Hi I downloaded the latest ES 1.1.1
I have a 200GB RAM with 2 x 8 cores hyper threaded. "32" cores total
machine 1.6T of disk space.
I start elastic search as follows...
./elasticsearch -Xms100g -Xmx100g -Des.index.store.type=memory
Using Java 1.7_51
I then create my index as follows...
$ curl -XPUT http://localhost:9200/myindex/ -d
'
index :
store:
type: memory
'
And my Java web app (Using vertx.io)
// On app startup... Ensure we have one instance of client. Regardless how
many app threads may write to the index.
synchronized(clientCreated) {
if(clientCreated.compareAndSet(false, true)) {
node = nodeBuilder().clusterName("elasticsearch").client(true).node();
client = node.client();
}
}
// Per request coming into my web application. Using vertx for the web
framework.
// For each request we use the one client instance.
client.prepareIndex("myindex", "doc", request.getString("id"))
.setSource(bodyStr) // Already sending Json so no need to convert
it!
.execute(new ActionListener(){
@Override
public void onFailure(Throwable t) {
req.response().end("Error: " + t.toString());
}
@Override
public void onResponse(IndexResponse res) {
req.response().end(res.getIndex());
}});
Both the webapp and ES running on same server. So all write/read requests
are localhost.
Testing as follows
JMeter (100 users, running on my desktop) ------ Remote ----> WebApp -----
localhost ----> ES
I get about 6000 writes/sec and it seems to get lower as the number of docs
that get indexed increases.
Average request/response latency is about 15-20ms.
Network Time/Jmeter data generation( Each document is about 1000 bytes)/web
app is about 5 ms. I know this because I also have a simple hello world
response to test the average latency of those 3 "parameters".
So it seems that in-memory takes average 15ms I would think ES can do much
better then that?
Is there any tuning settings I can try for strictly in-memory index?
Thanks
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