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It appears that the CSV plugin bundled in binjr is far more popular than I initially envisaged; as a matter of fact, it was originally built as proof-of-concept for the plugin API and never really refined since then.
It is therefore not a huge surprise than there have been several requests for enhancement on this plugin.
I'm starting this discussion to try and centralize these requests and gather feedback on their resolutions.
Add support for browsing all csv files in a folder or a zip archive.
Basically, the same kind of thing that can already be done with log files at the moment
Use a more robust backend
Currently, all data from parsed csv files are stored on the heap, in a NavigableMap. While this works fine for small data set, it will become limited very quickly when trying to address larger ones.
One way to avoir that would be to use a different approach for storing data, off the Java heap and even on disk if need be.
Possible candidates:
RRD4J: Efficient for compact dataset. Not so much for sparse ones. That won't work if the step in the csv timestamp is variable (which is quite likely).
Lucene: As used by the log files adapter. Not the most efficient, storage wise, for strict numerical timeseries.
Something new? QuestDB looks interesting. No prior implementation, though.
Add support for timestamps located elsewhere than the first column.
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Hello everyone!
It appears that the CSV plugin bundled in binjr is far more popular than I initially envisaged; as a matter of fact, it was originally built as proof-of-concept for the plugin API and never really refined since then.
It is therefore not a huge surprise than there have been several requests for enhancement on this plugin.
I'm starting this discussion to try and centralize these requests and gather feedback on their resolutions.
Please feel free to chime in.
support for timestamp in milliseconds (CSVAdapter) #114
This one is well underway: see 886f41e
Add support for browsing all csv files in a folder or a zip archive.
Basically, the same kind of thing that can already be done with log files at the moment
Use a more robust backend
Currently, all data from parsed csv files are stored on the heap, in a
NavigableMap
. While this works fine for small data set, it will become limited very quickly when trying to address larger ones.One way to avoir that would be to use a different approach for storing data, off the Java heap and even on disk if need be.
Possible candidates:
RRD4J: Efficient for compact dataset. Not so much for sparse ones.That won't work if the step in the csv timestamp is variable (which is quite likely).Add support for timestamps located elsewhere than the first column.
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