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Suggest chunking for large ELSER fields #2660

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Jan 30, 2024
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Suggest chunking for large ELSER fields #2660

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10 changes: 6 additions & 4 deletions docs/en/stack/ml/nlp/ml-nlp-elser.asciidoc
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Expand Up @@ -408,9 +408,11 @@ image::images/ml-nlp-elser-v2-test.png[alt="Testing ELSER",align="center"]
* ELSER works best on small-to-medium sized fields that contain natural
language. For connector or web crawler use cases, this aligns best with fields
like _title_, _description_, _summary_, or _abstract_. As ELSER encodes the
first 512 tokens of a field, it may not be as good a match for `body_content` on
web crawler documents, or body fields resulting from extracting text from office
documents with connectors.
first 512 tokens of a field, it may not provide as relevant of results for large
fields. For example, `body_content` on web crawler documents, or body fields
resulting from extracting text from office documents with connectors. For larger
fields like these, consider "chunking" the content into multiple values, where
each chunk can be under 512 tokens.
* Larger documents take longer at ingestion time, and {infer} time per
document also increases the more fields in a document that need to be processed.
* The more fields your pipeline has to perform inference on, the longer it takes
Expand Down Expand Up @@ -521,4 +523,4 @@ image::images/ml-nlp-elser-v2-opt-bm-results.png[alt="ELSER V2 optimized benchma
respectively 14 docs/s and 16 docs/s, indicating a performance improvement due
to virtual cores of 12%.

image::images/ml-nlp-elser-v2-cp-bm-results.png[alt="ELSER V2 cross-platform benchmarks",align="center"]
image::images/ml-nlp-elser-v2-cp-bm-results.png[alt="ELSER V2 cross-platform benchmarks",align="center"]