# Time Series Data Query Suggestions

**URL:** <https://discuss.elastic.co/t/time-series-data-query-suggestions/1740>\
**Category:** Elasticsearch\
**Created:** [June 2, 2015, 2:38pm UTC](https://discuss.elastic.co/t/time-series-data-query-suggestions/1740 "2015-06-02T14:38:31Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![svk](https://avatars.discourse-cdn.com/v4/letter/s/9de0a6/32.png) [@svk](https://discuss.elastic.co/u/svk)\
**Post date:** [June 2, 2015, 2:38pm UTC](https://discuss.elastic.co/t/time-series-data-query-suggestions/1740/1 "2015-06-02T14:38:31Z")

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Hello,

We are using time series data that comes into @ 10Gbytes / day rate. Our query response times increase dramatically if user wants to increase the the historical perspective they want to achieve. What are some of the strategies to limit the queries that make processor cores peaking trying to query all shards in the system?

Thanks,  
SV

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**Author:** ![otisg](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/otisg/32/492_2.png) [@otisg](https://discuss.elastic.co/u/otisg)\
**Post date:** [June 2, 2015, 6:55pm UTC](https://discuss.elastic.co/t/time-series-data-query-suggestions/1740/2 "2015-06-02T18:55:50Z")

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If you know which reports you need, you can pre-aggregate your data. The problem you are seeing is caused by there being too many docs that you are aggregating on the fly, at read-time.

## Otis

Monitoring \* Alerting \* Anomaly Detection \* Centralized Log Management  
Solr & Elasticsearch Support \* [http://sematext.com/](http://sematext.com/)

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**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [July 6, 2017, 12:10am UTC](https://discuss.elastic.co/t/time-series-data-query-suggestions/1740/3 "2017-07-06T00:10:07Z")

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Closed on July 6, 2017, 12:10am UTC