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Learn MorePros of Dask
Pros of jQuery
Pros of Dask
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Pros of jQuery
- Cross-browser1.3K
- Dom manipulation957
- Power809
- Open source660
- Plugins610
- Easy459
- Popular395
- Feature-rich350
- Html5281
- Light weight227
- Simple93
- Great community84
- CSS3 Compliant79
- Mobile friendly69
- Fast67
- Intuitive43
- Swiss Army knife for webdev42
- Huge Community35
- Easy to learn11
- Clean code4
- Because of Ajax request :)3
- Powerful2
- Nice2
- Just awesome2
- Used everywhere2
- Improves productivity1
- Javascript1
- Easy Setup1
- Open Source, Simple, Easy Setup1
- It Just Works1
- Industry acceptance1
- Allows great manipulation of HTML and CSS1
- Widely Used1
- I love jQuery1
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Cons of Dask
Cons of jQuery
Cons of Dask
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Cons of jQuery
- Large size6
- Sometimes inconsistent API5
- Encourages DOM as primary data source5
- Live events is overly complex feature2
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What is Dask?
It is a versatile tool that supports a variety of workloads. It is composed of two parts:
Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads.
Big Data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of dynamic task schedulers.
What is jQuery?
jQuery is a cross-platform JavaScript library designed to simplify the client-side scripting of HTML.
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What companies use Dask?
What companies use jQuery?
What companies use Dask?
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What tools integrate with Dask?
What tools integrate with jQuery?
What tools integrate with jQuery?
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What are some alternatives to Dask and jQuery?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
PySpark
It is the collaboration of Apache Spark and Python. it is a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.
Celery
Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.