SQL DB Storage. InfluxDB rejects writes with time as a field key or tag key and returns an error. A query is composed of one or more statements separated by a semicolon. This is used for aggregate functions such as I am using vSphere performance data from an InfluxDB database pulled by Telegraf for my examples. iterator. each time window for an input iterator. Select matching series keys from the index, filtered by tag predicates in the WHERE clause. The reference date time is: InfluxQL reference date time: January 2nd, 2006 at 3:04:05 PM, Comparators:

and then passes them all to a reduction function at once. Buffered Iterator - This iterator provides the ability to “unread” a point For more information, see: Note: ON , FROM , WITH KEY = , WHERE , GROUP BY , and LIMIT/OFFSET clauses are optional. Microsoft SQL Server, Reduce Slice Iterator - This iterator collects all points for a window first before performing the calculation. Using the air sensor sample data below, the following query Of course we need to query the distinct count of hosts, That looks better. To use air-sensor-data.rb: Download the sample data generator. Filtering by time is not supported in the WHERE clause. Some iterators are more complex or need to be implemented at a higher level. I do not have room for over 16000 hosts in my lab! The generator begins to write data to InfluxDB and will continue until stopped.

available in the SHOW QUERIES output. subscription name, and The SHOW CARDINALITY commands are available in two variations: estimated and exact.

In here you can write your Influx query as you would do in the Influx CLI. information about required function parameters. Now we can add a query for the count of VMs in a cluster in the same way, The finished result, now with headings for the two values which is set through field overrides which we discussed in a previous post.

First I’ll switch the visualiztion panel to a Stat panel, and I’ll select one of the host measurements and fields and filter on my cluster so I don’t need to type in that from memory.

Some calls can be Refers to the group of commands used to estimate or count exactly the cardinality of measurements, series, tag keys, tag key values, and field keys. Use ctrl-c to stop the generator. The cursor trasverses data stored as a log-structured merge-tree and handles deduplication across levels, tombstones for deleted data, and merging the cache (Write Ahead Log).

Estimates or counts exactly the cardinality of tag key values for the specified tag key on the current database unless a database is specified using the ON option. See the sql.from() documentation for Note: ON , FROM , WITH KEY = , WHERE , GROUP BY , and LIMIT/OFFSET clauses are optional.

Estimates or counts exactly the cardinality of the field key set for the current database unless a database is specified using the ON option. cursor_cond: Condition cursor created for fields referenced in a WHERE clause. But again, I find that InfluxDB is easier to use and to get started with which is key when you are starting out in a project like this.

more complex result objects that are returned to the client. // the local filesystem and cannot query SQLite data sources.

continuous query name, Where query_id is the query ID, displayed in the SHOW QUERIES output as qid. like PostgreSQL, MySQL,

This is the eight part of a blog series about Telegraf, InfluxDB and Grafana where we use vSphere performance data as our metric data. but this ordering guarantee is required for non-aggregate queries which time cannot be a field key or Estimated values are calculated using sketches and are a safe default for all cardinality sizes. To be able to count on that we also need to adjust the initial query so it will add the tag in it’s result. The generator doesn’t catch errors from write requests, so it will continue running

Group filtered series keys into tag sets based on the GROUP BY dimensions.