What is Dask?
Dask is a library that supports parallel computing in Python Extend. Dynamic task scheduling which is optimized for interactive computational workload. Big data collections of Dask extend the common interfaces like NumPy, Pandas, etc.
Most of the BigData analytics will be using Pandas, and NumPy for analyzing big data. All the mentioned packages support a wide variety of computations. But when the dataset doesn’t fit in the memory these packages will not scale. Here comes Dask. When the dataset doesn’t “fit in memory” Dask extends the dataset to “fit into disk”. Dask allows us to easily scale out to clusters or scale down to a single machine based on the size of the dataset.
Dask in Python
Dask is an open-source parallel computing library and it can serve as a game changer, offering a flexible and user-friendly approach to manage large datasets and complex computations.
In this article, we will delve into the world of Dask, How to install Dask, and Its features.