Documentation

Frequently asked questions

Account management
Security
Administration
Data types
Writing data
Querying data
Deleting data
InfluxDB tasks
Series and series cardinality

Account management

How do I reset my password?

Use the Forgot Password link on the InfluxDB Cloud login page to update your password. For more information, see Change your password.

How do I switch between InfluxDB Cloud accounts?

Use the Switch Accounts functionality in your InfluxDB Cloud account settings to switch between InfluxDB Cloud accounts. For more information, see Switch InfluxDB Cloud accounts.


Billing and usage

How do I manage payment methods?

  • If you subscribed to InfluxDB Cloud through InfluxData, you can manage payment methods in the Billing section of your InfluxDB Cloud account.
  • If you subscribed to InfluxDB Cloud through a cloud provider marketplace (AWS Marketplace, Azure Marketplace, or GCP Marketplace), use your cloud provider’s billing administration to manage payment methods.

For more information, see Manage InfluxDB Cloud billing.

Who do I contact for billing issues?

For billing issues, please contact InfluxData support.

How do I view data my data usage?

To view your InfluxDB Cloud organization’s data usage, view the Usage page in the InfluxDB Cloud user interface. For more information, see View InfluxDB Cloud data usage.

How do I increase my organization’s rate limits and quotas?


InfluxDB Cloud service health

Where can I see the current status of InfluxDB Cloud?

InfluxDB Cloud regions and underlying services are monitored at all times. To see the current status of InfluxDB Cloud, view the InfluxDB Cloud status page. To receive outage alerts and updates, subscribe to our status page.


Security

What different types of API tokens exist?

InfluxDB Cloud supports the following token types:

  • All-Access tokens
  • Custom tokens

For more information about each token type, see Manage API tokens.

Can I use InfluxDB with authentication disabled?

InfluxDB Cloud enforces security best practices by requiring API requests to be authenticated. Authentication cannot be disabled.

Can you change the permission level of members in your organization?

InfluxDB Cloud has only one permission level for users: Owner. With Owner permissions, a user can delete resources and other users from your organization. Take care when inviting a user.


Administration

How can I identify the version of Flux I’m using in InfluxDB?

For information about what versions of Flux are packaged with official InfluxDB releases, see Flux versions in InfluxDB.

If using a custom build, use the following query to return the current version of Flux being used:

import "array"
import "runtime"

array.from(rows: [{version: runtime.version()}])

For more information, see Query the Flux version.

Why isn’t data dropped after I update a bucket’s retention period?

Below are reasons why data may not be dropped immediately after updating the retention period of a bucket:

  • The retention enforcement service runs hourly. You may need to wait for the next retention enforcement cycle to run.

For more information, see Data retention.

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Data types

What are the minimum and maximum integers that InfluxDB can store?

InfluxDB stores all integers as signed 64bit integers.

Minimum integer: -9223372036854775808
Maximum integer: 9223372036854775807

Values close to but within those limits may lead to unexpected behavior. Some query operations convert 64bit integers to 64bit float values which can cause overflow issues.

What are the minimum and maximum timestamps that InfluxDB can store?

InfluxDB uses 64bit integers to represent Unix nanosecond timestamps.

Minimum timestamp: -9223372036854775806 or 1677-09-21T00:12:43.145224194Z
Maximum timestamp: 9223372036854775806 or 2262-04-11T23:47:16.854775806Z

Timestamps outside that range return a parsing error.

Can I change a field’s data type?

Flux type-conversion functions let you change a fields data type at query time. However, you cannot change the type of a field on disk. Below are some possible workarounds:

  • Copy a field to a new field as a different type. The example below does the following:

    • Queries the example-string-field.
    • Converts field values to booleans.
    • Changes the field name to example-boolean-field.
    • Writes the new field to the source bucket.
    from(bucket: "example-bucket")
        |> range(start: -30d)
        |> filter(fn: (r) => r._measurement == "exampled-measurement")
        |> filter(fn: (r) => r._field == "example-string-field")
        |> toBool()
        |> set(key: "_field", value: "example-boolean-field")
        |> to(bucket: "example-bucket")
    
  • Copy a field to a new bucket as a different type. The example below does the following:

    • Queries the example-int-field from the example-bucket-1 bucket.
    • Converts field values to float values.
    • Changes the field name to example-float-field.
    • Writes the new field to the example-bucket-2 bucket.
    from(bucket: "example-bucket-1")
        |> range(start: -30d)
        |> filter(fn: (r) => r._measurement == "exampled-measurement")
        |> filter(fn: (r) => r._field == "example-int-field")
        |> toFloat()
        |> set(key: "_field", value: "example-float-field")
        |> to(bucket: "example-bucket-2")
    

How does InfluxDB handle field type discrepancies across shards?

