For my thesis I am going to test the scalability/performance of the
Elasticsearch cluster depending on the number of nodes.
I have a physical server (with 8 cores, 30 GB memory) and on that physical
server I create* 4 virtual machines*, each assigned with 2 cores and 4GB of
On each virtual machine I install Elasticsearch, therefore each machine
represents a separate node in my Elasticsearch cluster.
The data contains* about 7 million documents*, I have* 5 shards and
replication_count=1 (default configuration)*.
I am executing a set of tests on the cluster with different
cluster-configurations. At first I assign only 1 node to the cluster and
execute the tests, then I assign 2 nodes to the cluster and execute the
same tests again, then 3 nodes etc.
The tests do not contain any fancy features (no facets, highlighting, etc),
but only filters and queries.
I expected that for each additional node in the cluster I would get a
linear improvement of the query response time. Because each node contains a
bit of the data (shard) and so the query could be executed on each shard at
the same time.
But it turns out that the response time of the query is not improving nor
is it getting worse, it almost stays the same....
So my question:
Are these results expected, that the query response time does NOT improve
when adding an additional node?
I execute the test queries one after another and not in parallel. Is
Elasticsearch made just to handle a high load of requests, but not for
improving the query time of a single request when I add additional nodes to
I mean, would I see only an improvement for each additional node, when I
would run the tests in parallel, because then the query load is
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