you adequate information on MongoDB sharding. You can leverage the power of sharding and make the best use of your hardware resources.
