now() and now() minus the FOR interval in the RESAMPLE clause. I'm sending queries/writes to the database via curl and python via requests. default execution time; cq_basic_offset executes at 8:15 instead of 8:00. This behavior is intentional and prevents the CQ from missing data between for an anomalous case). range between now() and 90 minutes prior to now(). In the end, there were 32 queries in total (or 8 in my example) with all the possible combinations of predicates. If no data fall within the FOR interval the CQ writes no points to the Two years ago I wrote about how to use InfluxDB & Grafana for better visualization of network statistics. InfluxDB v2.0 is the latest stable version. the three_weeks RP, and the average_passengers measurement. count_bees field: To see how to combine two InfluxDB features, CQs, and retention policies, GROUP BY time() interval. The default installation was modified in two ways: a small persistent disk was added to store time series data; a user was created ; In From MQTT to InfluxDB, we will write a small service that forwards data from Mosquitto, our MQTT broker, to InfluxDB. cq_basic_offset executes at one-hour intervals, the same interval as the Flux allows you to join on any columns common between two data streams and opens the door for operations such as cross-measurement joins and math across measurements. The CQ calculates the average for the 7:30 interval at 8:00 and 9:00. In the example below, mem is the alias for memUsed and proc is the alias for procTotal. If you’re looking for SHOW queries (for example, SHOW DATABASES or SHOW RETENTION POLICIES), see Schema Exploration.. I still loathe MRTG graphs, but configuring InfluxSNMP was a bit of a pain. A: You are correct. duration literals. and it calculates the average for the 8:00 time interval at 8:30 and 9:00. the destination measurement to store the downsampled data in a non-DEFAULT passengers and complaints: Use a simple CQ to automatically downsample data from a single field InfluxDB OSS 2.0 is now generally available and ready for production use. Notice that the timestamps are for 7:15 and 8:15 instead of 7:00 and 8:00. specified, the EVERY interval, InfluxDB returns the following error: To avoid missing data between execution times, the FOR interval must be equal Customize your InfluxDB OSS URL and we’ll update code examples for you. InfluxDB Primer. Kapacitor, InfluxData’s data processing engine, can do the same work as continuous queries in InfluxDB … InfluxDB does not accept the following query with a HAVING clause. The join() function merges two or more input streams, whose values are equal on a set of common columns, into a single output stream. For information about upgrading to InfluxDB OSS 2.0, see: time mean_complaints mean_passengers, 2016-08-28T07:00:00Z 9 6.5, 2016-08-28T07:30:00Z 9 7.5, 2016-08-28T08:00:00Z 8 11.5, 2016-08-28T08:30:00Z 7 16, examples of continuous queries in Kapacitor, Upgrade from InfluxDB 2.0 beta to InfluxDB 2.0. GROUP BY time() interval. See Frequently Asked Questions Thank you for being part of our community! For example I would need a fourth column d = ('a'+'b'+'c')/3. the query’s time range is between 16:00 and 16:59.999999999. In the interest of letting InfluxDB not worry about that, order tags lexicographically upstream and write your batches in ascending time order (oldest first). This comment type cannot span several lines. point between 8:00 and 9:00 (8, 15, 15, and 17). advanced CQ syntax. Needless to say that running them all took quite a while, because the table had around 200M records and only one predicate could profit from an index. The basic CQ runs a single query that covers the time range between now() Retention Policies Definition. intersects with now(). When the CQ executes, it runs a single query for the time range between The following function calculates the batch sizes written to an InfluxDB cluster by joining If the EVERY interval is greater than the GROUP BY time() interval, the CQ CQs operate on realtime data, that is, data with timestamps that occur handles duplicate points measurement. CQs operate on real-time data. This comment type can span several lines. The query calculates the average number of bees at 30 minute intervals and I'm putting meteorological data in to the database and am having trouble getting any CQs to work even with what I see as the simplest case. I'm trying to combine stats from a couple ethernet interfaces and combine them to show aggregate bandwidth. Then simply query the CQ results to calculate the outer-most function. between now() and now() minus the GROUP BY time() interval, that is, Most do not. For more on user privileges, see Authentication and Authorization. from every measurement in the transportation database (in this case, there’s only the create a temporary table/result set, with that new column d computed as one needs to). cq_advanced_every executes at 30-minute intervals, the same interval as the The RESAMPLE clause works with either or both of the EVERY and FOR intervals new _value column. between now() and now() minus the GROUP BY time() interval, that is, the between 8:00 and 9:00 (8,15, and 15). destination measurement. InfluxDB does not accept the following query with a nested function. Use a function with a wildcard (*) and INTO query’s to change the value reported for intervals with no data. previous value is outside the query’s time range. Note: If two continuous queries on different databases have the same name, only one of the continuous queries will run. For groups, the returned timestamps mark the start of the GROUP BY time() interval. It is possible to keep important data as long as you want to, without performance impact using so-called Continuous Queries (they will be described in part 2). GROUP BY time() interval. Note: InfluxQL supports subqueries which also offer the same functionality as nested functions. This page documents an earlier version of InfluxDB. If the GROUP BY time() interval is one hour and the current time is 17:00, cq_advanced_for_fill executes at one-hour intervals, the same interval as the Every hour, cq_basic_offset runs a single query that covers the time range total number of running processes, then calculate the average memory usage per running process. InfluxDB - memory usage and processes. See the equivalent InfluxDB v2.0 documentation: Process Data with InfluxDB tasks. The examples below use the following sample data in the transportation precision and remove the dispensable, high precision data from the database. range between now() and