Tag Archives: Linux operation and maintenance

Message log output sbridge: Handling MCE memory error error

/The var/log/message system log is always output, causing the/partition disk to be full

sbridge: HANDLING MCE MEMORY ERROR
kernel: CPU 8: Machine Check Exception: o Bank 5: cc00020000010090
kernel: TSC O ADDR 2068ce8080 MISC 40109086 PROCESSOR O: 206d6 TIME 1634693540 SOCKET 1 APIC 20

resolvent:

 rmmod -v sb_edac

[Solved] ELK Log System Error: “statusCode“:429,“error“:“Too Many Requests“,“message“ Data too large

Elk log system error

The error information is as follows:

{"statusCode":429,"error":"Too Many Requests","message":"[circuit_breaking_exception] [parent] Data too large, data for [indices:data/write/bulk[s]] would be [2087165840/1.9gb], which is larger than the limit of [2040109465/1.8gb], real usage: [2087165392/1.9gb], new bytes reserved: [448/448b], usages [request=0/0b, fielddata=182738/178.4kb, in_flight_requests=448/448b, model_inference=0/0b, accounting=89449992/85.3mb], with { bytes_wanted=2087165840 & bytes_limit=2040109465 & durability=\"PERMANENT\" }"}

Du Niang said something, which probably means that the memory given to ES is not enough. However, there is no timely recovery of memory
too much data leads to insufficient memory. You can set the memory limit of fielddata, which is 60% by default

Solution 1: modify the configuration file

Modify the ES configuration file and add the following configuration
[ root@sjyt -node-1 ~]# vim /etc/elasticsearch/elasticsearch.yml

# Avoid OOM, which can have a significant impact on the cluster, by combining request and fielddata breakers to ensure that the combination of the two does not use more than 70% of the heap memory.
indices.breaker.total.limit: 80%

# With this setting, the longest unused (LRU) fielddata will be reclaimed to make room for new data   
indices.fielddata.cache.size: 10%

# fielddata breaker defaults to set the heap as the upper limit of fielddata size.
indices.breaker.fielddata.limit: 60%

The #request breaker estimates the size of structures that need to complete other request parts, such as creating an aggregation bucket, with a default limit of 40% of the heap memory.
indices.breaker.request.limit: 40%

#Longest unused (LRU) fielddata will be reclaimed to make room for new data Must add configuration
indices.breaker.total.use_real_memory: false

After removing the note:

indices.breaker.total.limit: 80%  
indices.fielddata.cache.size: 10%
indices.breaker.fielddata.limit: 60%
indices.breaker.request.limit: 40%
indices.breaker.total.use_real_memory: false

Solution 2: dynamic setting

Reference connection: https://blog.csdn.net/sdlyjzh/article/details/48035723

PUT /_cluster/settings
{
"persistent" : {
"indices.breaker.fielddata.limit" : "40%"
}
}

When the size of the fielddata circuit breaker exceeds the set value, the data too large mentioned at the beginning will appear.

Docker delete error response from daemon: Conflict: unable to delete xxxxx solution

An error is reported when the docker image is deleted. After docker images , the output is as follows:

REPOSITORY                             TAG                        IMAGE ID            CREATED             SIZE
nvidia/cuda                            9.0-base                   74f5aea45cf6        6 weeks ago         134MB
paddlepaddle/paddle                    1.1.0-gpu-cuda8.0-cudnn7   b3cd25f64a2a        8 weeks ago         2.76GB
hub.baidubce.com/paddlepaddle/paddle   1.1.0-gpu-cuda8.0-cudnn7   b3cd25f64a2a        8 weeks ago         2.76GB
paddlepaddle/paddle                    1.1.0-gpu-cuda9.0-cudnn7   0df4fe3ecea3        8 weeks ago         2.89GB
hub.baidubce.com/paddlepaddle/paddle   1.1.0-gpu-cuda9.0-cudnn7   0df4fe3ecea3

The first image is successfully deleted by docker RMI 74f5aea45cf6 directly. However, the latter two images appear in pairs, and the direct docker RMI deletion fails. The error message is as follows:

Error response from daemon:
conflict: unable to delete b3cd25f64a2a (must be forced) - image 
is referenced in multiple repositories

Solution:

First, specify a name when docker RMI , instead of image ID , and then execute docker RMI - f image ID J

docker rmi paddlepaddle/paddle:1.1.0-gpu-cuda8.0-cudnn7
docker rmi -f b3cd25f64a2a