Re: Shard Allocation Problem

2015-04-01 Thread Marcelo Paes Rech
The ElasticSearch Team closed the issue, but I didn't have an answer. I 
still looking for a solution.


Regards.

Em sábado, 28 de março de 2015 16:29:05 UTC-3, Marcelo Paes Rech escreveu:

 Hi guys,

 Our cluster has 7 data nodes. Last week one of them was turned off. We 
 restarted the node and then the cluster started rebalancing. The problem is 
 it never finishes rebalancing.

 Node logs shows an update coming from master node during the rebalancing, 
 seconds later the rebalancing is canceled and then it starts again.

 I have created #10281 
 https://github.com/elastic/elasticsearch/issues/10281 on GitHub, but I 
 am including the problem here too. Maybe somebody ran into this problem and 
 already fixed it.

 The logs were collected in different moments but they represent the same 
 behaviour.

 The log follows:

 Data Node

 https://gist.github.com/marcelopaesrech/7b9f94310ff7a24bed9e

 Master Node

 https://gist.github.com/marcelopaesrech/c80542a85c83d9c1756d


 Regards.


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Re: Shard Allocation Problem

2015-03-28 Thread Marcelo Paes Rech
I will create a new post for that.

Em sábado, 28 de março de 2015 02:47:44 UTC-3, Mark Walkom escreveu:

 Please don't put such large logs directly into emails like this, use 
 gist/pastebin/etc :)

 If you can do that someone might be able to read things a little easier 
 and provide assistance.

 On 28 March 2015 at 04:27, Marcelo Paes Rech marcelo...@gmail.com 
 javascript: wrote:

 Hi guys,

 Our cluster has 7 data nodes. Last week one of them was turned off. We 
 restarted the node and then the cluster started rebalancing. The problem is 
 it nerver finishes rebalancing.

 Node logs shows an update coming from master node during the rebalancing, 
 seconds later the rebalancing is canceled and then it starts again.

 I have created #10281 
 https://github.com/elastic/elasticsearch/issues/10281 on GitHub, but I 
 am including the problem here too. Maybe somebody ran into this problem and 
 already fixed it.

 The logs were collected in different moments but they represent the same 
 behaviour.

 The log follows:

 Data Node:

 [2015-03-24 15:26:05,244][DEBUG][indices.cluster  ] [THE_CHOSEN_ONE] 
 [my_index][0] creating shard
 [2015-03-24 15:26:05,244][DEBUG][index.service] [THE_CHOSEN_ONE] 
 [my_index] creating shard_id [0]
 [2015-03-24 15:26:05,274][DEBUG][index.deletionpolicy ] [THE_CHOSEN_ONE] 
 [my_index][0] Using [keep_only_last] deletion policy
 [2015-03-24 15:26:05,275][DEBUG][index.merge.policy   ] [THE_CHOSEN_ONE] 
 [my_index][0] using [tiered] merge policy with expunge_deletes_allowed[10.0], 
 floor_segment[2mb], max_merge_at_once[10], max_merge_at_once_explicit[30], 
 max_merged_segment[5gb], segments_per_tier[10.0], reclaim_deletes_weight[2.0]
 [2015-03-24 15:26:05,276][DEBUG][index.merge.scheduler] [THE_CHOSEN_ONE] 
 [my_index][0] using [concurrent] merge scheduler with max_thread_count[3]
 [2015-03-24 15:26:05,278][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
 [my_index][0] state: [CREATED]
 [2015-03-24 15:26:05,278][DEBUG][index.translog   ] [THE_CHOSEN_ONE] 
 [my_index][0] interval [5s], flush_threshold_ops [5000], flush_threshold_size 
 [200mb], flush_threshold_period [30m]
 [2015-03-24 15:26:05,280][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
 [my_index][0] state: [CREATED]-[RECOVERING], reason [from 
 [VEROIA][Fto2cgJ-RB-IjV3EfLm1Sw][es2.mydomain][inet[/172.31.234.165:9300]]{master=false}]
 [2015-03-24 15:26:05,281][DEBUG][indices.cluster  ] [THE_CHOSEN_ONE] 
 [my_index][2] creating shard
 [2015-03-24 15:26:05,281][DEBUG][index.service] [THE_CHOSEN_ONE] 
 [my_index] creating shard_id [2]
 [2015-03-24 15:26:05,358][DEBUG][index.deletionpolicy ] [THE_CHOSEN_ONE] 
 [my_index][2] Using [keep_only_last] deletion policy
 [2015-03-24 15:26:05,361][DEBUG][index.merge.policy   ] [THE_CHOSEN_ONE] 
 [my_index][2] using [tiered] merge policy with expunge_deletes_allowed[10.0], 
 floor_segment[2mb], max_merge_at_once[10], max_merge_at_once_explicit[30], 
 max_merged_segment[5gb], segments_per_tier[10.0], reclaim_deletes_weight[2.0]
 [2015-03-24 15:26:05,363][DEBUG][index.merge.scheduler] [THE_CHOSEN_ONE] 
 [my_index][2] using [concurrent] merge scheduler with max_thread_count[3]
 [2015-03-24 15:26:05,371][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
 [my_index][2] state: [CREATED]
 [2015-03-24 15:26:05,373][DEBUG][index.translog   ] [THE_CHOSEN_ONE] 
 [my_index][2] interval [5s], flush_threshold_ops [5000], flush_threshold_size 
 [200mb], flush_threshold_period [30m]
 [2015-03-24 15:26:05,378][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
 [my_index][2] state: [CREATED]-[RECOVERING], reason [from 
 [PERAIA][bOUh4S-fSmW8vcD8Gw0sQw][es4.mydomain][inet[/172.31.234.167:9300]]{master=false}]
 [2015-03-24 15:26:05,380][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
 processing [zen-disco-receive(from master 
 [[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
  master=true}])]: done applying updated cluster_state (version: 116348)
 [2015-03-24 15:26:05,682][DEBUG][discovery.zen.publish] [THE_CHOSEN_ONE] 
 received cluster state version 116349
 [2015-03-24 15:26:05,684][DEBUG][discovery.zen] [THE_CHOSEN_ONE] 
 received cluster state from 
 [[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
  master=true}] which is also master but with cluster name [Cluster [gvtmusic]]
 [2015-03-24 15:26:05,685][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
 processing [zen-disco-receive(from master 
 [[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
  master=true}])]: execute
 [2015-03-24 15:26:05,685][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
 cluster state updated, version [116349], source [zen-disco-receive(from 
 master 
 [[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
  master=true}])]
 [2015-03-24 15:26:05,686][DEBUG

