Understanding Memory Usage in Relation to Search Requests
TLDR Andrew noticed memory spikes conducting searches. Jason advised it's due to data indexing. Kishore Nallan added that large results require working memory, causing temporary spikes.
Nov 23, 2022 (11 months ago)
Nov 24, 2022 (11 months ago)
Kishore Nallan01:40 AM
As for the second question, difficult to say because there are a few fixed per search overhead.
Indexed 2779 threads (79% resolved)
Increased Memory Usage After Implementing `pinned_hits` in Typesense
John experienced a significant increase in memory usage after using `pinned_hits` at query time in Typesense. Kishore Nallan suggested that the increase was due to the filtering of the dataset but the issue remains unresolved.
Understanding Indexing and Search-As-You-Type In Typesense
Steven had queries about indexing and search-as-you-type in Typesense. Jason clarified that bulk updates are faster and search-as-you-type is resource intensive but worth it. The discussion also included querying benchmarks and Typesense's drop_tokens_threshold parameter, with participation from bnfd.
Improving Typesense Query Performance
Jonathan queried about slower than expected typesense query performance. Jason and Kishore Nallan offered solutions and explanations. After a series of tests, Jonathan found other queries returned results quickly, indicating the issue was specific to the original query.