Understanding Timestamps in Couchbase

Oct 13, 2025 by magicalceylontours.com 102 views

Introduction

When working with time series data in Couchbase, it's essential to understand how to handle timestamps correctly to avoid errors in your queries. In this article, we'll explore a scenario where a query is not returning results due to a timestamp format mismatch between the data and the Couchbase Grafana plugin.

Understanding Timestamps in Couchbase

Couchbase stores JSON data, which can include time series data in a specific format. The _timeseries() function is used to perform cool time series queries on this data. However, when working with numeric timestamps, it's crucial to understand how the Couchbase Grafana plugin expects these timestamps to be formatted.

The Problem

We have two documents, foo1 and foo2, which contain time series data in a numeric timestamp format. When we try to query this data using the Couchbase Grafana plugin, we encounter an error due to a timestamp format mismatch.

The Query

Here's the query we're trying to execute:

SELECT t._t AS `time`, t._v0 AS `value`
FROM water AS d
USE KEYS(["foo1", "foo2"])
UNNEST _timeseries(d, {"ts_ranges": [1367513998000, 1380815997000]}) AS t
WHERE d.region = 'UK'
  AND time_range(t._t)
ORDER BY t._t ASC

The Logs

When we tail the Grafana logs, we see the following error messages:

logger=plugin.couchbase-datasource t=2025-03-11T21:43:47.151446-05:00 level=info msg="Querying couchbase" query_string="SELECT * FROM (SELECT t._t AS `time`, t._v0 AS `value`\nFROM water AS d\nUSE KEYS([\"foo1\", \"foo2\"])\nUNNEST _timeseries(d, {\"ts_ranges\": [1367513998000, 1380815997000]}) AS t\nWHERE d.region = 'UK'\n  AND TO_NUMBER(t._t) > STR_TO_MILLIS('2013-05-02T11:59:58-05:00') AND TO_NUMBER(t._t) <= STR_TO_MILLIS('2013-10-03T10:59:57-05:00')\nORDER BY t._t ASC) AS data ORDER by TO_NUMBER(data.t._t) ASC"
logger=plugin.couchbase-datasource t=2025-03-11T21:43:48.623558-05:00 level=info msg="Query ok"
logger=plugin.couchbase-datasource t=2025-03-11T21:43:48.654112-05:00 level=error msg="Panic occured: interface conversion: interface {} is float64, not string"
logger=plugin.couchbase-datasource t=2025-03-11T21:43:48.888814-05:00 level=error msg="plugin process exited" plugin=/usr/local/var/lib/grafana/plugins/couchbase-datasource/dist/gpx_couchbase_darwin_amd64 id=94249 error="exit status 2"

The Solution

The issue here is that the Couchbase Grafana plugin expects the time field to be a string (e.g., an ISO8601 format like "2013-05-02T11:59:58-05:00"), but our data contains numeric timestamps. To fix this, we need to convert the numeric timestamps to a string format that the plugin can understand.

Conclusion

In this article, we've explored a scenario where a query is not returning results due to a timestamp format mismatch between the data and the Couchbase Grafana plugin. By understanding how the plugin expects timestamps to be formatted, we can convert our numeric timestamps to a string format that the plugin can understand, resolving the issue.

Best Practices

To avoid similar issues in the future, follow these best practices:

Understand the plugin's expectations: Before working with a plugin, make sure you understand how it expects your data to be formatted.
Use the correct data type: Ensure that your data is in the correct data type (e.g., string, numeric) to avoid errors.
Convert data types as needed: If your data needs to be converted to a different data type, do so before passing it to the plugin.

Q&A

Q: What is the issue with the query not returning results? A: The issue is a timestamp format mismatch between the data and the Couchbase Grafana plugin. The plugin expects the time field to be a string (e.g., an ISO8601 format like "2013-05-02T11:59:58-05:00"), but the data contains numeric timestamps.

Q: Why is the plugin expecting a string timestamp? A: The plugin is designed to work with time series data, which is often stored in a string format. By expecting a string timestamp, the plugin can perform date and time calculations and formatting.

Q: How can I convert my numeric timestamps to a string format? A: You can use the STR_TO_MILLIS() function to convert your numeric timestamps to a string format. For example:

SELECT STR_TO_MILLIS(t._t) AS `time`
FROM water AS d
USE KEYS(["foo1", "foo2"])
UNNEST _timeseries(d, {"ts_ranges": [1367513998000, 1380815997000]}) AS t
WHERE d.region = 'UK'
  AND time_range(STR_TO_MILLIS(t._t))
ORDER BY STR_TO_MILLIS(t._t) ASC

Q: What is the difference between STR_TO_MILLIS() and TO_NUMBER()? A: STR_TO_MILLIS() converts a string timestamp to a numeric timestamp, while TO_NUMBER() converts a numeric timestamp to a string timestamp. In the context of this issue, STR_TO_MILLIS() is used to convert the numeric timestamps to a string format that the plugin can understand.

Q: How can I avoid similar issues in the future? A: To avoid similar issues in the future, follow these best practices:

Understand the plugin's expectations: Before working with a plugin, make sure you understand how it expects your data to be formatted.
Use the correct data type: Ensure that your data is in the correct data type (e.g., string, numeric) to avoid errors.
Convert data types as needed: If your data needs to be converted to a different data type, do so before passing it to the plugin.

Q: What are some common issues that can cause a query not to return results? A: Some common issues that can cause a query not to return results include:

Timestamp format mismatch: As seen in this issue, a mismatch between the data's timestamp format and the plugin's expected format can cause errors.
Data type mismatch: Passing data of the wrong data type to a plugin can cause errors.
Missing or incorrect data: If the data is missing or incorrect, the query may not return results.

Q: How can I troubleshoot issues with my queries? A: To troubleshoot issues with your queries, follow these steps:

Check the logs: Review the logs to see if there are any error messages that can help identify the issue.
Verify the data: Ensure that the data is correct and in the expected format.
Check the plugin's documentation: Review the plugin's documentation to ensure that you are using the correct syntax and data types.

By following these best practices and troubleshooting steps, you can avoid common issues like timestamp format mismatches and ensure that your queries return the expected results.