Hi Mark,

I run one random query out of four defined queries at a time.

   1. Getting the average of a field over some time period.
   2. Getting the max  of a field over some time period.
   3. Getting the min of a field over some time period.
   4. Getting a percentile of a field over some time period.

Note that one of this query runs only once a second.

Thanks
Malaka 

On Thursday, February 26, 2015 at 6:26:51 AM UTC+5:30, Mark Walkom wrote:
>
> What sort of queries are you running?
>
> On 25 February 2015 at 22:08, Malaka Gallage <[email protected] 
> <javascript:>> wrote:
>
>> Hi Mark,
>>
>> Yes I'm using bulk API for the tests. Usually OOM error happens when the 
>> cluster has around 30 million records. Is there anyway to tune the ES 
>> cluster to perform better?
>>
>> Thanks
>> Malaka
>>
>> On Wednesday, February 25, 2015 at 12:25:52 PM UTC+5:30, Mark Walkom 
>> wrote:
>>>
>>> If you are getting queue capacity rejections then you are over working 
>>> your cluster. Are you using the bulk API for your tests?
>>> How much data is in your cluster when you get OOM?
>>>
>>> On 25 February 2015 at 16:28, Malaka Gallage <[email protected]> wrote:
>>>
>>>> Hi all,
>>>>
>>>> I need some help here. I started a load test for Elasticsearch before 
>>>> using that in production environment. I have three EC2 instances that are 
>>>> configured in following manner which creates a Elasticsearch cluster.
>>>>
>>>> All three machines has the following same hardware configurations.
>>>>
>>>> 32GB RAM
>>>> 160GB SSD hard disk
>>>> 8 core CPU
>>>>
>>>> *Machine 01*
>>>> Elasticsearch server (16GB heap)
>>>> Elasticsearch Java client (Who generates a continues load and report to 
>>>> ES - 4GB heap)
>>>>
>>>>
>>>> *Machine 02*
>>>> Elasticsearch server (16GB heap)
>>>> Elasticsearch Java client (Who generates a continues load and report to 
>>>> ES - 4GB heap)
>>>>
>>>>
>>>> *Machine 03*
>>>> Elasticsearch server (16GB heap)
>>>> Elasticsearch Java client (Who queries from ES continuously - 1GB heap)
>>>>
>>>>
>>>> Note that the two clients together generates around 20K records per 
>>>> second and report them as bulks with average size of 25. The other client 
>>>> queries only one query per second. My document has the following format.
>>>>
>>>> {
>>>>             "_index": "my_index",
>>>>             "_type": "my_type",
>>>>             "_id": "7334236299916134105",
>>>>             "_score": 3.6111107,
>>>>             "_source": {
>>>>                "long_1": 96186289301793,
>>>>                "long_2": 7334236299916134000,
>>>>                "string_1": "random_string",
>>>>                "long_3": 96186289301793,
>>>>                "string_2": "random_string",
>>>>                "string_3": "random_string",
>>>>                "string_4": "random_string",
>>>>                "string_5": "random_string",
>>>>                "long_4": 5457314198948537000
>>>>           }
>>>> }
>>>>
>>>> The problem is, after few minutes, Elasticsearch reports errors in the 
>>>> logs like this.
>>>>
>>>> [2015-02-24 08:03:58,070][ERROR][marvel.agent.exporter    ] [Gateway] 
>>>> create failure (index:[.marvel-2015.02.24] type: [cluster_stats]): 
>>>> RemoteTransportException[[Marvel 
>>>> Girl][inet[/10.167.199.140:9300]][bulk/shard]]; 
>>>> nested: EsRejectedExecutionException[rejected execution (queue 
>>>> capacity 50) on org.elasticsearch.action.support.replication.
>>>> TransportShardReplicationOperationAction$AsyncShardOperationAction$1@
>>>> 76dbf01];
>>>>
>>>> [2015-02-25 04:23:36,459][ERROR][marvel.agent.exporter    ] [Wildside] 
>>>> create failure (index:[.marvel-2015.02.25] type: [index_stats]): 
>>>> UnavailableShardsException[[.marvel-2015.02.25][0] [2] shardIt, [0] 
>>>> active : Timeout waiting for [1m], request: org.elasticsearch.action.bulk.
>>>> BulkShardRequest@2e7693b7]
>>>>
>>>> Note that this error happens for different indices and different types.
>>>>
>>>> Again after few minutes, Elasticsearch clients get 
>>>> NoNodeAvailableException. I hope that is because Elasticsearch cluster 
>>>> malfunctioning due to above errors. But eventually the clients get 
>>>> "java.lang.OutOfMemoryError: GC overhead limit exceeded" error.
>>>>
>>>> I did some profiling and found out that increasing 
>>>> the org.elasticsearch.action.index.IndexRequest instances is the cause 
>>>> for this OutOfMemory error. I tried even with "index.store.type: memory" 
>>>> and it seems still the Elasticsearch cluster cannot build the indices to 
>>>> the required rate.
>>>>
>>>> Please point out any tuning parameters or any method to get rid of 
>>>> these issues. Or please explain a different way to report and query this 
>>>> amount of load.
>>>>
>>>>
>>>> Thanks
>>>> Malaka
>>>>
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>>>>
>>>
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