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For SPIKE MSEARCH-13 suggestion endpoint has been implemented in branch: feature/msearch-13. This controller allows to perform performing suggest request requests to Elasticsearch using 2 query parameters - query (suggestion prefix to analyze) and limit (default value is 5).
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Performance results of completion query:
- Indexed 2,5 millions million of instances
- Elasticsearch requires 2500 mb MB of java Java heap to store completion data
- Response time ~25~8-30ms10ms from Elasticsearch
MSEARCH-119
SPIKE MSEARCH-119 assumes that is there is a way to return suggest results using wildcard or prefix query.
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Disadvantages of this approach:
- It results in N random documents from Elasticsearch index without relevancy (score=1 for all search hits)
- Using copy_to functionality all values returned in the a lowercase way
- There is no way to use fuzziness search, suggestions can be provided using only by exact prefix match
Performance results:
- Indexed 1 Indexed 2,5 million of instances
- Response time ~20-50ms from Elasticsearch
- Reindexing process is slightly faster and it does not require a lot of Java Heap
Performance tests results:
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