Shard Allocation Problem

2015-03-28 Thread Marcelo Paes Rech


Hi guys,

Our cluster has 7 data nodes. Last week one of them was turned off. We 
restarted the node and then the cluster started rebalancing. The problem is 
it never finishes rebalancing.

Node logs shows an update coming from master node during the rebalancing, 
seconds later the rebalancing is canceled and then it starts again.

I have created #10281 
https://github.com/elastic/elasticsearch/issues/10281 on GitHub, but I am 
including the problem here too. Maybe somebody ran into this problem and 
already fixed it.

The logs were collected in different moments but they represent the same 
behaviour.

The log follows:

Data Node

https://gist.github.com/marcelopaesrech/7b9f94310ff7a24bed9e

Master Node

https://gist.github.com/marcelopaesrech/c80542a85c83d9c1756d


Regards.

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Shard Allocation Problem

2015-03-27 Thread Marcelo Paes Rech


Hi guys,

Our cluster has 7 data nodes. Last week one of them was turned off. We 
restarted the node and then the cluster started rebalancing. The problem is 
it nerver finishes rebalancing.

Node logs shows an update coming from master node during the rebalancing, 
seconds later the rebalancing is canceled and then it starts again.

I have created #10281 
https://github.com/elastic/elasticsearch/issues/10281 on GitHub, but I am 
including the problem here too. Maybe somebody ran into this problem and 
already fixed it.

The logs were collected in different moments but they represent the same 
behaviour.

The log follows:

Data Node:

