# Continuous query on the full database **URL:** \ **Category:** Systems\ **Tags:** influxdb, query\ **Created:** [April 10, 2019, 9:17am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379 "2019-04-10T09:17:32Z")\ **Posts on this page:** 8\ **Page:** 1
**Author:** ![thebuleon29](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/thebuleon29/32/2822_2.png) [@thebuleon29](https://community.influxdata.com/u/thebuleon29)\ **Post date:** [April 10, 2019, 9:17am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/1 "2019-04-10T09:17:32Z")
Hi, I am a new InfluxDB user and I need some advice on how to correctly use Continuous Queries for downsampling. If I understood the documentation correctly, a Continuous Query to group data by an interval i will be executed on data with timestamps in a range [now()-i, now()]. That means that if I insert data with timestamps older than now()-i, it won’t be concerned by the CQ. I understand that normally CQ are used to save disk space by copying new data in databases with longer Retention Policies and a lower level of detail. I don’t want to use it that way. I am using downsampled databases to make queries on a large time ranges faster and the main database (the one with the non downsampled data) for queries on smaller time ranges. I will also have to insert data with old timestamps from CSV files in the database I am building. That means that I need the CQ to covers the full database. I have two ideas : 1- run a SELECT … INTO … FROM … GROUP BY … query after importing a CSV file. 2- make a CQ with the EVERY and FOR keywords like : ```auto CREATE CONTINUOUS QUERY ON RESAMPLE EVERY FOR BEGIN END ``` This should run the query every EVERY intervals on data with timestamps between now()-FOR and now(). So my idea is to make the FOR interval “infinite”. What do you guys think about these ideas ? Is there a better way to do this ? ---
**Author:** ![rawkode](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/rawkode/32/5161_2.png) [@rawkode](https://community.influxdata.com/u/rawkode)\ **Post date:** [April 10, 2019, 9:38am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/2 "2019-04-10T09:38:16Z")
Hopefully this [example](https://rawko.de/influxdb-rollups) will help ```auto CREATE CONTINUOUS QUERY "rollup_1h" ON "system_stats" BEGIN SELECT mean(*) INTO forever.cpu FROM twoweeks.cpu GROUP BY time(1h) END ``` This rolls up 1s resolution into 1h resolution, rolling up data from `twoweeks.cpu` into `forever.cpu` ---
**Author:** ![thebuleon29](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/thebuleon29/32/2822_2.png) [@thebuleon29](https://community.influxdata.com/u/thebuleon29)\ **Post date:** [April 10, 2019, 9:53am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/3 "2019-04-10T09:53:25Z")
Thanks for your answer 🙂 But if I quote the documentation ([InfluxQL Continuous Queries | InfluxDB OSS 1.7 Documentation](https://docs.influxdata.com/influxdb/v1.7/query_language/continuous_queries/#schedule-and-coverage)): " CQs operate on realtime data. They use the local server’s timestamp, the `GROUP BY time()` interval, and InfluxDB’s preset time boundaries to determine when to execute and what time range to cover in the query. CQs execute at the same interval as the `cq_query` ’s `GROUP BY time()` interval, and they run at the start of InfluxDB’s preset time boundaries. If the `GROUP BY time()` interval is one hour, the CQ executes at the start of every hour. When the CQ executes, it runs a single query for the time range between [`now()`](https://docs.influxdata.com/influxdb/v1.7/concepts/glossary/#now) and `now()` minus the `GROUP BY time()` interval. If the `GROUP BY time()` interval is one hour and the current time is 17:00, the query’s time range is between 16:00 and 16:59.999999999." Doesn’t this mean that only the data from the last hour will be downsampled into “rollup\_1h” ? ---
**Author:** ![rawkode](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/rawkode/32/5161_2.png) [@rawkode](https://community.influxdata.com/u/rawkode)\ **Post date:** [April 10, 2019, 10:26am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/4 "2019-04-10T10:26:24Z")
From the docs: > Issue 3: Backfilling results for older data > > CQs operate on realtime data, that is, data with timestamps that occur relative to [`now()`](https://docs.influxdata.com/influxdb/v1.7/concepts/glossary/#now). Use a basic [`INTO` query](https://docs.influxdata.com/influxdb/v1.7/query_language/data_exploration/#the-into-clause) to backfill results for data with older timestamps. So the following query, as is my understanding, should handle backfilling older data, as it uses `INTO` ``` CREATE CONTINUOUS QUERY "rollup_1h" ON "system_stats" BEGIN SELECT mean(*) INTO forever.cpu FROM twoweeks.cpu GROUP BY time(1h) END ``` ---
**Author:** ![thebuleon29](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/thebuleon29/32/2822_2.png) [@thebuleon29](https://community.influxdata.com/u/thebuleon29)\ **Post date:** [April 10, 2019, 10:50am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/5 "2019-04-10T10:50:28Z")
According to [InfluxQL Continuous Queries | InfluxDB OSS 1.7 Documentation](https://docs.influxdata.com/influxdb/v1.7/query_language/continuous_queries/#basic-syntax), the INTO clause is mandatory in a CQ (“The `cq_query` requires a function, an `INTO`, and a `GROUP BY time()` clause”). So my understanding is that the INTO clause does not change the behavior of the CQ regarding the time range on which it performs the query. I think that the “basic INTO query” you mentioned refers to a regular query (not a continuous one) with an INTO clause, which corresponds to what I called “solution 1” in my original question. ---
**Author:** ![rawkode](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/rawkode/32/5161_2.png) [@rawkode](https://community.influxdata.com/u/rawkode)\ **Post date:** [April 10, 2019, 10:54am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/6 "2019-04-10T10:54:43Z")
Hi @thebuleon29, Let me check with my colleagues and I’ll get back to you 👍 ---
**Author:** ![rawkode](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/rawkode/32/5161_2.png) [@rawkode](https://community.influxdata.com/u/rawkode)\ **Post date:** [April 10, 2019, 11:27am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/7 "2019-04-10T11:27:09Z")
Hi @thebuleon29, My colleagues haven’t gotten back to me yet (timezones 🙂), but I’ve done a lot more reading and I think you’re correct. I’ll submit a PR to the docs to remove any ambiguity in them. You’d need to execute a one time `SELECT INTO` to backfill older data 👍 ---
**Author:** ![thebuleon29](https://sea1.discourse-cdn.com/flex023/user_avatar/community.influxdata.com/thebuleon29/32/2822_2.png) [@thebuleon29](https://community.influxdata.com/u/thebuleon29)\ **Post date:** [April 10, 2019, 11:28am UTC](https://community.influxdata.com/t/continuous-query-on-the-full-database/9379/8 "2019-04-10T11:28:18Z")
Ok, thank you very much !