docs-v2/content/influxdb/v2/write-data/troubleshoot.md

title	seotitle	weight	description	menu	influxdb/v2/tags	related
Troubleshoot issues writing data	Troubleshoot issues writing data to InfluxDB	106	Troubleshoot issues writing data. Find response codes for failed writes. Discover how writes fail, from exceeding rate or payload limits, to syntax errors and schema conflicts.	influxdb_v2 name parent Troubleshoot issues Write data	write line protocol errors	/influxdb/v2/api/#tag/Write, InfluxDB API /write endpoint /influxdb/v2/reference/internals /influxdb/v2/reference/cli/influx/write

Learn how to avoid unexpected results and recover from errors when writing to InfluxDB.

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• Handle write and delete responses
• Troubleshoot failures

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• Handle write and delete responses
• Troubleshoot failures
• Troubleshoot rejected points

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Handle write and delete responses

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In InfluxDB Cloud, writes and deletes are asynchronous and eventually consistent. Once InfluxDB validates your request and queues the write or delete, it sends a success response (HTTP 204 status code) as an acknowledgement. To ensure that InfluxDB handles writes and deletes in the order you request them, wait for the acknowledgement before you send the next request. Because writes are asynchronous, keep the following in mind:

• Data might not yet be queryable when you receive success (HTTP 204 status code).
• InfluxDB may still reject points after you receive success (HTTP 204 status code).

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If InfluxDB OSS successfully writes all the request data to the bucket, InfluxDB returns success (HTTP 204 status code). The first rejected point in a batch causes InfluxDB to reject the entire batch and respond with an HTTP error status.

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Review HTTP status codes

InfluxDB uses conventional HTTP status codes to indicate the success or failure of a request. Write requests return the following status codes:

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HTTP response code	Message	Description
204 "Success"		If InfluxDB validated the request data format and queued the data for writing to the bucket
400 "Bad request"	message contains the first malformed line	If data is malformed
401 "Unauthorized"		If the Authorization: Token header is missing or malformed or if the API token doesn't have permission to write to the bucket
404 "Not found"	requested resource type, e.g. "organization", and resource name	If a requested resource (e.g. organization or bucket) wasn't found
413 “Request too large”	cannot read data: points in batch is too large	If a write request exceeds the maximum global limit
429 “Too many requests”	Retry-After header: xxx (seconds to wait before retrying the request)	If a read or write request exceeds your plan's adjustable service quotas or if a delete request exceeds the maximum global limit
500 "Internal server error"		Default status for an error
503 “Service unavailable“	Series cardinality exceeds your plan's service quota	If series cardinality exceeds your plan's adjustable service quotas

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• 204 Success: All request data was written to the bucket.
• 400 Bad request: The line protocol data in the request was malformed. The response body contains the first malformed line in the data. All request data was rejected and not written.
• 401 Unauthorized: May indicate one of the following:
  • Authorization: Token header is missing or malformed.
  • API token value is missing from the header.
  • API token does not have sufficient permissions to write to the organization and the bucket. For more information about token types and permissions, see Manage API tokens.
• 404 Not found: A requested resource (e.g. an organization or bucket) was not found. The response body contains the requested resource type, e.g. "organization", and resource name.
• 413 Request entity too large: All request data was rejected and not written. InfluxDB OSS only returns this error if the Go (golang) ioutil.ReadAll() function raises an error.
• 500 Internal server error: Default HTTP status for an error.
• 503 Service unavailable: Server is temporarily unavailable to accept writes. The Retry-After header describes when to try the write again.

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The message property of the response body may contain additional details about the error. If some of your data did not write to the bucket, see how to troubleshoot rejected points.

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Troubleshoot partial writes

Because writes are asynchronous, they may fail partially or completely even though InfluxDB returns an HTTP 2xx status code for a valid request. For example, a partial write may occur when InfluxDB writes all points that conform to the bucket schema, but rejects points that have the wrong data type in a field. To check for writes that fail asynchronously, create a task to check the _monitoring bucket for rejected points. To resolve partial writes and rejected points, see troubleshoot failures.

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Troubleshoot failures

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If you notice data is missing in your bucket, do the following:

• Check the message property in the response body for details about the error.
• If the message describes a field error, troubleshoot rejected points.
• Verify all lines contain valid syntax (line protocol or CSV).
• Verify the timestamps match the precision parameter.
• Minimize payload size and network errors by optimizing writes.

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{{% cloud-only %}} If you notice data is missing in your bucket, do the following:

• Check the message property in the response body for details about the error--for example, partial write error indicates rejected points.
• Check for rejected points in your organization's _monitoring bucket.
• Verify all lines contain valid syntax (line protocol or CSV). See how to find parsing errors.
• Verify the data types match the series or bucket schema. See how to resolve explicit schema rejections.
• Verify the timestamps match the precision parameter.
• Minimize payload size and network errors by optimizing writes. {{% /cloud-only %}}

Troubleshoot rejected points

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InfluxDB rejects points for the following reasons:

• The batch contains another point with the same series, but one of the fields has a different value type.
• The bucket contains another point with the same series, but one of the fields has a different value type.

Check for field type differences between the missing data point and other points that have the same series--for example, did you attempt to write string data to an int field?

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InfluxDB may have rejected points even if the HTTP request returned "Success". InfluxDB logs rejected data points and associated errors to your organization's _monitoring bucket.

