What are the main components of the Hadoop ecosystem?

The main components of the Hadoop ecosystem include the following aspects:
1. Hadoop core components: including Hadoop Distributed File System (HDFS) and Hadoop MapReduce.
2. Hadoop storage and computing engines: such as Apache Hive, Apache Pig, Apache HBase, and Apache Spark, used for data storage, processing, and analysis.
3. Hadoop data integration and workflow management tools: including Apache Sqoop, Apache Flume, and Apache Oozie, used for data import/export and workflow management.
4. Hadoop data querying and analysis tools: such as Apache Drill, Apache Impala, and Apache Phoenix, used for SQL querying and analysis on Hadoop data.
5. Hadoop data visualization tools: including Apache Zeppelin, Tableau, and QlikView, used for visualizing and analyzing data in Hadoop.
6. Hadoop security management and data governance tools: such as Apache Ranger, Apache Atlas, and Apache Knox, used for security management and data governance in Hadoop clusters.
7. Hadoop cloud computing and containerization support tools: such as Apache Mesos, Apache YARN, and Docker, used for deploying and managing Hadoop clusters in cloud and containerized environments.
8. Hadoop machine learning and AI tools: such as Apache Mahout, Apache MXNet, and TensorFlow, used for machine learning and AI tasks in the Hadoop environment. These components and tools form the Hadoop ecosystem, providing a rich set of functionalities and toolchains to support storage, processing, analysis, and mining of large-scale data.