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Facet & Analytics Performance

Yonik Seeley

Solr Facet Performance

Section titled “Solr Facet Performance”

These benchmarks compare the performance of the new JSON Facet API with it’s “performance-first” architecture, and the existing (legacy) Solr Facets.

Test index details:

  documents: 5M
  index segments: 25
  index size: 1.74GB
  6 single valued string fields with 10, 100, 1000, 10000, 100000, 1000000 unique values respectively.
  6 single valued integer fields as above.
  6 multi-valued string fields with 1-5 values per field, with 10, 100, 1000, 10000, 100000, 1000000 unique values respectively.
  6 multi-valued integer fields as above.
  5% chance of any given field having no values for a particular document.

Test requests details:

  Base test query and filters (the domain) matches 2,161,827 documents.
  Single client thread (and both requests only use a single internal thread per request).
  Single warm-up run per implementation that is discarded.
  Multiple runs across all fields, with fastest time being taken for each field.

Faceting + Average performance

Section titled “Faceting + Average performance”

These benchmarks test faceting on one field and finding the average value in another field per facet bucket.

JSON Facet API command:

json.facet={
  f:{
    type : terms,
    field : m100_5_ss,
    facet : { mean : "avg(s10_s)" }
  }
}

Legacy Facet command:

facet=true&
stats=true&
stats.field={!tag=stat1+mean=true}s10_s&
facet.pivot={!stats=stat1}m100_5_ss&
f.m100_5_ss.facet.limit=10

Only sorting by count was tested since legacy facets (pivot + stats component) do not support sorting buckets by anything else.