When formatting as a timeseries, convert to many instead of wide

[iwysiu]

Currently, when we need to convert frames into the timeseries format, we covert the long format (what we get from the queries) into a wide format with the data.LongToWide function. The problem with wide format, which we currently use, is that if labels (string fields) have unique values, it creates a new column for every value. This means, that for data with n points, we end up with a n x n sized frame after converting it. Instead, we should convert to the many format, which would create n separate size 1 data frames, taking up significantly less memory.

The main part of this is that we currently use the data.LongToWide function from grafana-plugin-sdk-go and there isn't an equivalent function for LongToMany. From what I understand, the two formats should behave the same, but we should test that.

Info about formats: https://grafana.com/developers/dataplane/timeseries

issue reported in https://github.com/grafana/support-escalations/issues/6904

[reagankan]

Hello team, any updates on if this will be worked on? AMG customers are reaching out for a fix. Thank you

[Brandon-Kimberly]

Bumping this again. Any updates?

[taleena]

Hello, we are currently working through support coverage with AWS. This is not in place yet, but once it is we will be able to take this on.

[bhks]

Hi @taleena ,

Do we have this fix worked on, customers are waiting for this issue to get fixed ?

[sidd328]

Hi there, checking in on this issue to see if there is an update?

[iwysiu]

Hi! I'm looking into implementing a fix for this, but I want to understand the use case better. Are the labels distinct for every data point? In that case, what is the use case for formatting it as a time series? It wouldn't be able to graph it as actual time series, it would just appear as a bunch of separate points. Would they be able to use it formated as a table?