Top ten issues when dealing with Hadoop 
For users, the top ten most challenging issues with Hadoop are as follows:
1. Hadoop Distributed File System (HDFS) has a single point of failure.
2. Hadoop integration, deployment, configuration manage-ment, and performance optimization are time-consuming and labor-intensive.
3. Hadoop hogs memory, storage, input/output, and network bandwidth. 
4. Hadoop cluster management tools vary widely in functionality. 
5. Hadoop mixed-workload management is tricky.
6. HDFS and Hive are not optimal for real-time applications. 
7. Integrated tools are lacking for management of Hadoop, NoSQL, RDBMS, and EDW platforms. 
8. Hadoop skills are in short supply and the Hadoop commu-nity, not vendors, are often the best support resource for troubleshooting and optimization.
9. Monitoring, diagnostic, and troubleshooting tools for Hadoop are often inadequate. 
10. Security, governance, usage accounting, and information life-cycle management tools for Hadoop are mostly nonexistent.
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