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83 lines
3.7 KiB
Scala
83 lines
3.7 KiB
Scala
package com.twitter.product_mixer.component_library.selector
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import com.twitter.product_mixer.component_library.model.candidate.BaseTweetCandidate
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import com.twitter.product_mixer.component_library.model.candidate.IsPinnedFeature
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import com.twitter.product_mixer.core.feature.featuremap.FeatureMapBuilder
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import com.twitter.product_mixer.core.model.common.presentation.ItemCandidateWithDetails
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import com.twitter.product_mixer.core.model.common.presentation.CandidatePipelines
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import com.twitter.product_mixer.core.model.common.presentation.CandidateSources
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import com.twitter.product_mixer.core.model.common.presentation.CandidateSourcePosition
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/**
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* Once a pair of duplicate candidates has been found we need to someone 'resolve' the duplication.
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* This may be as simple as picking whichever candidate came first (see [[PickFirstCandidateMerger]]
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* but this strategy could mean losing important candidate information. Candidates might, for
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* example, have different features. [[CandidateMergeStrategy]] lets you define a custom behavior
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* for resolving duplication to help support these more nuanced situations.
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*/
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trait CandidateMergeStrategy {
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def apply(
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existingCandidate: ItemCandidateWithDetails,
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newCandidate: ItemCandidateWithDetails
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): ItemCandidateWithDetails
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}
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/**
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* Keep whichever candidate was encountered first.
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*/
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object PickFirstCandidateMerger extends CandidateMergeStrategy {
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override def apply(
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existingCandidate: ItemCandidateWithDetails,
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newCandidate: ItemCandidateWithDetails
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): ItemCandidateWithDetails = existingCandidate
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}
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/**
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* Keep the candidate encountered first but combine all candidate feature maps.
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*/
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object CombineFeatureMapsCandidateMerger extends CandidateMergeStrategy {
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override def apply(
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existingCandidate: ItemCandidateWithDetails,
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newCandidate: ItemCandidateWithDetails
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): ItemCandidateWithDetails = {
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// Prepend new because list set keeps insertion order, and last operations in ListSet are O(1)
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val mergedCandidateSourceIdentifiers =
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newCandidate.features.get(CandidateSources) ++ existingCandidate.features
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.get(CandidateSources)
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val mergedCandidatePipelineIdentifiers =
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newCandidate.features.get(CandidatePipelines) ++ existingCandidate.features
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.get(CandidatePipelines)
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// the unitary features are pulled from the existing candidate as explained above, while
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// Set Features are merged/accumulated.
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val mergedCommonFeatureMap = FeatureMapBuilder()
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.add(CandidatePipelines, mergedCandidatePipelineIdentifiers)
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.add(CandidateSources, mergedCandidateSourceIdentifiers)
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.add(CandidateSourcePosition, existingCandidate.sourcePosition)
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.build()
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existingCandidate.copy(features =
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existingCandidate.features ++ newCandidate.features ++ mergedCommonFeatureMap)
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}
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}
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/**
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* Keep the pinnable candidate. For cases where we are dealing with duplicate entries across
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* different candidate types, such as different sub-classes of
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* [[com.twitter.product_mixer.component_library.model.candidate.BaseTweetCandidate]], we will
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* prioritize the candidate with [[IsPinnedFeature]] because it contains additional information
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* needed for the positioning of a pinned entry on a timeline.
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*/
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object PickPinnedCandidateMerger extends CandidateMergeStrategy {
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override def apply(
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existingCandidate: ItemCandidateWithDetails,
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newCandidate: ItemCandidateWithDetails
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): ItemCandidateWithDetails =
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Seq(existingCandidate, newCandidate)
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.collectFirst {
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case candidate @ ItemCandidateWithDetails(_: BaseTweetCandidate, _, features)
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if features.getTry(IsPinnedFeature).toOption.contains(true) =>
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candidate
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}.getOrElse(existingCandidate)
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}
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