rollup.js
Webpack
npm
Parcel
Brunch
JSPM
stealjs
esbuild
Hadoop
Apache Spark
PostgreSQL
Apache Flink
Apache Cassandra
MongoDB
Apache Storm
Apache Kafka
rollup.js HadoopNo rollup.js videos yet. You could help us improve this page by suggesting one.
Based on our record, rollup.js should be more popular than Hadoop. It has been mentiond 46 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
A big part of my work revolves around JavaScript tooling, and as such it's important to keep an eye on the ecosystem and see where things are going. It's no secret that recently lots of projects are native-ying (??) parts of their codebase, or even rewriting them to native languages altogether. Esbuild is one of the first popular and successful examples of this, which was written in Go. Other examples are Rspack... - Source: dev.to / 8 days ago
If we don't want to use Vite or SvelteKit, or if we don't have the means to use them, then we need to integrate Svelte with our own environment. In our daily development, we usually use webpack or Rollup as our project's module management packaging tool. Therefore, I will introduce these two environments, how to build the Svelte environment. - Source: dev.to / 8 days ago
Unlike Webpack, the Vite DevServer only compiles files when they are requested. It leverages ES module imports, which allow JS files to import other files without needing to bundle them together during development. When one file changes, only that file needs to be re-compiled, and the rest can remain unchanged. Project files are compiled with Rollup.js. Third-party dependencies in node_modules are pre-compiled... - Source: dev.to / 3 months ago
Besides Webpack, there are many other popular web bundlers available, such as Parcel, Esbuild, Rollup, and more. They all have their own unique features and strengths, and you should make your decision based on the needs and requirements of your specific project. Please refer to their official websites for details. - Source: dev.to / 7 months ago
In the Node.js ecosystem, bundling is typically handled by third-party tools rather than Node.js itself. Some of the most popular bundlers in the Node.js world include Webpack, Rollup, and Parcel, offering features like code splitting, tree shaking, and hot module replacement. - Source: dev.to / 8 months ago
Did you check out tools like https://hadoop.apache.org/ ? Source: about 1 year ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 1 year ago
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / over 1 year ago
Webpack - Webpack is a module bundler. Its main purpose is to bundle JavaScript files for usage in a browser, yet it is also capable of transforming, bundling, or packaging just about any resource or asset.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
npm - npm is a package manager for Node.
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
Parcel - Blazing fast, zero configuration web application bundler
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
