This repository was archived by the owner on Oct 29, 2024. It is now read-only.
Improve DataFrameClient tags line-protocol conversion performance #503
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
In `_convert_dataframe_to_lines`, if only `global_tags` is specified but not `tag_columns`, take a faster route to process the tags. Previously, in such a case, global tags are duplicated as tag columns and processed as if they were tag columns. Such processing is wasteful and results in a slowdown that becomes noticeable when batch loading many thousands of data points with a handful of global tags.
|
I did a simple performance test on a ~70K data point with 20 global tags. It seems to improve performance by at least 2 times. Here's the test (ipynb). |
|
Nice! |
aviau
approved these changes
Oct 12, 2017
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
In
_convert_dataframe_to_lines, if onlyglobal_tagsis specified butnot
tag_columns, take a faster route to process the tags. Previously,in such a case, global tags are duplicated as tag columns and processed
as if they were tag columns. Such processing is wasteful and results in
a slowdown that becomes noticeable when batch loading many thousands of
data points with a handful of global tags.