Field values can be floats, integers, strings, or Booleans. Field value types cannot differ within a shard, but they can differ across shards.

The SELECT statement returns all field values if all values have the same type. If field value types differ across shards, InfluxDB first performs any applicable cast operations and then returns all values with the type that occurs first in the following list: float, integer, string, Boolean.

If your data have field value type discrepancies, use the syntax <field_key>::<type> to query the different data types.

Example

The measurement just_my_type has a single field called my_field. my_field has four field values across four different shards, and each value has a different data type (float, integer, string, and Boolean).

SELECT * returns only the float and integer field values. Note that InfluxDB casts the integer value to a float in the response.

SELECT * FROM just_my_type

name: just_my_type
------------------
time		                	my_field
2016-06-03T15:45:00Z	  9.87034
2016-06-03T16:45:00Z	  7

SELECT <field_key>::<type> [...] returns all value types. InfluxDB outputs each value type in its own column with incremented column names. Where possible, InfluxDB casts field values to another type; it casts the integer 7 to a float in the first column, and it casts the float 9.879034 to an integer in the second column. InfluxDB cannot cast floats or integers to strings or Booleans.

SELECT "my_field"::float,"my_field"::integer,"my_field"::string,"my_field"::boolean FROM just_my_type

name: just_my_type
------------------
time			               my_field	 my_field_1	 my_field_2		 my_field_3
2016-06-03T15:45:00Z	 9.87034	  9
2016-06-03T16:45:00Z	 7	        7
2016-06-03T17:45:00Z			                     a string
2016-06-03T18:45:00Z					                                true

SHOW FIELD KEYS returns every data type, across every shard, associated with the field key.

Example

The measurement just_my_type has a single field called my_field. my_field has four field values across four different shards, and each value has a different data type (float, integer, string, and Boolean). SHOW FIELD KEYS returns all four data types:

> SHOW FIELD KEYS

name: just_my_type
fieldKey   fieldType
--------   ---------
my_field   float
my_field   string
my_field   integer
my_field   boolean

Writing data

How do I write integer and unsigned integer field values?

In line protocol, identify integers with a trailing i and unsigned integers with a trailing u. Without these, numeric field values are parsed as floats.

# Integer
value=100i

# Unsigned integer
value=100u

# Float
value=100

How does InfluxDB handle duplicate points?

InfluxDB uniquely identifies a point by its measurement, tag set, and timestamp. If you submit a new point with the same measurement, tag set, and timestamp as an existing point, InfluxDB unions the old field with the new field set, and any ties go to the new field set.

For more information, see Handle duplicate data points.

What newline character does the InfluxDB write API require?

InfluxDB line protocol relies on line feed (\n, which is ASCII 0x0A) to indicate the end of one line and the beginning of a new line. Files or data that use a newline character other than \n will result in errors similar to bad timestamp or unable to parse.

Windows newlines

Windows uses carriage return and line feed (\r\n) as the newline character which will result in an error if you manually write line protocol on a Windows machine. Strip out any carriage returns (\r) before submitting the line protocol to the InfluxDB write API.

When should I single quote and when should I double quote when writing data?

Line protocol quote usage guidelines are provided in the line protocol documentation.

Does the precision of the timestamp matter?

Yes. Timestamp precision affects ingest performance. The more precise the timestamp, the longer it takes to write the point. To maximize performance, use the coarsest possible timestamp precision when writing data to InfluxDB. However, if too coarse, you risk writing points from the same series with the same timestamp, which would be treated as duplicate points.


Querying data

Flux

How do I structure fields as columns (like InfluxQL)?

A SELECT statement in InfluxQL returns data with a column for each queried tag and field. The Flux from() function returns data with a column for each tag as well as a _field column that contains the field key. Each field is grouped into a different table.

