perf(ingest/dataplex): stream list_entries / search_entries instead of eager list()#17730
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…list() Calling list() on the GCP pager forces the client to fetch every page before processing begins. For large entry groups like @bigquery with tens-of-thousands of tables this causes an apparent hang. Switch all five call sites to iterate the pager directly so processing starts as soon as the first page arrives and pages are fetched on demand. https://claude.ai/code/session_019UExFjBkJnaKzN4BbdPt9o
…mance concern Glossaries, categories, and terms are small datasets that don't suffer from the eager-evaluation hang. Revert dataplex_glossary.py to its original state; only the entries-specific list_entries / search_entries calls needed the streaming fix. https://claude.ai/code/session_019UExFjBkJnaKzN4BbdPt9o
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treff7es
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Jun 4, 2026
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Why
The Dataplex
@bigqueryentry group is a virtual group that automatically contains metadata for every BigQuery dataset and table in a project. For large projects this can be tens or hundreds of thousands of entries.The old code wrapped both
list_entriesandsearch_entriesinlist(...), which forces the GCP client library to fetch every page before the first entry is processed. With a page size of 100, a project with 50 k tables requires 500 sequential API calls before anything happens — causing an apparent hang.What changed
dataplex_entries.pyonly:_list_entry_stubs: iterate thelist_entriespager directly; the processing loop is now inside thePerfTimerblock so it fires page-by-page._process_spanner_entries: same treatment forsearch_entries; the result loop moved inside the existingtry/exceptso lazy page-fetch errors are still caught.Glossary/term/category calls are left unchanged — those datasets are small and don't exhibit the problem.
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