Hi,
I use the twitter river who use bulk indexing.
I have a Python script who analyse tweets and return some data.
So i want to analyse each tweet and add two fields to the river with the
returned data.
Maybe i can build a second sheme with id and treatment status in order to
run the script separately and update each doc, but i'm pretty sure there is
a cleaner/easier solution.
Thanks for helping
Thibaut
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Hi,
I am afraid the easiest solution here is to not use rivers but instead
do the loading yourself - using a dedicated python process to consume
the twitter stream, enriching the data and loading it into
elasticsearch using the stream_bulk helper in the official python
client (0).
0 - Helpers — Python Elasticsearch client 8.11.0 documentation
Hope this helps,
Honza
On Tue, Mar 25, 2014 at 5:38 PM, Thibaut Lapierre
thibaut.lapierre@gmail.com wrote:
Hi,
I use the twitter river who use bulk indexing.
I have a Python script who analyse tweets and return some data.
So i want to analyse each tweet and add two fields to the river with the
returned data.
Maybe i can build a second sheme with id and treatment status in order to
run the script separately and update each doc, but i'm pretty sure there is
a cleaner/easier solution.
Thanks for helping
Thibaut
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