To structure each field as a column, use either pivot() or schema.fieldsAsCols().

exampleData
    |> pivot(rowKey: ["_time"], columnKey: ["_field"], valueColumn: "_value")
import "influxdata/influxdb/schema"

exampleData
    |> schema.fieldsAsCols()
Example data returned by from()
_measurementsensor_idlocation_field_time_value
machineabc123station20temp2022-01-01T00:00:00Z150.1
machineabc123station20temp2022-01-01T00:00:10Z152.8
machineabc123station20temp2022-01-01T00:00:20Z153.3
_measurementsensor_idlocation_field_time_value
machineabc123station20flow2022-01-01T00:00:00Z12.2
machineabc123station20flow2022-01-01T00:00:10Z14.9
machineabc123station20flow2022-01-01T00:00:20Z16.1
Example pivoted data
_measurementsensor_idlocation_timetempflow
machineabc123station202022-01-01T00:00:00Z150.112.2
machineabc123station202022-01-01T00:00:10Z152.814.9
machineabc123station202022-01-01T00:00:20Z153.316.1

How can I derive a state from multiple field values?

To compare multiple field values and derive a state:

  1. Query all fields necessary to derive a state.

  2. Use pivot() or schema.fieldsAsCols() to pivot fields into columns.

  3. Use map() to iterate over each input row assign a new column value based on values in the field columns.

    The fn parameter of map() defines a functions that outputs a record for each input row. Use conditional logic to assign a state.

from(bucket: "example-bucket")
    |> range(start: -1h)
    |> filter(fn: (r) => r._measurement == "example-measurement")
    |> filter(fn: (r) => r._field == "field1" or r._field == "field2")
    |> pivot(rowKey: ["_time"], columnKey: ["_field"], valueColumn: "_value")
    |> map(
        fn: (r) =>
            ({r with state:
                    if r.field1 > 90 and r.field2 < 10 then
                        "critical"
                    else if r.field1 > 70 and r.field2 < 30 then
                        "warning"
                    else if r.field1 > 40 and r.field2 < 60 then
                        "info"
                    else
                        "ok",
            }),
    )

InfluxQL

How do I use InfluxQL with InfluxDB Cloud?

Using InfluxQL with InfluxDB Cloud is made possible by the 1.x compatiblity API which replicates the /query endpoint from InfluxDB 1.x. This allows all InfluxDB 1.x-compatible clients to work with InfluxDB Cloud. However, InfluxQL relies on a database and retention policy data model doesn’t exist in InfluxDB Cloud, but has been replaced by buckets.

InfluxDB Cloud lets you map unique database and retention policy combinations used in InfluxQL to specific buckets using DBRP mappings.

For detailed instructions on using InfluxQL with InfluxDB Cloud and configuring DBRP mapping, see Query with InfluxQL.

How do I perform mathematical operations in an InfluxQL function?

InfluxQL does not support mathematical operations within functions. Use a subquery to perform the mathematical calculation.

For example, InfluxQL does not support the following syntax:

SELECT MEAN("dogs" - "cats") from "pet_daycare"

Instead, use a subquery to get the same result:

SELECT MEAN("difference") FROM (SELECT "dogs" - "cat" AS "difference" FROM "pet_daycare")

Why does my query return epoch 0 as the timestamp?

In InfluxQL, epoch 0 (1970-01-01T00:00:00Z) is often used as a null timestamp equivalent. If you request a query that has no timestamp to return, such as an aggregation function with an unbounded time range, InfluxDB returns epoch 0 as the timestamp.

Which InfluxQL functions support nesting?

The following InfluxQL functions support nesting:

For information on how to use subqueries as substitutes for nested functions, see InfluxQL data exploration.

What determines the time intervals returned by GROUP BY time() queries?

The time intervals returned by GROUP BY time() queries conform to the InfluxDB database’s preset time windows or to the user-specified offset interval.

Preset time windows

For example, the following query calculates the average value of sunflowers between 6:15pm and 7:45pm and groups those averages into one hour intervals:

SELECT mean("sunflowers")
FROM "flower_orders"
WHERE time >= '2016-08-29T18:15:00Z' AND time <= '2016-08-29T19:45:00Z' GROUP BY time(1h)

InfluxQL uses the duration specified in the GROUP BY time() clause to partition data based on time. Preset time window boundaries fall on the duration unit specified.

For example:

GROUP BY time() durationResulting window boundaries
1s00:00:00 - 00:00:01, 00:00:01 - 00:00:02, etc.
1m00:00:00 - 00:01:00, 00:01:00 - 00:02:00, etc.
5m00:00:00 - 00:05:00, 00:05:00 - 00:10:00, etc.
1h00:00:00 - 01:00:00, 01:00:00 - 02:00:00, etc.

Although window boundaries may fall outside of the queried time range, only points within the queried time range are used in the calculation for each window.

