I am using 14 trial account of elastic search. This account showing me I have a 4.6GB heap size. I want to reduce my heap size to 2GB so how I can reduce this. I have checked the way of changing the heap size using the following options:
export ES_HEAP_SIZE=2g or
ES_JAVA_OPTS="-Xms2g -Xmx2g" ./bin/elasticsearch
But How I can reduce the heap size using one of the above option in the elastic cloud?
Since Elastic Cloud is a managed service, end users do not have access to the backend master and data nodes in the cluster. Unfortunately, you cannot change the heap size setting of an Elastic Cloud Elasticsearch cluster. You can however scale down your cluster so that the heap memory allocated also reduces. Alternatively, you could try emailing Elastic support at support#elastic.co and ask if they can change the heap size for you but I highly doubt that level of customization is offered for Elastic Cloud service.
Related
Out of memory*
Elastic search service frequently going down.
It consuming more resource and running out of memory.
Issue with heap memory for elastic search.
Update below value:
Go to /installer/templates/elasticsearch/start.sh.template
Increase HEAP_MB value
I am trying to calculate good balance of total memory in three node es cluster.
If I have three node e.s cluster each with 32G memory, 8 vcpu. Which combination would be more suitable for balancing memory between all the components? I know there will be no fixed answers but just trying to get as accurate as I can.
different elasticsearch components will be used are beats (filebeat, metricbeat,heartbeat), logstash, elasticsearch, kibana.
most use case for this cluster will be, application logs getting indexed and running query on them like fetch average response time for 7 days,30 days, how many are different status codes for last 24 hrs, 7 days etc through curl calls, so aggregation will be used and other use case is monitoring, seeing logs through kibana but no ML jobs or dashboard creation etc..
After going through below official docs, its recommended to set heap size as below,
logstash -
https://www.elastic.co/guide/en/logstash/current/jvm-settings.html#heap-size
The recommended heap size for typical ingestion scenarios should be no less than 4GB and no more than 8GB.
elasticsearch -
https://www.elastic.co/guide/en/elasticsearch/reference/current/advanced-configuration.html#set-jvm-heap-size
Set Xms and Xmx to no more than 50% of your total memory. Elasticsearch requires memory for purposes other than the JVM heap
Kibana -
I have't found default or recommended memory for kibana but in our test cluster of single node of 8G memory it is taking 1.4G as total (256 MB/1.4 GB)
beats -
not found what is the default or recommended memory for beats but they will also consume more or less.
What should the ideal combination from below?
32G = 16G for OS + 16G for Elasticsearch heap.
for logstash 4G from 16G of OS, say three beats will consume 4G, kibana 2G
this leaves OS with 6G and if any new component has to be install in future like say APM or any other OS related then they all will have only 6G with OS.
Above is, per offical recommendation for all components. (i.e 50% for OS and 50% for es)
32G = 8G for elasticsearch heap. (25% for elasticsearch)
4G for logstash + beats 4G + kibana 2G
this leaves 14G for OS and for any future component.
I am missing to cover something that can change this memory combination?
Any suggestion by changing in above combination or any new combination is appreciated.
Thanks,
Deployed elastic search Kubernetes in GKE. With 2GB memory and 1GB persistence disk.
We got an error out of storage exception. After that, we have Increased to 2GB on the next day itself it reached 2GB, but we haven’t run any big queries. Then again we have increased the persistence disk size to 10 GB. After that, there is no increase in the data persistence disk storage.
On further analysis, we have found total Indices take 20MB of memory unable to what are the data in the disk.
Used elastic search nodes stats API to get the details on disk and node statistics.
I am unable to find the exact reason why memory exceeds and what are the data in the disk. Also, suggest ways to prevent this future.
It is continuously receiving data and based on your config it creates multiple copies of indices and may create a new index daily. Check the config file.
if the elasticsearch cluster fails each time it creates a backup of data so you may need to delete old backups before restarting the cluster.
I would like to change my AWS Elasticsearch thread_pool.write.queue_size setting. I see that the recommended technique is to update the elasticsearch.yml file as it can't be done dynamically by the API in the newer versions.
However, since I am using AWS's Elasticsearch service, as far as I'm aware, I don't have access to that file. Is there anyway to make this change? I don't see it referenced for version 6.3 here so I don't know how to do it with AWS.
You do not have a lot of flexibility with AWS ES. In your case, scale your data node instance type to a bigger instance and that should provide you higher thread pool queue size. A note on increasing the number of shards - do not do it unless really required as it may cause performance issues while searching, aggregating etc. A shard can easily hold upto 50 GB of data, so if you have a lot of shards with very less data then think about shrinking the shards. Each shard in itself consumes resources (cpu, memory) etc and shard configuration should be proportional to the heap memory available on the node.
My elasticsearch service is consuming around 1 gb.
My total memory is 2gb. The elasticsearch service keeps getting shut down. I guess the reason is because of the high memory consumption. How can i limit the usage to just 512 MB?
This is the memory before starting elastic search
After running sudo service elasticsearch start the memory consumption jumps
I appreciate any help! Thanks!
From the official doc
The default installation of Elasticsearch is configured with a 1 GB heap. For just about every deployment, this number is usually too small. If you are using the default heap values, your cluster is probably configured incorrectly.
So you can change it like this
There are two ways to change the heap size in Elasticsearch. The easiest is to set an environment variable called ES_HEAP_SIZE. When the server process starts, it will read this environment variable and set the heap accordingly. As an example, you can set it via the command line as follows: export ES_HEAP_SIZE=512m
But it's not recommended. You just can't run an Elasticsearch in the optimal way with so few RAM available.