Be aware that we do not yet officially support G1GC. You should also reduce
your heap to 31GB.

Ideally you want to keep shard size below 50GB, so you will need to adjust
things as you grow. Be careful creating a lot of indices though, each one
takes overhead and if you increase the number of indices and the amount of
data you have in them you could be wasting resources.

However when querying, 100 indices with 1 shard is the same as 1 index with
100 shards.

On 28 January 2015 at 10:11, Chris Neal <[email protected]> wrote:

> Hi all,
>
> I've seen lots of posts about this, and want to make sure I'm
> understanding correctly.
>
> Background:
>
>    - Our cluster has 6 servers.  They are Dell R720xd with 64GB RAM,
>    2xE5-2600v2 CPU (2 sockets, 6 cores/socket), 16TB disk
>    - Elasticsearch is set to have 6 shards, and 1 replica, giving two
>    shards per server.  I'm giving ES 32GB heaps on Java 1.7 with G1 GC.
>
>
> I'm concerned about the size of our indexes.  Right now, we store all data
> in one index per day, with various types within that to separate data.
>
> The indexes are averaging about 50GB/day (not including replicas).  Shard
> size is 8GB each.
>
> We have a LOT more data to index.  At least 20x more.  Should I be
> concerned with indexes of that size (~1000GB) and shards of that size
> (~160GB)?  Is it merely a question of having enough hardware, or is there
> more to it?
>
> I'm considering splitting the data into a different indexing strategy so
> that the index size is smaller, but there are more of them.  The result is
> the amount of data is the same, so I'm not sure if that will do anything or
> not.
>
> If I'm optimizing for searching, does querying multiple smaller indices
> perform better than querying fewer larger ones?
>
> Thank you for your time.
> Chris
>
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