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branch-4.1: [opt](point query) reduce point-query network overhead by resending query context on cache miss #62836#63013

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branch-4.1: [opt](point query) reduce point-query network overhead by resending query context on cache miss #62836#63013
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@github-actions github-actions Bot commented May 6, 2026

Cherry-picked from #62836

…uery context on cache miss (#62836)

During each point query operation, the FE sends the queried table,
output expression, and query option to the BE. When the hit rate of the
BE lookup connection cache is very high, this request parameter is
invalid.​
If the request sent by FE to BE ignores these parameters, BE will
request FE to resend these parameters when it clearly knows that its
cache is missing. When the cache hit rate of BE lookup connection is
very high, this benefit will be significant. Generally, only when a
connection is newly established for the first time will there be an
additional resend request (this can also be optimized in the future).​
In our production environment, when performing 340,000 QPS/s queries on
an 11-column table, the outbound network traffic of FE reaches as high
as 2.29 GB/s, but the actual inbound network traffic of the Client is
only 430 MB/s, which means that up to 1.9 GB/s of traffic is the request
traffic sent by FE to BE. After applying this optimization, the outbound
network traffic of FE is only 550 MB/s, and the query throughput under
the same concurrency has also increased by 10%.
@github-actions github-actions Bot requested a review from yiguolei as a code owner May 6, 2026 07:50
@hello-stephen
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Thank you for your contribution to Apache Doris.
Don't know what should be done next? See How to process your PR.

Please clearly describe your PR:

  1. What problem was fixed (it's best to include specific error reporting information). How it was fixed.
  2. Which behaviors were modified. What was the previous behavior, what is it now, why was it modified, and what possible impacts might there be.
  3. What features were added. Why was this function added?
  4. Which code was refactored and why was this part of the code refactored?
  5. Which functions were optimized and what is the difference before and after the optimization?

@hello-stephen
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run buildall

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