Offset time windows

As another example, the following query calculates the average value of sunflowers between 6:15pm and 7:45pm and groups those averages into one hour intervals. It offsets the InfluxDB database’s preset time windows by 15 minutes.

SELECT mean("sunflowers")
FROM "flower_orders"
WHERE time >= '2016-08-29T18:15:00Z' AND time <= '2016-08-29T19:45:00Z' GROUP BY time(1h,15m)
                                                                                         ---
                                                                                          |
                                                                                   offset interval

InfluxQL uses the duration and offset specified in the GROUP BY time() clause to partition data based on time. Time boundaries begin at the specified offset.

For example:

GROUP BY time() duration and offsetResulting window boundaries
1m,30s00:30:00 - 01:30:00, 01:30:00 - 02:30:00, etc.
5m,15s00:00:15 - 00:05:15, 00:05:15 - 00:10:15, etc.
1h,20m00:20:00 - 01:20:00, 01:20:00 - 02:20:00, etc.

Why do my queries return no data or partial data?

The most common reasons why your query returns no data or partial data:

Querying the wrong retention policy

InfluxDB automatically queries data in a database’s default retention policy (configured as part of a DBRP mapping). If your data is associated another retention policy, you must specify the correct retention policy to get results.

No field key in the SELECT clause

An InfluxQL query requires at least one field key in the SELECT clause. If the SELECT clause includes only tag keys, the query returns an empty response. For more information, see InfluxQL Data exploration.

SELECT query includes GROUP BY time()

If your SELECT query includes a GROUP BY time() clause, only data points between 1677-09-21 00:12:43.145224194 and now() are returned. If any of your data points occur after now(), specify an alternative upper bound in your time interval.

Tag and field key with the same name

Avoid using the same name for a tag and field key. If you inadvertently add the same name for a tag and field key, and then query both together, the query results show the second key queried (tag or field) appended with _1. To query a tag or field key appended with _1, you must drop the appended _1 and include the syntax ::tag or ::field. For example:

-- Query duplicate keys using the correct syntax
SELECT "leaves"::tag, "leaves"::field FROM db.rp."grape"

name: grape
time                leaves     leaves_1
----                --------   ----------
1574128162128468000 species    6.00
1574128238044155000            5.00

Why don’t my GROUP BY time() queries return timestamps that occur after now()?

SELECT statements without a time range defined in the WHERE clause have a default time range of 1677-09-21 00:12:43.145224194 to 2262-04-11T23:47:16.854775806Z UTC. For SELECT statements that don’t specify a time range but have a GROUP BY time() clause, the default time range is 1677-09-21 00:12:43.145224194 UTC to now().

To query data with timestamps that occur after now(), SELECT statements with a GROUP BY time() clause must provide an alternative upper bound in the WHERE clause. For example:

SELECT MEAN("boards") FROM "hillvalley"
WHERE time >= '2022-01-01T00:00:00Z' AND time <= now() + 10d
GROUP BY time(12m) fill(none)

Note that the WHERE clause must provide an alternative upper bound to override the default now() upper bound. The following query merely resets the lower bound to now() such that the query’s time range is between now() and now():

SELECT MEAN("boards") FROM "hillvalley"
WHERE time >= now()
GROUP BY time(12m) fill(none)

For for more on time syntax in queries, see InfluxQL data Exploration.

Can I perform mathematical operations against timestamps?

InfluxQL does not support mathematical operators against timestamp values. Most time calculations must be carried out by the client receiving the query results.

There is limited support for using InfluxQL functions against timestamp values. The ELAPSED() function returns the difference between subsequent timestamps in a single field.

Can I identify write precision from returned timestamps?

InfluxDB stores all timestamps as nanosecond values, regardless of the write precision supplied. InfluxQL silently drops trailing zeros from timestamps which obscures the initial write precision. Because InfluxDB silently drops trailing zeros on returned timestamps, the write precision is not recognizable in the returned timestamps.

When should I use single quote versus double quotes in a query?

