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55 lines
2.1 KiB
Scala
55 lines
2.1 KiB
Scala
package com.twitter.home_mixer.functional_component.feature_hydrator
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import com.twitter.home_mixer.model.HomeFeatures.UserStateFeature
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import com.twitter.home_mixer.service.HomeMixerAlertConfig
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import com.twitter.product_mixer.core.feature.Feature
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import com.twitter.product_mixer.core.feature.featuremap.FeatureMap
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import com.twitter.product_mixer.core.feature.featuremap.FeatureMapBuilder
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import com.twitter.product_mixer.core.functional_component.feature_hydrator.QueryFeatureHydrator
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import com.twitter.product_mixer.core.model.common.identifier.FeatureHydratorIdentifier
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import com.twitter.product_mixer.core.pipeline.PipelineQuery
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import com.twitter.stitch.Stitch
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import com.twitter.timelines.user_health.{thriftscala => uh}
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import com.twitter.timelines.user_health.v1.{thriftscala => uhv1}
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import com.twitter.user_session_store.ReadOnlyUserSessionStore
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import com.twitter.user_session_store.ReadRequest
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import com.twitter.user_session_store.UserSessionDataset
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import com.twitter.user_session_store.UserSessionDataset.UserSessionDataset
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import javax.inject.Inject
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import javax.inject.Singleton
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@Singleton
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case class UserStateQueryFeatureHydrator @Inject() (
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userSessionStore: ReadOnlyUserSessionStore)
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extends QueryFeatureHydrator[PipelineQuery] {
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override val identifier: FeatureHydratorIdentifier =
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FeatureHydratorIdentifier("UserState")
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override val features: Set[Feature[_, _]] = Set(UserStateFeature)
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private val datasets: Set[UserSessionDataset] = Set(UserSessionDataset.UserHealth)
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override def hydrate(query: PipelineQuery): Stitch[FeatureMap] = {
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userSessionStore
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.read(ReadRequest(query.getRequiredUserId, datasets))
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.map { userSession =>
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val userState = userSession.flatMap {
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_.userHealth match {
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case Some(uh.UserHealth.V1(uhv1.UserHealth(userState))) => userState
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case _ => None
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}
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}
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FeatureMapBuilder()
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.add(UserStateFeature, userState)
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.build()
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}
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}
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override val alerts = Seq(
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HomeMixerAlertConfig.BusinessHours.defaultSuccessRateAlert(99.9)
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)
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}
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