[2015-03-24 15:26:05,244][DEBUG][indices.cluster  ] [THE_CHOSEN_ONE] 
[my_index][0] creating shard
[2015-03-24 15:26:05,244][DEBUG][index.service] [THE_CHOSEN_ONE] 
[my_index] creating shard_id [0]
[2015-03-24 15:26:05,274][DEBUG][index.deletionpolicy ] [THE_CHOSEN_ONE] 
[my_index][0] Using [keep_only_last] deletion policy
[2015-03-24 15:26:05,275][DEBUG][index.merge.policy   ] [THE_CHOSEN_ONE] 
[my_index][0] using [tiered] merge policy with expunge_deletes_allowed[10.0], 
floor_segment[2mb], max_merge_at_once[10], max_merge_at_once_explicit[30], 
max_merged_segment[5gb], segments_per_tier[10.0], reclaim_deletes_weight[2.0]
[2015-03-24 15:26:05,276][DEBUG][index.merge.scheduler] [THE_CHOSEN_ONE] 
[my_index][0] using [concurrent] merge scheduler with max_thread_count[3]
[2015-03-24 15:26:05,278][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
[my_index][0] state: [CREATED]
[2015-03-24 15:26:05,278][DEBUG][index.translog   ] [THE_CHOSEN_ONE] 
[my_index][0] interval [5s], flush_threshold_ops [5000], flush_threshold_size 
[200mb], flush_threshold_period [30m]
[2015-03-24 15:26:05,280][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
[my_index][0] state: [CREATED]-[RECOVERING], reason [from 
[VEROIA][Fto2cgJ-RB-IjV3EfLm1Sw][es2.mydomain][inet[/172.31.234.165:9300]]{master=false}]
[2015-03-24 15:26:05,281][DEBUG][indices.cluster  ] [THE_CHOSEN_ONE] 
[my_index][2] creating shard
[2015-03-24 15:26:05,281][DEBUG][index.service] [THE_CHOSEN_ONE] 
[my_index] creating shard_id [2]
[2015-03-24 15:26:05,358][DEBUG][index.deletionpolicy ] [THE_CHOSEN_ONE] 
[my_index][2] Using [keep_only_last] deletion policy
[2015-03-24 15:26:05,361][DEBUG][index.merge.policy   ] [THE_CHOSEN_ONE] 
[my_index][2] using [tiered] merge policy with expunge_deletes_allowed[10.0], 
floor_segment[2mb], max_merge_at_once[10], max_merge_at_once_explicit[30], 
max_merged_segment[5gb], segments_per_tier[10.0], reclaim_deletes_weight[2.0]
[2015-03-24 15:26:05,363][DEBUG][index.merge.scheduler] [THE_CHOSEN_ONE] 
[my_index][2] using [concurrent] merge scheduler with max_thread_count[3]
[2015-03-24 15:26:05,371][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
[my_index][2] state: [CREATED]
[2015-03-24 15:26:05,373][DEBUG][index.translog   ] [THE_CHOSEN_ONE] 
[my_index][2] interval [5s], flush_threshold_ops [5000], flush_threshold_size 
[200mb], flush_threshold_period [30m]
[2015-03-24 15:26:05,378][DEBUG][index.shard.service  ] [THE_CHOSEN_ONE] 
[my_index][2] state: [CREATED]-[RECOVERING], reason [from 
[PERAIA][bOUh4S-fSmW8vcD8Gw0sQw][es4.mydomain][inet[/172.31.234.167:9300]]{master=false}]
[2015-03-24 15:26:05,380][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
processing [zen-disco-receive(from master 
[[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
 master=true}])]: done applying updated cluster_state (version: 116348)
[2015-03-24 15:26:05,682][DEBUG][discovery.zen.publish] [THE_CHOSEN_ONE] 
received cluster state version 116349
[2015-03-24 15:26:05,684][DEBUG][discovery.zen] [THE_CHOSEN_ONE] 
received cluster state from 
[[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
 master=true}] which is also master but with cluster name [Cluster [gvtmusic]]
[2015-03-24 15:26:05,685][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
processing [zen-disco-receive(from master 
[[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
 master=true}])]: execute
[2015-03-24 15:26:05,685][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
cluster state updated, version [116349], source [zen-disco-receive(from master 
[[MR3][4LssjGYPTX6EL7Kv-ylgMQ][master3.mydomain][inet[/172.31.234.181:9300]]{data=false,
 master=true}])]
[2015-03-24 15:26:05,686][DEBUG][cluster.service  ] [THE_CHOSEN_ONE] 
set local cluster state to version 116349
[2015-03-24 15:26:05,687][DEBUG][indices.cluster  ] [THE_CHOSEN_ONE] 
[my_index][0] removing shard (different instance of it allocated on this node, 
current [[my_index][0], node[OI3VgsmPSBekiVF7WhSm4Q], relocating 
[gBhKyL1gQ1WnHLUFvR_BPQ], [R], s[INITIALIZING]], global [[my_index][0], 
node[OI3VgsmPSBekiVF7WhSm4Q], [R], s[INITIALIZING]])
[2015-03-24 

No Node Available

2014-06-13 Thread Marcelo Paes Rech
Hi guys,

I googled about NoNodeAvailableException, but none answers for my questions 
until now. I'm getting this error when the ES connections between Server 
and Client are idle during a long time. I saw the number of connections in 
9300 port and there is a huge opened sockets number (something like 700 
connections). But if I count every client connection the number should be 
32.

Every morning I get this Exception once, and then everything works fine, 
without Exceptions anymore.

My client configurations follow:
client.transport.sniff: false
client.transport.ping_timeout: 30s
client.transport.nodes_sampler_interval: 5s

Regards.

