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update cloud env #1057
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| Original file line number | Diff line number | Diff line change |
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| --- | ||
| title: Operating in the cloud | ||
| title: Cloud operation costs | ||
| sidebar_position: 1 | ||
| --- | ||
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| Quickwit has only been tested on AWS S3. This page sums up what we have learned from that. | ||
| Quickwit has been tested on Amazon S3. This page sums up what we have learned from that experience. | ||
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| ## Data transfers costs and latency | ||
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| Cloud providers charge for data transfers in and out of their networks. In addition, querying an index from a remote machine adds some extra latency. For those reasons, we recommend that you test and use the Quickwit from an instance located within your cloud provider's network. | ||
| Cloud providers charge for data transfers in and out of their networks. In addition, querying an index from a remote machine adds some extra latency. | ||
| For those reasons, we recommend that you test and use the Quickwit from an instance located within your cloud provider's network. | ||
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| ## Optimizing bandwidth with wisely chosen instances | ||
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| To get the best performance out of Quickwit search from object storage, we recommend picking an instance with high network bandwidth. | ||
| In our experience, `c5n.2xlarge` instances offer the bigger bang for your buck. | ||
| We recommend picking instances with high network performance to allow faster downloads from Amazon S3. In our experience, `c5n.2xlarge` instances offer the best bang for your buck. | ||
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| ## GET/PUT requests costs | ||
| ## Requests cost | ||
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| A final note on object storage requests costs. These are [quite low](https://aws.amazon.com/s3/pricing/) actually, $0,0004 / 1000 requests for GET and $0.005 / 1000 requests for PUT on AWS S3, so you don't need to worry too much about it. | ||
| A final note on object storage requests costs. These are [quite low](https://aws.amazon.com/s3/pricing/) actually, $0,0004 / 1000 requests for GET and $0.005 / 1000 requests for PUT on AWS S3. | ||
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| Indeed when indexing, Quickwit generates [splits](../overview/architecture.md#splits) of 5 millions documents each and then | ||
| upload them. As they are composed of 9 files, this generates 9 PUT requests per split. When querying one term, Quickwit only needs to make 3 GET requests per split. | ||
| ### PUT requests | ||
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| Of course, these requests could add up quickly if you have a large amount of requests. | ||
| During indexing, Quickwit uploads new splits on Amazon S3 and progressively merges them until they reach 10 million documents that we call “mature splits”. Such splits have a typical size between 1GB and 10GB and will usually require 2 PUT requests to be uploaded (1 PUT request / 5GB). | ||
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| With default indexing parameters `commit_timeout_secs` of 60 seconds and `merge_policy.merge_factor` of 10 and assuming you want to ingest 1 million documents every minute, this will cost you less than $1 / month. | ||
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| ### GET requests | ||
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| When querying, Quickwit needs to make multiple GET requests: | ||
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| ```jsx | ||
| #num requests = #num splits * ((#num search fields * #num terms * 3) + #num fast fields) | ||
| ``` | ||
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| The above formula assumes that the hotcache is cached, which will be loaded after the first query for every split. | ||
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| When positions are not enabled, only 2 GET requests will be executed per term. | ||
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| These requests costs could add up quickly if you have a high number of splits or QPS > 10. | ||
| Don't hesitate to [contact us](mailto:hello@quickwit.io) if this is the case :). | ||
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I would prefer to not put fast field number as today I think we are only getting the timestamp fast field values, right? So I would put only 1.
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Yes you are right, timestamp and sort_by, but sort_by is deacticated