Follow these general rules for quotes in InfluxQL queries:

Single quotes
  • Use to quote literal string values, like tag values.
  • Do not use on identifiers like database names, retention policy names, user names, measurement names, tag keys, and field keys.
  • Use on date-time strings.
Double quotes
  • Use on identifiers that start with a digit, contain characters other than [A-z,0-9,_], or that are an InfluxQL keyword. We generally recommend using double quotes on all identifiers, even if they don’t meet these criteria.
  • Do not use on date-time strings.
-- Correctly quote usage

SELECT bikes_available FROM bikes WHERE station_id='9'

SELECT "bikes_available" FROM "bikes" WHERE "station_id"='9'

SELECT MIN("avgrq-sz") AS "min_avgrq-sz" FROM telegraf

SELECT * from "cr@zy" where "p^e"='2'

SELECT "water_level" FROM "h2o_feet" WHERE time > '2015-08-18T23:00:01.232000000Z' AND time < '2015-09-19'

-- Incorrect quote usage

SELECT 'bikes_available' FROM 'bikes' WHERE 'station_id'="9"

SELECT * from cr@zy where p^e='2'

SELECT "water_level" FROM "h2o_feet" WHERE time > "2015-08-18T23:00:01.232000000Z" AND time < "2015-09-19"

Why is my query with a WHERE OR time clause returning empty results?

InfluxQL does not support using OR in the WHERE clause to specify multiple time ranges and returns an empty response if multiple are specified. For example, the following query will return an empty response:

SELECT * FROM "absolutismus"
WHERE time = '2016-07-31T20:07:00Z' OR time = '2016-07-31T23:07:17Z'

Why does fill(previous) return empty results?

fill(previous) doesn’t fill a null value if there is no previous value inside the queried time range.

How do I query data with an identical tag key and field key?

Use the :: syntax to specify if the key is a field key or tag key. For example:

SELECT * FROM "candied" WHERE "almonds"::field > 51
SELECT * FROM "candied" WHERE "almonds"::tag='true'

How do I query data across measurements?

InfluxQL does not support querying multiple measurements All data must be under a single measurement to query it together. To perform cross-measurement queries, use Flux.

Does the order timestamps in a query matter?

No, it doesn’t. There is a only a negligible difference between the following queries:

SELECT ... FROM ... WHERE time > 'timestamp1' AND time < 'timestamp2'
SELECT ... FROM ... WHERE time < 'timestamp2' AND time > 'timestamp1'

How do I query data by a tag with a null value?

In your WHERE clause, specify an empty or null tag value with ''. For example:

SELECT * FROM "vases" WHERE priceless=''

Why am I getting the error, “total duration of queries in the last 30s exceeds limit of 25m0s”?

This error indicates you are exceeding the Total query time global limit for your organization. Potential causes include:

  • A single long-running query.
  • Running too many queries at once.
  • A combination of both.

If you are encountering this error due to a single long-running query, the query and potentially your schema should be analyzed for optimization. The following resources may help:

If you are encountering this error due to the number of concurrent queries, try delaying or staggering queries so they don’t all run at the same time.


Deleting data

Can I delete a field?

Yes. InfluxDB Cloud supports deleting data by field. Use the _field label in your delete predicate to identify the field to delete.

_field == "example-field"

Can I delete a measurement?

Yes. InfluxDB Cloud supports deleting data by measurement. Use the _measurement label in your delete predicate to identify the measurement to delete.

_measurement == "example-measurement"

Can I delete multiple measurements at the same time?

No. InfluxDB Cloud does not support deleting multiple measurements in a single delete request. To delete multiple measurements, issue a delete request for each measurement.

Do I need to verify that data is deleted?

It is not necessary to verify delete operations once they have been submitted to the queue. The /api/v2/delete endpoint returns a 204 response when the delete request has been added to the queue.

Because the delete queue executes asynchronously, there isn't a way to accurately predict when the delete operation will be performed at the storage layer.

If you wish to verify a delete has occurred, try to query the deleted data. If the query returns results, the data has not been fully deleted.


InfluxDB tasks

How does retrying a task affect relative time ranges?

When you retry a task that uses relative time ranges, it will query the original time range of the task execution (run). Whenever a task executes, InfluxDB sets the now option in the task to the scheduled execution time of the task. When using range() or other functions that support relative duration values, these duration values are relative to now(), which returns the value of the now option. Every task run has a unique now option based on the time the run was scheduled to execute.


Series and series cardinality

What is series cardinality?

Series cardinality is the total number of unique measurement, tag set, and field key combinations (series) stored on disk and indexed in memory.

Why does series cardinality matter?

InfluxDB maintains an in-memory index of every series. As the number of unique series grows, it can negatively affect query performance. Each InfluxDB Cloud organization has a series cardinality limit to prevent runaway cardinality. For information about adjusting cardinality limits, see How do I increase my organization’s rate limits and quotas?.

Use influxdb.cardinality() in Flux or SHOW SERIES CARDINALITY in InfluxQL to measure the series cardinality in a bucket. See Resolve high series cardinality for information about reducing series cardinality.


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