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Re: Best cluster environment for search

2014-06-11 Thread Marcelo Paes Rech
I have just created a issue:

https://github.com/elasticsearch/elasticsearch/issues/6463

Regards.

Em quinta-feira, 5 de junho de 2014 20h02min05s UTC-3, Mark Walkom escreveu:

 This would probably be worth raising as a github issue - 
 https://github.com/elasticsearch/

 Regards,
 Mark Walkom

 Infrastructure Engineer
 Campaign Monitor
 email: ma...@campaignmonitor.com javascript:
 web: www.campaignmonitor.com
  

 On 5 June 2014 22:38, Marcelo Paes Rech marcelo...@gmail.com 
 javascript: wrote:

 Hi Jörg. Thanks for your reply again.

 As I said, I already had used ids filter, but I got the same behaviour. 

 I realized what was wrong. Maybe it could be a bug in ES or not. When I 
 executed the filter I included from and size attibutes. In this case 
 size was 99, but the final result would be just 10 documents. 
 Aparently ES pre-allocates the objects that I say I will use (maybe for 
 performance reasons), but if the final result is not the total (99), ES 
 doesn't remove remaining pre-allocated objects until the memory (heap) is 
 full.

 I changed the size attribute to 10 and heap became stable.


 That's it. Thanks.

 Regards.

 Em quarta-feira, 4 de junho de 2014 19h54min15s UTC-3, Jörg Prante 
 escreveu:

 Why do you use terms on _id field and not the the ids filter? ids filter 
 is more efficient since it reuses the _uid field which is cached by default.

 Do the terms in the query vary from query to query? If so, caching might 
 kill your heap. 

 Another possible issue is that your query is not distributed to all 
 shards, if the query does not vary from user to user in your test. If so, 
 you created a hot spot, all the load from the 100 users wold go to a 
 limited number of node with a limited shard count. 

 The search thread pool seems small with 50 searches if you execute 
 searches for 100 users in parallel, this can lead to a congestion of the 
 search module. Why don't you use 100 (at least)?

 Jörg


 On Wed, Jun 4, 2014 at 2:40 PM, Marcelo Paes Rech marcelo...@gmail.com 
 wrote:

 Hi Jörg. Thanks for your reply.

 Here is my filter.
 {filter:
 {
   terms : {
 _id : [ QSxrbEM8TKe5zr8931xBjA, wj63ghegRwC6qLsWq2chkA, 
 hYEhDbAqQwSRxhYfvDgFkg, 4bZmPE1fTYqijphRyyWiuQ, 
 Fhq53yYyT3CEw6vclKu_NA, XL2atBraTEyx57MefjFVhA, 
 951i0dZkT064FlQkzHnnWA, O8Ixbir1TrGT_IA3wKfsHg, 
 8k4U7KsuTmsThqxy-5YaKw, GNOoQTHglf22kzcE7EOf8g, 
 -RQeY48fTg2kYnh2M4E1cQ, u8DGBdfVR9WRVj6d9E4Ebw, 
 WFHSXd7UQvCMYFBhFcTsng, qnQ7q7FyTsg397lM1EWgqA, 
 wRQtUzdMRy2qOkMCNxdpgA, Ll83iglxSUS_Gs7mjkMt8w, 
 d2sxZ1oBTfuvAfov5EJ0iw, cyht-vB4Q-mMSg9N5jcGXg, 
 bNSVaO47QTOCkfJhWo0qjg, BHuhm55IRerKnynJ8WgFTw, 
 fHKA4PF2QteWm8E7dW7CAw, DLE6A7tyQJ-zcKcCa6IPSA, 
 qfelTW7-SuGRQ0GKbngARA, R7VHHJhYsUqfuxYof8BJ8w, 
 W4PqiJfPSlSFjVKFsGkA4Q, Juq62zOsRdheuW3O6Gb2KA, 
 U9v0IKj_RrgRNjE31ZTt2g, uNHa0kOOT5qjPpzxZcs35A, 
 SwOgVNgIRwyVU3pEEycBuQ, LaEpxFGIQgCArsNZ2rd4Pw, 
 CiJ9gouZsbmTtxTWx7w6lA, TaQV_I01RfCq3B6uAtIBoQ, 
 9Jpjo5k-RlGfLVLF6nDgze, 57YpjRdASsrrae-RD3spog, 
 bmA4EWFSTiKUaDzaNcCFKQ, Fui9z_UbRe6AY1VhAr8Crw, 
 2PORr5BzSDOmBXgmQkO5Zg, snfwTmtuTv-uj5mOWSJpgA, 
 0nHIrtePSaeW8aWArh_Mrg, s0g9QHnjTgWX3rCIu1g0Hg, 
 Jl67fACuQvCFgZxXAFtDOg ],
 _cache : true,
 _cache_key : my_terms_cache
   }
 }
 }

 I already used *ids filter* but I got same behaviour. One thing that 
 I realized is that one of the cluster's nodes is increasing the Search 
 Thread Pool (something like Queue: 50 and Count: 47) and the others don't 
 (something like Queue: 0 and Count: 1). If I remove this node from the 
 cluster another one starts with the same problem.

