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Filter out external feature columns in consistency job comparison #599

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Filter out external feature columns in consistency job comparison #599

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c093e08
filter out external feat cols
aarongreen-stripe Oct 30, 2023
c0430f8
scalafmt
aarongreen-stripe Oct 30, 2023
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12 changes: 10 additions & 2 deletions spark/src/main/scala/ai/chronon/spark/stats/ConsistencyJob.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -88,10 +88,18 @@ class ConsistencyJob(session: SparkSession, joinConf: Join, endDate: String) ext
if (unfilledRanges.isEmpty) return null
val allMetrics = unfilledRanges.map { unfilled =>
val comparisonDf = tableUtils.sql(unfilled.genScanQuery(null, joinConf.metaData.comparisonTable))
// External parts / contextual features don't get logged in the online data but do appear in the comparison table.
// We need to remove them from the comparison df otherwise the comparison metric computation will fail.
// We need to prepend `ext_contextual_` to the feature name since that's how it appears in the comparison df.
val externalFeatureColumns = joinConf.getExternalFeatureCols.map(col => s"ext_contextual_$col")
val comparisonDfNoExternalCols = comparisonDf.select(
comparisonDf.columns.filterNot(externalFeatureColumns.contains(_)).map(org.apache.spark.sql.functions.col): _*
)
val loggedDf =
tableUtils.sql(unfilled.genScanQuery(null, joinConf.metaData.loggedTable)).drop(Constants.SchemaHash)
// there could be external columns that are logged during online env, therefore they could not be used for computing OOC
val loggedDfNoExternalCols = loggedDf.select(comparisonDf.columns.map(org.apache.spark.sql.functions.col): _*)
val loggedDfNoExternalCols =
loggedDf.select(comparisonDfNoExternalCols.columns.map(org.apache.spark.sql.functions.col): _*)
println("Starting compare job for stats")
val joinKeys = if (joinConf.isSetRowIds) {
joinConf.rowIds.toScala
Expand All @@ -100,7 +108,7 @@ class ConsistencyJob(session: SparkSession, joinConf: Join, endDate: String) ext
}
println(s"Using ${joinKeys.mkString("[", ",", "]")} as join keys between log and backfill.")
val (compareDf, metricsKvRdd, metrics) =
CompareBaseJob.compare(comparisonDf,
CompareBaseJob.compare(comparisonDfNoExternalCols,
loggedDfNoExternalCols,
keys = joinKeys,
tableUtils,
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