Skip to content

Latest commit

 

History

History
51 lines (37 loc) · 1.79 KB

README.rst

File metadata and controls

51 lines (37 loc) · 1.79 KB
Raw

AWS CloudSearch: Exactly Suggestive

This sample code is intended to accompany a blog post and presentation about using AWS CloudSearch to get exact queries as well as human-friendly suggestions of the exact names.

create-domain-indexes.py

Use this to create a new index and domains, or update indexes on an existing domain. If an index already exists, it won't be updated. If any index changes, it will initiate reindexing. For example:

./create-indexes.py --domain exactly-suggestive --update

The indexes it creates are:

  • title: text index which is single valued (only one title is possible)
  • albums: exact-match literal-array (multivalued, case-sensitive, no stemming/splitting) case-insensitive, with stemming/splitting)
  • albums_text: for the suggester, a text-array (multivalued, case-insenstive, with stemming and splitting)

import-docs.py

We've created a sample-docs.json file with titles and albums pulled from production, but all the details redacted. When the data has no albums, we inject 1-4 Rock'n'Roll album names so you can experiment with suggesters.

You can import this (or a modified set of of docs) like:

./import-docs.py --jsonfile sample-docs.json --domain exactly-suggestive

INFO:__main__:Reading file sample-docs.json
INFO:__main__:Sending 166331 docs...

The importer batches updates into about 4MB chunk size to avoid CloudSearch bottlenecks that would occur with single-doc-at-a-time-updates. Never the less, it can take a while to send and ingest those docs. Afterwards, it may take a while for CloudSearch to to actually index these documents so they are searchable.

00:20:00?

TODO: maybe I should have a --maxdocs instead of sending all 166K?