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What is this?
This is a comprehensive Chinese-language study guide covering the big data ecosystem: Hadoop, Hive, Spark, Storm, Flink, HBase, Kafka, Zookeeper, Flume, Sqoop, Azkaban, and Scala.
This is a comprehensive Chinese-language study guide covering the big data ecosystem: Hadoop, Hive, Spark, Storm, Flink, HBase, Kafka, Zookeeper, Flume, Sqoop, Azkaban, and Scala.Is this a tutorial series or a reference book?It's a collection of markdown notes organized by topic, each covering concepts plus hands-on cluster setup and API usage, essentially a self-study curriculum rather than a runnable codebase.
It's a collection of markdown notes organized by topic, each covering concepts plus hands-on cluster setup and API usage, essentially a self-study curriculum rather than a runnable codebase.How is the content organized and where should I start?It's structured chapter by chapter starting with Hadoop (HDFS, MapReduce, YARN) and cluster setup, then moves through Hive, Spark, Storm, Flink, HBase, Kafka, Zookeeper, Flume, Sqoop, Azkaban, and finally Scala as a standalone language primer.
It's structured chapter by chapter starting with Hadoop (HDFS, MapReduce, YARN) and cluster setup, then moves through Hive, Spark, Storm, Flink, HBase, Kafka, Zookeeper, Flume, Sqoop, Azkaban, and finally Scala as a standalone language primer.Do I need prior Java or Linux experience to follow along?Yes, the guides assume Linux-based cluster installs and use Java APIs throughout (e.g. HDFS Java API, HBase Java API, Zookeeper's Apache Curator client), so basic Java and Linux shell familiarity is expected.
Yes, the guides assume Linux-based cluster installs and use Java APIs throughout (e.g. HDFS Java API, HBase Java API, Zookeeper's Apache Curator client), so basic Java and Linux shell familiarity is expected.Is this available only in Chinese?Yes, the entire guide is written in Chinese; an offline reading version is distributed via a WeChat public account rather than as a packaged ebook on GitHub.
Yes, the entire guide is written in Chinese; an offline reading version is distributed via a WeChat public account rather than as a packaged ebook on GitHub.Who is this guide for?It's aimed at beginners entering the big data field who want a structured path from distributed storage and compute basics through stream processing and workflow scheduling.
It's aimed at beginners entering the big data field who want a structured path from distributed storage and compute basics through stream processing and workflow scheduling.Does it cover both batch and stream processing frameworks?Yes, it covers Spark (Core, SQL, Streaming), Storm, and Flink for stream and batch processing, alongside Hive and HBase for storage and querying.
Yes, it covers Spark (Core, SQL, Streaming), Storm, and Flink for stream and batch processing, alongside Hive and HBase for storage and querying.Is cluster setup included or just theory?Both: each major component has dedicated chapters for standalone/pseudo-distributed setup and full cluster deployment, often paired with Zookeeper for high availability, in addition to concept explanations.
Both: each major component has dedicated chapters for standalone/pseudo-distributed setup and full cluster deployment, often paired with Zookeeper for high availability, in addition to concept explanations.Why is Scala included alongside the big data tools?Scala is covered as a standalone language primer because it's the native language for Spark development, with chapters on data types, collections, pattern matching, and implicits.
Scala is covered as a standalone language primer because it's the native language for Spark development, with chapters on data types, collections, pattern matching, and implicits.What's in the 'public content' section at the end?It covers common packaging methods for big data applications, i.e. how to package and deploy jobs for the frameworks discussed earlier.
It covers common packaging methods for big data applications, i.e. how to package and deploy jobs for the frameworks discussed earlier.What are similar projects?God-Of-BigData, spark, flink-learning, presto, trino, data-science-ipython-notebooks, doris, technology-talk
God-Of-BigData, spark, flink-learning, presto, trino, data-science-ipython-notebooks, doris, technology-talk