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Copy file name to clipboardExpand all lines: .github/PULL_REQUEST_TEMPLATE.md
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@@ -10,5 +10,5 @@ attention.
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- Have you followed the [contributor guidelines](https://github.com/elastic/elasticsearch/blob/master/CONTRIBUTING.md)?
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- If submitting code, have you built your formula locally prior to submission with `gradle check`?
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- If submitting code, is your pull request against master? Unless there is a good reason otherwise, we prefer pull requests against master and will backport as needed.
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- If submitting code, have you checked that your submission is for an [OS that we support](https://www.elastic.co/support/matrix#show_os)?
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- If submitting code, have you checked that your submission is for an [OS and architecture that we support](https://www.elastic.co/support/matrix#show_os)?
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- If you are submitting this code for a class then read our [policy](https://github.com/elastic/elasticsearch/blob/master/CONTRIBUTING.md#contributing-as-part-of-a-class) for that.
The above will index information into the @kimchy@ index. Each user will get their own special index.
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Complete control on the index level is allowed. As an example, in the above case, we would want to change from the default 5 shards with 1 replica per index, to only 1 shard with 1 replica per index (== per twitter user). Here is how this can be done (the configuration can be in yaml as well):
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Complete control on the index level is allowed. As an example, in the above case, we might want to change from the default 1 shard with 1 replica per index, to 2 shards with 1 replica per index (because this user tweets a lot). Here is how this can be done (the configuration can be in yaml as well):
@@ -191,7 +191,7 @@ h3. Distributed, Highly Available
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Let's face it, things will fail....
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Elasticsearch is a highly available and distributed search engine. Each index is broken down into shards, and each shard can have one or more replicas. By default, an index is created with 5 shards and 1 replica per shard (5/1). There are many topologies that can be used, including 1/10 (improve search performance), or 20/1 (improve indexing performance, with search executed in a map reduce fashion across shards).
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Elasticsearch is a highly available and distributed search engine. Each index is broken down into shards, and each shard can have one or more replicas. By default, an index is created with 1 shards and 1 replica per shard (1/1). There are many topologies that can be used, including 1/10 (improve search performance), or 20/1 (improve indexing performance, with search executed in a map reduce fashion across shards).
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In order to play with the distributed nature of Elasticsearch, simply bring more nodes up and shut down nodes. The system will continue to serve requests (make sure you use the correct http port) with the latest data indexed.
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