I'm running Elastic and kibana on a clean linode instance with 8 GB RAM. Only imported a csv file through logstash into Elasticsearch in a index. Plain text fields with two Dates and some numeric ones. About the index, it has 2 shards, 425948 docs, size is: 283.7mb For learning how to use kibana,…

6.3, current one. Btw I see in a diagnosing tool (Cerebro) that my 2 shards are unallocated, is that problematic?

Your cluster is exposed to the internet, I guessed the IP from your image above. You might want to look at that first.

Thanks for that, it's already blocked :blush:

Ok cool. So my guess is that the visualisation you have created is generating too many buckets, and it's OOMing from that. What happens if you split the 4 metrics into their own visualisation, with the sub-buckets?

What sizes have you configured for your aggregations? Can you expand the view?

We had 50000 on size in the 4 buckets. Is that too much? I actually tried reducing it to 5, but it looks like however elasticsearch gc cannot finish cleaning the objects. [vzbqXTQ] [gc][old][1026][43] duration [18.4s], collections [2]/[18.4s], total [18.4s]/[5.9m], memory [3.9gb]->[3.9gb]/[3.9gb]…

That will generate 50000^4 buckets, which is quite a lot. What is the cardinality of those fields?

What is that mean? Btw here some details on the buckets: [image] [image]

java.lang.OutOfMemoryError: Java heap space - GC overhead using visualizations

Elastic Stack Elasticsearch

akapit (Alejandro Kapit) July 5, 2018, 9:08am 7

I disabled 3 of the 4 metrics this visualisation has, and it's still eating the whole heap.
IMO this is a kinda normal visualisation, it doesn't look like too much either.

Maybe something with the buckets can be wrong? It's too strange

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java.lang.OutOfMemoryError: Java heap space - GC overhead using visualizations

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