From 36a66fa90114b492f4562dfa50e6c4eca54ac30f Mon Sep 17 00:00:00 2001 From: Krishna Chaiatanya Date: Fri, 13 Sep 2024 14:05:11 +0530 Subject: [PATCH] Update spark@UljuqA89_SlCSDWWMD_C_.md (#7095) * Update spark@UljuqA89_SlCSDWWMD_C_.md * Update src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md --------- Co-authored-by: Arik Chakma --- src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md b/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md index 206fba2c1..1979aa860 100644 --- a/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md +++ b/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md @@ -1,8 +1,9 @@ # Spark -Apache Spark is an open-source distributed computing system used for big data processing and analytics. It provides an interface for programming entire clusters with implicit data parallelism and fault tolerance. +Apache Spark is an open-source distributed computing system designed for big data processing and analytics. It offers a unified interface for programming entire clusters, enabling efficient handling of large-scale data with built-in support for data parallelism and fault tolerance. Spark excels in processing tasks like batch processing, real-time data streaming, machine learning, and graph processing. It’s known for its speed, ease of use, and ability to process data in-memory, significantly outperforming traditional MapReduce systems. Spark is widely used in big data ecosystems for its scalability and versatility across various data processing tasks. Visit the following resources to learn more: +- [@official@ApacheSpark](https://spark.apache.org/documentation.html) - [@article@Spark By Examples](https://sparkbyexamples.com) - [@feed@Explore top posts about Apache Spark](https://app.daily.dev/tags/spark?ref=roadmapsh)