ten minutes prior to now(). Because of the way InfluxDB specified measurement. now() and now() minus the GROUP BY time() interval, that is, the time This allows for fast access for aggregate queries which do not need stronger sorting guarantees. configured. bus_data measurement and stores the results in the average_passengers Search form. the population of graphs and dashboards. After making some assumptions, I can calculate the efficiency of heat transfer with this formula: I collect temperature reading from each sensor at 2 different times for a total of 8 points. To find support, the following resources are available: InfluxDB Cloud and InfluxDB Enterprise customers can contact InfluxData Support. bus_data measurement). Retries — If the write destination (InfluxDB, load balancer, message queue, etc.) Shorten query runtimes by pre-calculating expensive queries with CQs. to build a new table by mapping the existing _time column to a new _time that covers the time range between now() and now() minus the EVERY if the EVERY interval or FOR interval is not provided (see the first issue in To learn when to use Kapacitor instead of InfluxDB and how to perform the same CQ Currently, this is the intended behavior. basic syntax behavior Use a FOR interval and fill() to change the value reported for time Grafana join two tables. InfluxDB Jaeger Loki Microsoft SQL Server MySQL OpenTSDB PostgreSQL Prometheus Tempo ... For users, with numerous dashboards or with a large volume of queries, the ability to reuse the query result from one panel in another panel can be a huge performance gain. Every 30 minutes, cq_advanced_every runs a single query that covers the time range between now() and now() minus the FOR interval, that is, the time Every 30 minutes, cq_basic_br runs a single query that covers the time range cq_advanced_for_fill calculates the one-hour average of passengers from the The structure of and data stored in _internal can change at any time. function, cq_basic_br executes at 30 minutes intervals, the same interval as the GROUP BY time() interval. InfluxDB database’s preset time boundaries to determine when to execute and what time from the bus_data measurement and stores the results in the InfluxDB OSS 2.0 is now generally available and ready for production use. cq_basic calculates the average hourly number of passengers from the fill() By default, all See the advanced syntax for how to configure the query’s outlines a feature request for CQs to support gaps in data coverage. measurement in the transportation database. CQs do not write any results for a time interval if no data fall within that database. We recommend visiting the Downsampling and Data Retention guide to see how to combine two InfluxDB features, CQs and retention policies, to periodically downsample data and automatically expire the dispensable high precision data. Yes, I am aware that one can have that "d" field, as a predefined column (pre-computed) in the datasource (i.e. Expiring the old data in the time series database is enabled through continuous queries and data retention policies. If the EVERY interval is two hours, InfluxDB executes the CQ at the top of The cq_query requires a This returns the number of running processes. Only admin users are allowed to work with CQs. I have some network counters in Influx that I graph with Grafana. EVERY interval. Any user-specified time ranges in the cq_query’s WHERE clause will be ignored Note that at least one data point must fall within the FOR interval for fill() is backed up or down, clients (in this case, Telegraf) can fail to write. GitHub Issue #6963 that fall within that time range. an INTO clause, bus_data measurement and stores the results in the average_passengers by the system. guide for an in-depth discussion about this CQ use case. cover in the query. Every hour, cq_basic_rp runs a single query that covers the time range between A possible workaround is to use the In this case the labels that represent the dimensions will have two keys based on the two string typed columns Location and Sensor. To change a CQ, you must DROP and reCREATE it with the updated settings. cq_advanced_for calculates the 30-minute average of passengers range between now() and now() minus the FOR interval, that is, the time This is how my data are organized: I know InfluxDB doesn’t do `JOIN`s but is there a way to perform something like the following query? Tip: Pre-calculate queries for your preferred graphing tool to accelerate Kapacitor, InfluxData’s data processing engine, can do the same work as If your function does not support nesting, you can get the same functionality using a CQ to calculate data |deadman(100.0, 10s, lambda: hour("time") >= 8 AND hour("time") <= … server’s timestamp, the information in the RESAMPLE clause, and the InfluxDB range between now() and one hour prior to now(). If the FOR interval is less than the GROUP BY time() interval or, if CQ’s WHERE clause; cq_basic_offset queries between 7:15 and 8:14.999999999 instead of 7:00 and 7:59.999999999. of bees at 30 minute intervals and the average of those counts: This step performs the count("bees") part of the nested function above. Now that you know how to create CQs with InfluxDB, check out Downsampling and Data Retention for how to combine CQs with retention policies to automatically downsample data and expire unnecessary data. The following CQ automatically calculates the number of non-null values of bees at 30 minute intervals See the InfluxDB OSS 2.0 release notes. The measurement bus_data stores 15-minute resolution data on the number of bus and writes those counts to the count_bees field in the aggregate_bees measurement. CQs default to the relevant You'll also learn how to combine Flux queries with other data to perform advanced analytics and joins to truly understand your entire environment! I also found #3762 and some other tickets where people asked for the same. Annotated log output on the morning of August 28, 2016: Fully qualify To see how to combine two InfluxDB features, CQs, and retention policies, to periodically downsample data and automatically expire the dispensable high precision data, see Downsampling and data retention. and now() minus the GROUP BY time() interval. measurement. The CQ calculates the average for the 7:30 time interval at 8:00 and at 8:30, to backfill results for data with older timestamps. 2. Because this step creates a CQ you only need to execute it once. Read on for details about to monitor network interface statistics using Telegraf, InfluxDB and Grafana.