The memory consumption of hadoop's namenode?
Can anyone give a detailed analysis of memory consumption of namenode? Or is there some reference material ? Can not find material in the network.Thank you!
Answer
I suppose the memory consumption would depend on your HDFS setup, so depending on overall size of the HDFS and is relative to block size. From the Hadoop NameNode wiki:
Use a good server with lots of RAM. The more RAM you have, the bigger the file system, or the smaller the block size.
From https://twiki.opensciencegrid.org/bin/view/Documentation/HadoopUnderstanding:
Namenode: The core metadata server of Hadoop. This is the most critical piece of the system, and there can only be one of these. This stores both the file system image and the file system journal. The namenode keeps all of the filesystem layout information (files, blocks, directories, permissions, etc) and the block locations. The filesystem layout is persisted on disk and the block locations are kept solely in memory. When a client opens a file, the namenode tells the client the locations of all the blocks in the file; the client then no longer needs to communicate with the namenode for data transfer.
the same site recommends the following:
Namenode: We recommend at least 8GB of RAM (minimum is 2GB RAM), preferably 16GB or more. A rough rule of thumb is 1GB per 100TB of raw disk space; the actual requirements is around 1GB per million objects (files, directories, and blocks). The CPU requirements are any modern multi-core server CPU. Typically, the namenode will only use 2-5% of your CPU. As this is a single point of failure, the most important requirement is reliable hardware rather than high performance hardware. We suggest a node with redundant power supplies and at least 2 hard drives.
For a more detailed analysis of memory usage, check this link out: https://issues.apache.org/jira/browse/HADOOP-1687
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