 My current environment is:
 - 7 Data nodes with 16Gb (8Gb for ES)and 8 cores each one;
 - 4 Load balancer Nodes (no data, no master)  with 4Gb (3Gb for ES) and 
 8 cores each one;
 - 4 MasterNodes (only master, no data)  with 4Gb (3Gb for ES) and 8 
 cores each one;
 - Thread Pool Search 47 (the others are standard config);
 - 7 Shards and 2 replicas Index;
 - 14.6Gb Index size (14.524.273 documents);


 I'm executing this filter with 50 concurrent users.


 Regards

 Em terça-feira, 3 de junho de 2014 20h33min45s UTC-3, Jörg Prante 
 escreveu:

 Can you show your test code?

 You seem to look at the wrong settings - by adjusting node number, 
 shard number, replica number alone, you can not find out the maximum node 
 performance. E.g. concurrency settings, index optimizations, query 
 optimizations, thread pooling, and most of all, fast disk subsystem I/O 
 is 
 important.

 Jörg


 On Wed, Jun 4, 2014 at 12:18 AM, Marcelo Paes Rech 
 marcelo...@gmail.com wrote:

 Thanks for your reply Nikolas. It helps a lot.

 And about the quantity of documents of each shard, or size of each 
 shard. And the need of no data nodes or only master nodes. When is it 
 necessary?

 Some tests I did, when I increased request's number (like 100 users 
 at same moment, and redo it again and again), 5 nodes with 1 shard and 2 
 replicas each and 16Gb RAM (8Gb for ES and 8Gb for OS) weren't enough. 
 The 
 response time

Re: Best cluster environment for search

2014-06-05 Thread Marcelo Paes Rech
Hi Jörg. Thanks for your reply again.

As I said, I already had used ids filter, but I got the same behaviour. 

I realized what was wrong. Maybe it could be a bug in ES or not. When I 
executed the filter I included from and size attibutes. In this case 
size was 99, but the final result would be just 10 documents. 
Aparently ES pre-allocates the objects that I say I will use (maybe for 
performance reasons), but if the final result is not the total (99), ES 
doesn't remove remaining pre-allocated objects until the memory (heap) is 
full.

I changed the size attribute to 10 and heap became stable.


That's it. Thanks.

Regards.

Em quarta-feira, 4 de junho de 2014 19h54min15s UTC-3, Jörg Prante escreveu:

 Why do you use terms on _id field and not the the ids filter? ids filter 
 is more efficient since it reuses the _uid field which is cached by default.

 Do the terms in the query vary from query to query? If so, caching might 
 kill your heap. 

 Another possible issue is that your query is not distributed to all 
 shards, if the query does not vary from user to user in your test. If so, 
 you created a hot spot, all the load from the 100 users wold go to a 
 limited number of node with a limited shard count. 

 The search thread pool seems small with 50 searches if you execute 
 searches for 100 users in parallel, this can lead to a congestion of the 
 search module. Why don't you use 100 (at least)?

 Jörg


 On Wed, Jun 4, 2014 at 2:40 PM, Marcelo Paes Rech marcelo...@gmail.com 
 javascript: wrote:

 Hi Jörg. Thanks for your reply.

