We've played around with heap size and various settings to improve the 
indexing speed. Also setting up multiple nodes would likely help.

The instance currently being loaded at our site will have 800,000+ 
resources. It seems to be running fine performance wise with 4Gb heap, 1 
node and 189k resource that are in there already BUT we don't have many 
people using it concurrently at this stage.

Once the data loading is completed we will be looking at configuring 
additional nodes.




On Wednesday, September 4, 2019 at 12:18:34 AM UTC+1, Martha S wrote:
>
> Hi, All,
>
> Our new Arches installation is on a clean Ubuntu 18.04 server, so we are 
> currently working with default settings for everything. We've got a 
> relatively large database of more than 110,000 items with complex 
> interrelations. Our ElasticSearch data is currently at 6.7 GB. Search and 
> load time is unacceptably slow and I'd like to hear about what others have 
> tried and achieved the most with. 
>
> 1. We have 28 GB of memory on this server, most of which is going unused. 
> It seems my first step should be to increase the ElasticSearch heap and 
> allocate it at boot. Has anyone had experience with this?
>
> 2. We have mounted two solid state drives, but both the ElasticSearch data 
> and the Postgres database are currently on the OS partition. Has anyone 
> found that moving one or both helped?
>
> 3. The server has four cores. Would upping this make a difference? 
>
> 4. Have you done something else that sped up your system response time?
>
> Thanks in advance,
> Martha
>

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