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Implement production cassandra schema
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3
src/main/scala/com/microsoft/partnercatalyst/fortis/spark/dto/AnalyzedItem.scala
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96 changes: 87 additions & 9 deletions
96
...in/scala/com/microsoft/partnercatalyst/fortis/spark/sinks/cassandra/CassandraSchema.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,17 +1,95 @@ | ||
| package com.microsoft.partnercatalyst.fortis.spark.sinks.cassandra | ||
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| import java.time.Instant.now | ||
| import java.util.UUID | ||
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| import com.microsoft.partnercatalyst.fortis.spark.dto.AnalyzedItem | ||
| import com.microsoft.partnercatalyst.fortis.spark.sinks.cassandra.Utils.{mean, rescale} | ||
| import com.microsoft.partnercatalyst.fortis.spark.transforms.sentiment.SentimentDetector.Neutral | ||
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| case class Sentiment( | ||
| pos_avg: Float, | ||
| neg_avg: Float) | ||
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| case class Gender( | ||
| male_mentions: Int, | ||
| female_mentions: Int) | ||
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| // todo: update with real schema once defined on the cassandra db | ||
| case class CassandraRow( | ||
| created_at: Long, | ||
| pipeline: String) | ||
| case class Entities( | ||
| name: String, | ||
| externalsource: String, | ||
| externalrefid: String, | ||
| count: Float) | ||
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| case class Feature( | ||
| mentions: Int, | ||
| sentiment: Set[Sentiment], | ||
| gender: Set[Gender], | ||
| entities: Set[Entities]) | ||
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| case class Event( | ||
| pipeline: String, | ||
| externalid: String, | ||
| computedfeatures: Set[Feature], | ||
| detectedkeywords: Set[String], | ||
| detectedplaceids: Set[String], | ||
| event_time: Long, | ||
| eventlangcode: String, | ||
| id: UUID, | ||
| insertion_time: Long, | ||
| messagebody: String, | ||
| sourceid: String, | ||
| sourceurl: String, | ||
| title: String) | ||
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| object CassandraSchema { | ||
| def apply(item: AnalyzedItem): CassandraRow = { | ||
| CassandraRow( | ||
| created_at = item.createdAtEpoch, | ||
| pipeline = item.publisher | ||
| ) | ||
| def apply(item: AnalyzedItem): Event = { | ||
| Event( | ||
| pipeline = item.publisher, | ||
| externalid = null, // todo | ||
| computedfeatures = Set(getFeature(item)), | ||
| detectedkeywords = item.analysis.keywords.map(_.name).toSet, | ||
| detectedplaceids = item.analysis.locations.map(_.wofId).toSet, | ||
| event_time = item.createdAtEpoch, | ||
| eventlangcode = item.analysis.language.orNull, | ||
| id = item.id, | ||
| insertion_time = now.getEpochSecond, | ||
| messagebody = item.body, | ||
| sourceid = null, // todo | ||
| sourceurl = item.sourceUrl, | ||
| title = item.title) | ||
| } | ||
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| private def getFeature(item: AnalyzedItem): Feature = { | ||
| val genderCounts = item.analysis.genders.map(_.name).groupBy(identity).mapValues(_.size) | ||
| val entityCounts = item.analysis.entities.map(_.name).groupBy(identity).mapValues(_.size) | ||
| val (positiveSentiments, negativeSentiments) = item.analysis.sentiments.partition(_ > Neutral) | ||
| Feature( | ||
| mentions = -1, | ||
| sentiment = Set(Sentiment( | ||
| pos_avg = mean(rescale(positiveSentiments, 0, 1)).toFloat, | ||
| neg_avg = mean(rescale(negativeSentiments, 0, 1)).toFloat)), | ||
| gender = Set(Gender( | ||
| male_mentions = genderCounts("M"), | ||
| female_mentions = genderCounts("F"))), | ||
| entities = entityCounts.map(kv => Entities( | ||
| name = kv._1, | ||
| count = kv._2, | ||
| externalsource = null, | ||
| externalrefid = null)).toSet) | ||
| } | ||
| } | ||
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| object Utils { | ||
| def mean(items: List[Double]): Double = { | ||
| items.sum / items.length | ||
| } | ||
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| /** @see https://stats.stackexchange.com/a/25897 */ | ||
| def rescale(items: List[Double], min_new: Double, max_new: Double): List[Double] = { | ||
| val min_old = items.min | ||
| val max_old = items.max | ||
| val coef = (max_new - min_new) / (max_old - min_old) | ||
| items.map(v => coef * (v - max_old) + max_new) | ||
| } | ||
| } |
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18 changes: 18 additions & 0 deletions
18
src/test/scala/com/microsoft/partnercatalyst/fortis/spark/sinks/cassandra/UtilsSpec.scala
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,18 @@ | ||
| package com.microsoft.partnercatalyst.fortis.spark.sinks.cassandra | ||
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| import java.text.DecimalFormat | ||
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| import org.scalatest.FlatSpec | ||
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| class UtilsSpec extends FlatSpec { | ||
| "The mean function" should "compute the mean" in { | ||
| assert(Utils.mean(List(1, 2, 3, 4)) == 2.5) | ||
| assert(Utils.mean(List(1.2, -0.2, 1.0, 2)) == 1.0) | ||
| } | ||
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| "The rescale function" should "rescale numbers" in { | ||
| val formatter = new DecimalFormat("#.#") | ||
| assert(Utils.rescale(List(10, 20, 30), 1, 3) == List(1, 2, 3)) | ||
| assert(Utils.rescale(List(0.2, 0.4, 0.6), 0, 1).map(formatter.format) == List("0", "0.5", "1")) | ||
| } | ||
| } |