HADOOP_HEAPSIZE=1024

HADOOP_NAMENODE_OPTS=-Xms1024 -Xmx1024 -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+CMSParallelRemarkEnabled -XX:+PrintTenuringDistribution -XX:OnOutOfMemoryError={{AGENT_COMMON_DIR}}/killparent.sh

Both HADOOP_NAMENODE_OPTS and HADOOP_HEAPSIZE are stored in /etc/hadoop/conf/hadoop-env.sh.

You can monitor your heap memory usage several ways:

In HDFS, data and metadata are decoupled. Data files are split into block files that are stored, and replicated, on DataNodes across the cluster. The filesystem namespace tree and associated metadata are stored on the NameNode.

Namespace objects are file inodes and blocks that point to block files on the DataNodes. These namespace objects are stored as a file system image (fsimage) in the NameNode's memory and also persist locally. Updates to the metadata are written to an edit log. When the NameNode starts, or when a checkpoint is taken, the edits are applied, the log is cleared, and a new fsimage is created.

  Important: The NameNode keeps the entire namespace image in memory. The Secondary NameNode, on its own JVM, does the same when creating an image checkpoint.

On average, each file consumes 1.5 blocks of storage. That is, the average file is split into two block files—one that consumes the entire allocated block size and a second that consumes half of that. On the NameNode, this same average file requires three namespace objects—one file inode and two blocks.

The CDH default block size (dfs.blocksize) is set to 128 MB. Each namespace object on the NameNode consumes approximately 150 bytes.

On DataNodes, data files are measured by disk space consumed—the actual data length—and not necessarily the full block size. For example, a file that is 192 MB consumes 192 MB of disk space and not some integral multiple of the block size. Using the default block size of 128 MB, a file of 192 MB is split into two block files, one 128 MB file and one 64 MB file. On the NameNode, namespace objects are measured by the number of files and blocks. The same 192 MB file is represented by three namespace objects (1 file inode + 2 blocks) and consumes approximately 450 bytes of memory.

Large files split into fewer blocks generally consume less memory than small files that generate many blocks. One data file of 128 MB is represented by two namespace objects on the NameNode (1 file inode + 1 block) and consumes approximately 300 bytes of memory. By contrast, 128 files of 1 MB each are represented by 256 namespace objects (128 file inodes + 128 blocks) and consume approximately 38,400 bytes. The optimal split size, then, is some integral multiple of the block size, for memory management as well as data locality optimization.

By default, Cloudera Manager allocates a maximum heap space of 1 GB for every million blocks (but never less than 1 GB). How much memory you actually need depends on your workload, especially on the number of files, directories, and blocks generated in each namespace. If all of your files are split at the block size, you could allocate 1 GB for every million files. But given the historical average of 1.5 blocks per file (2 block objects), a more conservative estimate is 1 GB of memory for every million blocks.

  Important: Cloudera recommends 1 GB of NameNode heap space per million blocks to account for the namespace objects, necessary bookkeeping data structures, and the remote procedure call (RPC) workload. In practice, your heap requirements will likely be less than this conservative estimate.

The default block replication factor (dfs.replication) is three. Replication affects disk space but not memory consumption. Replication changes the amount of storage required for each block but not the number of blocks. If one block file on a DataNode, represented by one block on the NameNode, is replicated three times, the number of block files is tripled but not the number of blocks that represent them.

With replication off, one file of 192 MB consumes 192 MB of disk space and approximately 450 bytes of memory. If you have one million of these files, or 192 TB of data, you need 192 TB of disk space and, without considering the RPC workload, 450 MB of memory: (1 million inodes + 2 million blocks) * 150 bytes. With default replication on, you need 576 TB of disk space: (192 TB * 3) but the memory usage stay the same, 450 MB. When you account for bookkeeping and RPCs, and follow the recommendation of 1 GB of heap memory for every million blocks, a much safer estimate for this scenario is 2 GB of memory (with or without replication).