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<!-- Add the related story/sub-task/bug number, like Resolves #123, or remove if NA --> **Related issue:** Resolves #42836 This is another hot path optimization. ## Before When a host submits policy results via `SubmitDistributedQueryResults`, the system needed to determine which policies "flipped" (changed from passing to failing or vice versa). Each consumer computed this independently: ``` SubmitDistributedQueryResults(policyResults) | +-- processScriptsForNewlyFailingPolicies | filter to failing policies with scripts | BUILD SUBSET of results | CALL FlippingPoliciesForHost(subset) <-- DB query #1 | convert result to set, filter, queue scripts | +-- processSoftwareForNewlyFailingPolicies | filter to failing policies with installers | BUILD SUBSET of results | CALL FlippingPoliciesForHost(subset) <-- DB query #2 | convert result to set, filter, queue installs | +-- processVPPForNewlyFailingPolicies | filter to failing policies with VPP apps | BUILD SUBSET of results | CALL FlippingPoliciesForHost(subset) <-- DB query #3 | convert result to set, filter, queue VPP | +-- webhook filtering | filter to webhook-enabled policies | CALL FlippingPoliciesForHost(subset) <-- DB query #4 | register flipped policies in Redis | +-- RecordPolicyQueryExecutions CALL FlippingPoliciesForHost(all results) <-- DB query #5 reset attempt counters for newly passing INSERT/UPDATE policy_membership ``` Each `FlippingPoliciesForHost` call runs `SELECT policy_id, passes FROM policy_membership WHERE host_id = ? AND policy_id IN (?)`. All 5 queries hit the same table for the same host before `policy_membership` is updated, so they all see identical state. Each consumer also built intermediate maps to narrow down to its subset before calling `FlippingPoliciesForHost`, then converted the result into yet another set for filtering. This meant 3-4 temporary maps per consumer. ## After ``` SubmitDistributedQueryResults(policyResults) | CALL FlippingPoliciesForHost(all results) <-- single DB query build newFailingSet, normalize newPassing | +-- processScriptsForNewlyFailingPolicies | filter to failing policies with scripts | CHECK newFailingSet (in-memory map lookup) | queue scripts | +-- processSoftwareForNewlyFailingPolicies | filter to failing policies with installers | CHECK newFailingSet (in-memory map lookup) | queue installs | +-- processVPPForNewlyFailingPolicies | filter to failing policies with VPP apps | CHECK newFailingSet (in-memory map lookup) | queue VPP | +-- webhook filtering | filter to webhook-enabled policies | FILTER newFailing/newPassing by policy IDs (in-memory) | register flipped policies in Redis | +-- RecordPolicyQueryExecutions USE pre-computed newPassing (skip DB query) reset attempt counters for newly passing INSERT/UPDATE policy_membership ``` The intermediate subset maps and per-consumer set conversions are removed. Each process function goes directly from "policies with associated automation" to "is this policy in newFailingSet?" in a single map lookup. # Checklist for submitter If some of the following don't apply, delete the relevant line. - [x] Changes file added for user-visible changes in `changes/`, `orbit/changes/` or `ee/fleetd-chrome/changes`. ## Testing - [x] Added/updated automated tests - [x] QA'd all new/changed functionality manually <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Performance Improvements** * Reduced redundant database queries during policy result submissions by computing flipping policies once per host check-in instead of multiple times. <!-- end of auto-generated comment: release notes by coderabbit.ai -->
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- Reduced redundant database queries during policy result submission by computing flipping policies once per host check-in instead of multiple times.
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