 Here is my filter.
 {filter:
 {
   terms : {
 _id : [ QSxrbEM8TKe5zr8931xBjA, wj63ghegRwC6qLsWq2chkA, 
 hYEhDbAqQwSRxhYfvDgFkg, 4bZmPE1fTYqijphRyyWiuQ, 
 Fhq53yYyT3CEw6vclKu_NA, XL2atBraTEyx57MefjFVhA, 
 951i0dZkT064FlQkzHnnWA, O8Ixbir1TrGT_IA3wKfsHg, 
 8k4U7KsuTmsThqxy-5YaKw, GNOoQTHglf22kzcE7EOf8g, 
 -RQeY48fTg2kYnh2M4E1cQ, u8DGBdfVR9WRVj6d9E4Ebw, 
 WFHSXd7UQvCMYFBhFcTsng, qnQ7q7FyTsg397lM1EWgqA, 
 wRQtUzdMRy2qOkMCNxdpgA, Ll83iglxSUS_Gs7mjkMt8w, 
 d2sxZ1oBTfuvAfov5EJ0iw, cyht-vB4Q-mMSg9N5jcGXg, 
 bNSVaO47QTOCkfJhWo0qjg, BHuhm55IRerKnynJ8WgFTw, 
 fHKA4PF2QteWm8E7dW7CAw, DLE6A7tyQJ-zcKcCa6IPSA, 
 qfelTW7-SuGRQ0GKbngARA, R7VHHJhYsUqfuxYof8BJ8w, 
 W4PqiJfPSlSFjVKFsGkA4Q, Juq62zOsRdheuW3O6Gb2KA, 
 U9v0IKj_RrgRNjE31ZTt2g, uNHa0kOOT5qjPpzxZcs35A, 
 SwOgVNgIRwyVU3pEEycBuQ, LaEpxFGIQgCArsNZ2rd4Pw, 
 CiJ9gouZsbmTtxTWx7w6lA, TaQV_I01RfCq3B6uAtIBoQ, 
 9Jpjo5k-RlGfLVLF6nDgze, 57YpjRdASsrrae-RD3spog, 
 bmA4EWFSTiKUaDzaNcCFKQ, Fui9z_UbRe6AY1VhAr8Crw, 
 2PORr5BzSDOmBXgmQkO5Zg, snfwTmtuTv-uj5mOWSJpgA, 
 0nHIrtePSaeW8aWArh_Mrg, s0g9QHnjTgWX3rCIu1g0Hg, 
 Jl67fACuQvCFgZxXAFtDOg ],
 _cache : true,
 _cache_key : my_terms_cache
   }
 }
 }

 I already used *ids filter* but I got same behaviour. One thing that I 
 realized is that one of the cluster's nodes is increasing the Search Thread 
 Pool (something like Queue: 50 and Count: 47) and the others don't 
 (something like Queue: 0 and Count: 1). If I remove this node from the 
 cluster another one starts with the same problem.

 My current environment is:
 - 7 Data nodes with 16Gb (8Gb for ES)and 8 cores each one;
 - 4 Load balancer Nodes (no data, no master)  with 4Gb (3Gb for ES) and 8 
 cores each one;
 - 4 MasterNodes (only master, no data)  with 4Gb (3Gb for ES) and 8 cores 
 each one;
 - Thread Pool Search 47 (the others are standard config);
 - 7 Shards and 2 replicas Index;
 - 14.6Gb Index size (14.524.273 documents);


 I'm executing this filter with 50 concurrent users.


 Regards

 Em terça-feira, 3 de junho de 2014 20h33min45s UTC-3, Jörg Prante 
 escreveu:

 Can you show your test code?

 You seem to look at the wrong settings - by adjusting node number, shard 
 number, replica number alone, you can not find out the maximum node 
 performance. E.g. concurrency settings, index optimizations, query 
 optimizations, thread pooling, and most of all, fast disk subsystem I/O is 
 important.

 Jörg


 On Wed, Jun 4, 2014 at 12:18 AM, Marcelo Paes Rech marcelo...@gmail.com
  wrote:

 Thanks for your reply Nikolas. It helps a lot.

 And about the quantity of documents of each shard, or size of each 
 shard. And the need of no data nodes or only master nodes. When is it 
 necessary?

 Some tests I did, when I increased request's number (like 100 users at 
 same moment, and redo it again and again), 5 nodes with 1 shard and 2 
 replicas each and 16Gb RAM (8Gb for ES and 8Gb for OS) weren't enough. The 
 response time start to increase more than 5s (I think less than 1s,  in 
 this case, would be acceptable) .

 This test has a lot of documents (something like 14 millions).


 Thanks. Regards.

 Em segunda-feira, 2 de junho de 2014 17h09min04s UTC-3, Nikolas Everett 
 escreveu:




 On Mon, Jun 2, 2014 at 3:52 PM, Marcelo Paes Rech 
 marcelo...@gmail.com wrote:

 Hi guys,

 I'm looking for an article or a guide for the best cluster 
 configuration. I read a lot of articles like change this configuration 
 and you must

Re: Best cluster environment for search

2014-06-04 Thread Marcelo Paes Rech
Hi Jörg. Thanks for your reply.