• Review rejected points
  • Find parsing errors
  • Find data type conflicts and schema rejections
• Resolve data type conflicts
• Resolve explicit schema rejections

Review rejected points

To get a log of rejected points, query the rejected_points measurement in your organization's _monitoring bucket. To more quickly locate rejected_points, keep the following in mind:

• If your line protocol batch contains single lines with multiple fields, InfluxDB logs an entry for each point (each unique field) that is rejected.
• Each entry contains a reason tag that describes why the point was rejected.
• Entries for data type conflicts and schema rejections have a count field value of 1.
• Entries for parsing errors contain an error field (and don't contain a count field).

rejected_points schema

Name	Value
_measurement	rejected_points
_field	count or error
_value	1 or error details
bucket	ID of the bucket that rejected the point
measurement	Measurement name of the point
field	Name of the field that caused the rejection
reason	Brief description of the problem. See specific reasons in data type conflicts and schema rejections
gotType	Received field type: Boolean, Float, Integer, String, or UnsignedInteger
wantType	Expected field type: Boolean, Float, Integer, String, or UnsignedInteger
<timestamp>	Time the rejected point was logged

Find parsing errors

If InfluxDB can't parse a line (e.g. due to syntax problems), the response message might not provide details. To find parsing error details, query rejected_points entries that contain the error field.

from(bucket: "_monitoring")
    |> range(start: -1h)
    |> filter(fn: (r) => r._measurement == "rejected_points")
    |> filter(fn: (r) => r._field == "error")

Find data type conflicts and schema rejections

To find rejected_points caused by data type conflicts or schema rejections, query for the count field.

from(bucket: "_monitoring")
    |> range(start: -1h)
    |> filter(fn: (r) => r._measurement == "rejected_points")
    |> filter(fn: (r) => r._field == "count")

Resolve data type conflicts

When you write to a bucket that has the implicit schema type, InfluxDB compares new points to points that have the same series. If a point has a field with a different data type than the series, InfluxDB rejects the point and logs a rejected_points entry. The rejected_points entry contains one of the following reasons:

Reason	Meaning
type conflict in batch write	The batch contains another point with the same series, but one of the fields has a different value type.
type conflict with existing data	The bucket contains another point with the same series, but one of the fields has a different value type.

Resolve explicit schema rejections

If you write to a bucket with an explicit schema, the data must conform to the schema. Otherwise, InfluxDB rejects the data.

Do the following to interpret explicit schema rejections:

• Detect a measurement mismatch
• Detect a field type mismatch

Detect a measurement mismatch

InfluxDB rejects a point if the measurement doesn't match the name of a bucket schema. The rejected_points entry contains the following reason tag value:

Reason	Meaning
measurement not allowed by schema	The bucket is configured to use explicit schemas and none of the schemas matches the measurement of the point.

Consider the following line protocol data.

airSensors,sensorId=TLM0201 temperature=73.97,humidity=35.23,co=0.48 1637014074

The line has an airSensors measurement and three fields (temperature, humidity, and co). If you try to write this data to a bucket that has the explicit schema type and doesn't have an airSensors schema, the /api/v2/write InfluxDB API returns an error and the following data:

{
  "code": "invalid",
  "message": "3 out of 3 points rejected (check rejected_points in your _monitoring bucket for further information)"
}

InfluxDB logs three rejected_points entries, one for each field.

_measurement	_field	_value	field	measurement	reason
rejected_points	count	1	humidity	airSensors	measurement not allowed by schema
rejected_points	count	1	co	airSensors	measurement not allowed by schema
rejected_points	count	1	temperature	airSensors	measurement not allowed by schema

Detect a field type mismatch

InfluxDB rejects a point if the measurement matches the name of a bucket schema and the field data types don't match. The rejected_points entry contains the following reason:

Reason	Meaning
field type mismatch with schema	The point has the same measurement as a configured schema and they have different field value types.

Consider a bucket that has the following airSensors explicit bucket schema:

{
 "name": "airSensors",
 "columns": [
   {
     "name": "time",
     "type": "timestamp"
   },
   {
     "name": "sensorId",
     "type": "tag"
   },
   {
     "name": "temperature",
     "type": "field",
     "dataType": "float"
   },
   {
     "name": "humidity",
     "type": "field",
     "dataType": "float"
   },
   {
     "name": "co",
     "type": "field",
     "dataType": "float"
   }
 ]
}

The following line protocol data has an airSensors measurement, a sensorId tag, and three fields (temperature, humidity, and co).

airSensors,sensorId=L1 temperature=90.5,humidity=70.0,co=0.2 1637014074
airSensors,sensorId=L1 temperature="90.5",humidity=70.0,co=0.2 1637014074

In the example data above, the second point has a temperature field value with the string data type. Because the airSensors schema requires temperature to have the float data type, InfluxDB returns a 400 error and a message that describes the result:

{
  "code": "invalid",
  "message": "partial write error (5 accepted): 1 out of 6 points rejected (check rejected_points in your _monitoring bucket for further information)"
}

InfluxDB logs the following rejected_points entry to the _monitoring bucket:

_measurement	_field	_value	bucket	field	gotType	measurement	reason	wantType
rejected_points	count	1	a7d5558b880a93da	temperature	String	airSensors	field type mismatch with schema	Float

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