How does ES scale with many fields?


(Bernhard Berger) #1

I want to save a filter over a category-field (with about 5 distinct
values) of my Elasticsearch documents and ask me if I could use
different field names for every category instead.

F.ex. instead of the fields:
"category", "date"
I would use
"dateRed", "dateBlue", "dateGreen"

So to get all dates from category red I could use "dateRed" instead of
"date && Filter(category=Red)".

I know, I could use different types for every category, but the
documents share some common fields together.

Does Elasticsearch scale well when I use lot of different fields (~100
fields) in my documents or is it better to keep the field number small?

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(Binh Ly) #2

Bernhard,

I would suggest to experiment and see what you find. I've created indexes
with 10 fields, and others with hundreds of fields. Performance should not
be a problem (but experiment anyway). I would be more concerned with
maintainability/usability of your index, i.e. is it easier for you/your
clients to query your index using normalized fields or denormalized fields.

On Wednesday, January 22, 2014 7:38:12 AM UTC-5, Bernhard Berger wrote:

I want to save a filter over a category-field (with about 5 distinct
values) of my Elasticsearch documents and ask me if I could use
different field names for every category instead.

F.ex. instead of the fields:
"category", "date"
I would use
"dateRed", "dateBlue", "dateGreen"

So to get all dates from category red I could use "dateRed" instead of
"date && Filter(category=Red)".

I know, I could use different types for every category, but the
documents share some common fields together.

Does Elasticsearch scale well when I use lot of different fields (~100
fields) in my documents or is it better to keep the field number small?

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(system) #3