Here is my filter.
{filter:
{
  terms : {
_id : [ QSxrbEM8TKe5zr8931xBjA, wj63ghegRwC6qLsWq2chkA, 
hYEhDbAqQwSRxhYfvDgFkg, 4bZmPE1fTYqijphRyyWiuQ, 
Fhq53yYyT3CEw6vclKu_NA, XL2atBraTEyx57MefjFVhA, 
951i0dZkT064FlQkzHnnWA, O8Ixbir1TrGT_IA3wKfsHg, 
8k4U7KsuTmsThqxy-5YaKw, GNOoQTHglf22kzcE7EOf8g, 
-RQeY48fTg2kYnh2M4E1cQ, u8DGBdfVR9WRVj6d9E4Ebw, 
WFHSXd7UQvCMYFBhFcTsng, qnQ7q7FyTsg397lM1EWgqA, 
wRQtUzdMRy2qOkMCNxdpgA, Ll83iglxSUS_Gs7mjkMt8w, 
d2sxZ1oBTfuvAfov5EJ0iw, cyht-vB4Q-mMSg9N5jcGXg, 
bNSVaO47QTOCkfJhWo0qjg, BHuhm55IRerKnynJ8WgFTw, 
fHKA4PF2QteWm8E7dW7CAw, DLE6A7tyQJ-zcKcCa6IPSA, 
qfelTW7-SuGRQ0GKbngARA, R7VHHJhYsUqfuxYof8BJ8w, 
W4PqiJfPSlSFjVKFsGkA4Q, Juq62zOsRdheuW3O6Gb2KA, 
U9v0IKj_RrgRNjE31ZTt2g, uNHa0kOOT5qjPpzxZcs35A, 
SwOgVNgIRwyVU3pEEycBuQ, LaEpxFGIQgCArsNZ2rd4Pw, 
CiJ9gouZsbmTtxTWx7w6lA, TaQV_I01RfCq3B6uAtIBoQ, 
9Jpjo5k-RlGfLVLF6nDgze, 57YpjRdASsrrae-RD3spog, 
bmA4EWFSTiKUaDzaNcCFKQ, Fui9z_UbRe6AY1VhAr8Crw, 
2PORr5BzSDOmBXgmQkO5Zg, snfwTmtuTv-uj5mOWSJpgA, 
0nHIrtePSaeW8aWArh_Mrg, s0g9QHnjTgWX3rCIu1g0Hg, 
Jl67fACuQvCFgZxXAFtDOg ],
_cache : true,
_cache_key : my_terms_cache
  }
}
}

I already used *ids filter* but I got same behaviour. One thing that I 
realized is that one of the cluster's nodes is increasing the Search Thread 
Pool (something like Queue: 50 and Count: 47) and the others don't 
(something like Queue: 0 and Count: 1). If I remove this node from the 
cluster another one starts with the same problem.

My current environment is:
- 7 Data nodes with 16Gb (8Gb for ES)and 8 cores each one;
- 4 Load balancer Nodes (no data, no master)  with 4Gb (3Gb for ES) and 8 
cores each one;
- 4 MasterNodes (only master, no data)  with 4Gb (3Gb for ES) and 8 cores 
each one;
- Thread Pool Search 47 (the others are standard config);
- 7 Shards and 2 replicas Index;
- 14.6Gb Index size (14.524.273 documents);


I'm executing this filter with 50 concurrent users.


Regards

Em terça-feira, 3 de junho de 2014 20h33min45s UTC-3, Jörg Prante escreveu:

 Can you show your test code?

 You seem to look at the wrong settings - by adjusting node number, shard 
 number, replica number alone, you can not find out the maximum node 
 performance. E.g. concurrency settings, index optimizations, query 
 optimizations, thread pooling, and most of all, fast disk subsystem I/O is 
 important.

 Jörg


 On Wed, Jun 4, 2014 at 12:18 AM, Marcelo Paes Rech marcelo...@gmail.com 
 javascript: wrote:

 Thanks for your reply Nikolas. It helps a lot.

 And about the quantity of documents of each shard, or size of each shard. 
 And the need of no data nodes or only master nodes. When is it necessary?

 Some tests I did, when I increased request's number (like 100 users at 
 same moment, and redo it again and again), 5 nodes with 1 shard and 2 
 replicas each and 16Gb RAM (8Gb for ES and 8Gb for OS) weren't enough. The 
 response time start to increase more than 5s (I think less than 1s,  in 
 this case, would be acceptable) .

 This test has a lot of documents (something like 14 millions).


 Thanks. Regards.

 Em segunda-feira, 2 de junho de 2014 17h09min04s UTC-3, Nikolas Everett 
 escreveu:




 On Mon, Jun 2, 2014 at 3:52 PM, Marcelo Paes Rech marcelo...@gmail.com 
 wrote:

 Hi guys,

 I'm looking for an article or a guide for the best cluster 
 configuration. I read a lot of articles like change this configuration 
 and you must create X shards per node but I didn't saw nothing like 
 ElasticSearch Official guide for creating a cluster.

