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A curated Chinese-language knowledge base for learning big data engineering and passing big data interviews, covering Java fundamentals, distributed systems theory, and deep dives into Hadoop, Hive, Spark, Flink, HBase, Kafka, and Zookeeper.
A curated Chinese-language knowledge base for learning big data engineering and passing big data interviews, covering Java fundamentals, distributed systems theory, and deep dives into Hadoop, Hive, Spark, Flink, HBase, Kafka, and Zookeeper.Is this a software project or a collection of study notes?It is a collection of markdown articles and notes organized by topic, not a library or tool — the author's own blog/public-account posts curated into a structured learning path.
It is a collection of markdown articles and notes organized by topic, not a library or tool — the author's own blog/public-account posts curated into a structured learning path.How is the content organized?It splits into four sections: basics (Java, NIO, concurrency, JVM, distributed theory, Zookeeper, RPC, Netty), framework deep-dives (Hadoop, Hive, Spark, Flink, HBase, Kafka, Zookeeper), practical advanced articles, and an interview-prep section with question compilations.
It splits into four sections: basics (Java, NIO, concurrency, JVM, distributed theory, Zookeeper, RPC, Netty), framework deep-dives (Hadoop, Hive, Spark, Flink, HBase, Kafka, Zookeeper), practical advanced articles, and an interview-prep section with question compilations.Is all the content freely accessible?Most of it is, but the per-framework '系统性总结' deep summaries for Hadoop, Hive, Spark, Flink, and HBase are marked as exclusive to subscribers of the author's paid '知识星球' (Zhihu Planet) community.
Most of it is, but the per-framework '系统性总结' deep summaries for Hadoop, Hive, Spark, Flink, and HBase are marked as exclusive to subscribers of the author's paid '知识星球' (Zhihu Planet) community.Where should a beginner start?The README points newcomers to a dedicated roadmap article, '八千里路云和月|从零到大数据专家学习路径指南', which maps out a full path from zero to big data architect.
The README points newcomers to a dedicated roadmap article, '八千里路云和月|从零到大数据专家学习路径指南', which maps out a full path from zero to big data architect.Does it include an interview question bank?Yes, there's a dedicated '大数据开发面试篇' section with compiled interview question sets ('面试系列合集') plus a separate big data algorithms section for interview prep.
Yes, there's a dedicated '大数据开发面试篇' section with compiled interview question sets ('面试系列合集') plus a separate big data algorithms section for interview prep.Which big data frameworks does it cover?Hadoop, Hive, Spark, Flink, HBase, Kafka, and Zookeeper, each with its own learning-path overview and deep-dive articles.
Hadoop, Hive, Spark, Flink, HBase, Kafka, and Zookeeper, each with its own learning-path overview and deep-dive articles.Is this still being updated?It includes yearly curated article collections like '2020精品文章合集' and '2021精品文章合集', indicating it was actively maintained through at least 2021, with practical/advanced content added over time.
It includes yearly curated article collections like '2020精品文章合集' and '2021精品文章合集', indicating it was actively maintained through at least 2021, with practical/advanced content added over time.Why is it called 'God of Big Data'?The name reflects the project's framing as a step-by-step path to mastering big data ('成神之路' = 'road to becoming a god'), going from Java basics all the way to the full big data stack and interview readiness.
The name reflects the project's framing as a step-by-step path to mastering big data ('成神之路' = 'road to becoming a god'), going from Java basics all the way to the full big data stack and interview readiness.What are similar projects?BigData-Notes, flink-learning, hello-algorithm, technology-talk, Java, zju-icicles, JavaFamily, Android
BigData-Notes, flink-learning, hello-algorithm, technology-talk, Java, zju-icicles, JavaFamily, AndroidWhich topics is it in?flink, hdfs, hive, bigdata, hadoop, zookeeper, spark, kafka, study-guide, interview-questions, computer-science, knowledge-base
flink, hdfs, hive, bigdata, hadoop, zookeeper, spark, kafka, study-guide, interview-questions, computer-science, knowledge-base