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JWJames Wucalm-engineering-loud-bugs.hashnode.devFeb 6 · 11 min read

Big Data Analytics Tools: What to Use and When

If you talk to ten data teams about “big data analytics,” you’ll probably hear ten different tool names. Hadoop, Spark, Kafka, TensorFlow, Snowflake, Power BI… Most modern big data stacks are built from the same few layers that work together: How yo...

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SKSaket Khopkarlearnaimldswithsk.hashnode.devJan 2 · 6 min read

Day 21 : Introduction to the Big Data Ecosystem

Everyone uses YouTube. Every day there are millions of uploads (could be videos or shorts) on this popular video streaming channel. On top of that billions of people like, comment and share videos globally. These actions generate data, basically a di...

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OAOmar Al-Khaldiomaralkhaldi.hashnode.devOct 19, 2025 · 7 min read

Crash Course : Apache Hive

Introduction to Apache Hive Apache Hive is one of the most widely used tools in the big data ecosystem, providing a powerful interface to query large datasets stored in Hadoop Distributed File System (HDFS) using a familiar SQL-like language called H...

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KMkiran mvkiran12345.hashnode.devSep 18, 2025 · 8 min read

Revolutionizing Big Data With Open Source: Hadoop, Spark, Kafka, and Beyond

Over 90% of data created throughout the globe has been generated over the last couple of years. But much of that data is yet to be properly organized or even processed. It awaits systems capable of dealing with its high volume as well as velocity. It...

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JPJidhun Puthuppattujidhun.hashnode.devAug 29, 2025 · 4 min read

Big Data

In the digital era, data has become one of the most valuable assets. From social media posts and sensor readings to e-commerce transactions and satellite images, the volume of data generated daily is enormous. Traditional data storage and processing ...

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RSRicky Suhanrydatarunner01.hashnode.devAug 7, 2025 · 11 min read

A Deep Dive into Hadoop Ecosystem

As we have already seen with the Big Data and Hadoop components (Article 1 , Article 2), Hadoop Ecosystem is always changing and being adapted for new applications. Large-scale datasets can now be stored, processed, and subjected to data-oriented ana...

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RSRicky Suhanrydatarunner01.hashnode.devJul 21, 2025 · 10 min read

Understanding Big Data Frameworks: Apache Hadoop

In the previous article, we already talking a little bit about big data and Apache Hadoop. Consider once more the hundreds of thousands of commodity hardware nodes and the hundreds of thousands of petabytes (PB) of data. In the context of big data, t...

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APAnamika Patelanamikabigdata.hashnode.devJun 30, 2025 · 3 min read

Understanding YARN: The Hidden Traffic Controller in Hadoop

When we talk about Hadoop, most people think of HDFS (Hadoop Distributed File System) — the giant warehouse where massive amounts of data are stored. But storing data is only half the battle. What happens when multiple teams, processes, or applicatio...

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ZZenvilazenvila.hashnode.devJun 29, 2025 · 5 min read

Machine Learning and Its Tools

What is AI? Artificial Intelligence (AI)Definition: AI is a broad field of computer science that aims to create systems that can mimic human intelligence. It can include rule-based logic. What is Machine Learning? ML is a subset of AI that enables m...

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APAnamika Patelanamikabigdata.hashnode.devJun 26, 2025 · 3 min read

Namenode Vs Datanode: Responsibilities and Failure Handling

When you copy data to HDFS (Hadoop Distributed File System), it is split into fixed-size blocks (default: 128MB or 256MB) and stored across DataNodes. The NameNode does not store the data itself — instead, it stores the metadata: information about wh...

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#hadoop

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Trending tags this week

Big Data Analytics Tools: What to Use and When

Day 21 : Introduction to the Big Data Ecosystem

Crash Course : Apache Hive

Revolutionizing Big Data With Open Source: Hadoop, Spark, Kafka, and Beyond

Big Data

A Deep Dive into Hadoop Ecosystem

Understanding Big Data Frameworks: Apache Hadoop

Understanding YARN: The Hidden Traffic Controller in Hadoop

Machine Learning and Its Tools

Namenode Vs Datanode: Responsibilities and Failure Handling