Non-uniform memory access (NUMA) is a computer memory design used in multiprocessing, where the memory access time depends on the memory location relative to the processor. Under NUMA, a processor can access its own local memory faster than non-local memory (memory local to another processor or memory shared between processors). Yarn Containers can make benefit of this NUMA design to get better performance by binding to a specific NUMA node and all subsequent memory allocations will be served by the same node, reducing remote memory accesses. NUMA support for YARN Container has to be enabled only if worker node machines has NUMA support.
LinuxContainerExecutor
(LCE)1) Enable/Disable the NUMA awareness
This property enables the NUMA awareness feature in the Node Manager for the containers. By default, the value of this property is false which means it is disabled. If this property is true
then only the below configurations will be applicable otherwise they will be ignored.
In yarn-site.xml
add
<property> <name>yarn.nodemanager.numa-awareness.enabled</name> <value>true</value> </property>
2) NUMA topology
This property decides whether to read the NUMA topology from the system or from the configurations. If this property value is true then the topology will be read from the system using numactl --hardware
command in UNIX systems and similar way in windows. If this property is false then the topology will be read using the below configurations. Default value of this configuration is false which means NodeManager will read the NUMA topology from the below configurations.
In yarn-site.xml
add
<property> <name>yarn.nodemanager.numa-awareness.read-topology</name> <value>false</value> </property>
3) Numa command
This property is passed when yarn.nodemanager.numa-awareness.read-topology
is set to true. It is recommended to verify the installation of numactl
command in the Linux OS of every node.
Use /usr/bin/numactl --hardware
to verify. Sample output of /usr/bin/numactl --hardware
available: 2 nodes (0-1) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 node 0 size: 191297 MB node 0 free: 186539 MB node 1 cpus: 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 node 1 size: 191383 MB node 1 free: 185914 MB node distances: node 0 1 0: 10 21 1: 21 10
In yarn-site.xml
add
<property> <name>yarn.nodemanager.numa-awareness.numactl.cmd</name> <value>/usr/bin/numactl</value> </property>
4) NUMA nodes id’s
This property is used to provide the NUMA node ids as comma separated values.It will be read only when the yarn.nodemanager.numa-awareness.read-topology
is false.
In yarn-site.xml
add
<property> <name>yarn.nodemanager.numa-awareness.node-ids</name> <value>0,1</value> </property>
5) NUMA Node memory
This property will be used to read the memory(in MB) configured for each NUMA node specified in yarn.nodemanager.numa-awareness.node-ids
by substituting the node id in the place of <NODE_ID>
.It will be read only when the yarn.nodemanager.numa-awareness.read-topology
is false.
In yarn-site.xml
add
<property> <name>yarn.nodemanager.numa-awareness.<NODE_ID>.memory</name> <value>191297</value> </property>
The value passed is the per node memory available , from the above sample output of numactl --hardware
the value passed for the property is the memory available i.e 191297
6) NUMA Node CPUs
This property will be used to read the number of CPUs configured for each node specified in yarn.nodemanager.numa-awareness.node-ids
by substituting the node id in the place of <NODE_ID>
.It will be read only when the yarn.nodemanager.numa-awareness.read-topology
is false.
In yarn-site.xml
add
<property> <name>yarn.nodemanager.numa-awareness.<NODE_ID>.cpus</name> <value>48</value> </property>
referring to the numactl --hardware
output , number of cpu’s in a node is 48
.
7) Passing java_opts for map/reduce
Every container has to be aware of NUMA and the JVM can be notified via passing NUMA flag. Spark, Tez and other YARN Applications also need to set the container JVM Opts to leverage NUMA Support.
In mapred-site.xml
add
<property> <name>mapreduce.reduce.java.opts</name> <value>-XX:+UseNUMA</value> </property> <property> <name>mapreduce.map.java.opts</name> <value>-XX:+UseNUMA</value> </property>
Property | Default value |
---|---|
yarn.nodemanager.numa-awareness.enabled | false |
yarn.nodemanager.numa-awareness.read-topology | false |
In linux, by default numa balancing is by default off. For more performance improvement, NumaBalancing can be turned on for all the nodes in cluster
echo 1 | sudo tee /proc/sys/kernel/numa_balancing
1) NodeManager log
In any of the NodeManager, grep log file using below command
grep "NUMA resources allocation is enabled," *
Sample log with LinuxContainerExecutor
enabled message
<nodemanager_ip>.log.2022-06-24-19.gz:2022-06-24 19:16:40,178 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.linux.resources.numa.NumaResourceHandlerImpl (main): NUMA resources allocation is enabled, initializing NUMA resources allocator.
2) Container Log
Grep the NodeManager log using below grep command to check if a container is assigned with NUMA node resources.
grep "NUMA node" | grep <container_id>