 What I would like to know are informations like. 
 - How to calculate how many shards will be good for the cluster.
 - How many shards do we need per node? And if this is variable, how do 
 I calculate this?
 - How much memory do I need per node and how many nodes?

 I think ElasticSearch is well documentated. But it is very fragmented.



 For some of these that is because it depends is the answer.  For 
 example, you'll want larger heaps for aggregations and faceting.

 There are some rules of thumb:
 1.  Set Elasticsearch's heap memory to 1/2 of ram but not more then 
 30GB.  Bigger then that and the JVM can't do pointer compression and you 
 effectively lose ram.
 2.  #1 implies that having much more then 60GB of ram on each node 
 doesn't make a big difference.  It helps but its not really as good as 
 having more nodes.
 3.  The most efficient efficient way of sharding is likely one shard on 
 each node.  So if you have 9 nodes and a replication factor of 2 (so 3 
 total copies) then 3 shards is likely to be more efficient then having 2 or 
 4.  But this only really matters when those shards get lots of traffic.  
 And it breaks down a bit when you get lots of nodes.  And the in presence 
 of routing.  Its complicated.

 But these are really just starting points, safe-ish defaults.

 Nik

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 You received this message because you are subscribed to the Google Groups 
 elasticsearch group.
 To unsubscribe from this group and stop

Re: Best cluster environment for search

2014-06-03 Thread Marcelo Paes Rech
Thanks for your reply Nikolas. It helps a lot.

And about the quantity of documents of each shard, or size of each shard. 
And the need of no data nodes or only master nodes. When is it necessary?

Some tests I did, when I increased request's number (like 100 users at same 
moment, and redo it again and again), 5 nodes with 1 shard and 2 replicas 
each and 16Gb RAM (8Gb for ES and 8Gb for OS) weren't enough. The response 
time start to increase more than 5s (I think less than 1s,  in this case, 
would be acceptable) .

This test has a lot of documents (something like 14 millions).


Thanks. Regards.

Em segunda-feira, 2 de junho de 2014 17h09min04s UTC-3, Nikolas Everett 
escreveu:




 On Mon, Jun 2, 2014 at 3:52 PM, Marcelo Paes Rech marcelo...@gmail.com 
 javascript: wrote:

 Hi guys,

 I'm looking for an article or a guide for the best cluster configuration. 
 I read a lot of articles like change this configuration and you must 
 create X shards per node but I didn't saw nothing like ElasticSearch 
 Official guide for creating a cluster.

 What I would like to know are informations like. 
 - How to calculate how many shards will be good for the cluster.
 - How many shards do we need per node? And if this is variable, how do I 
 calculate this?
 - How much memory do I need per node and how many nodes?

 I think ElasticSearch is well documentated. But it is very fragmented.



 For some of these that is because it depends is the answer.  For 
 example, you'll want larger heaps for aggregations and faceting.

 There are some rules of thumb:
 1.  Set Elasticsearch's heap memory to 1/2 of ram but not more then 30GB.  
 Bigger then that and the JVM can't do pointer compression and you 
 effectively lose ram.
 2.  #1 implies that having much more then 60GB of ram on each node doesn't 
 make a big difference.  It helps but its not really as good as having more 
 nodes.
 3.  The most efficient efficient way of sharding is likely one shard on 
 each node.  So if you have 9 nodes and a replication factor of 2 (so 3 
 total copies) then 3 shards is likely to be more efficient then having 2 or 
 4.  But this only really matters when those shards get lots of traffic.  
 And it breaks down a bit when you get lots of nodes.  And the in presence 
 of routing.  Its complicated.

 But these are really just starting points, safe-ish defaults.

 Nik


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Best cluster environment for search

2014-06-02 Thread Marcelo Paes Rech
Hi guys,

I'm looking for an article or a guide for the best cluster configuration. I 
read a lot of articles like change this configuration and you must 
create X shards per node but I didn't saw nothing like ElasticSearch 
Official guide for creating a cluster.

What I would like to know are informations like. 
- How to calculate how many shards will be good for the cluster.
- How many shards do we need per node? And if this is variable, how do I 
calculate this?
- How much memory do I need per node and how many nodes?

I think ElasticSearch is well documentated. But it is very fragmented.



Best regards.

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You received this message because you are subscribed to the Google Groups 
elasticsearch group.
To unsubscribe from this group and stop receiving emails from it, send an email 
to elasticsearch+unsubscr...@googlegroups.com.
To view this discussion on the web visit 
https://groups.google.com/d/msgid/elasticsearch/b8894495-e64b-4796-9eb4-e49e1b9ce556%40googlegroups.com.
For more options, visit https://groups.google.com/d/optout.