| package io.prediction.commons.settings |
| |
| import org.specs2._ |
| import org.specs2.specification.Step |
| import com.mongodb.casbah.Imports._ |
| |
| class ParamGenInfosSpec extends Specification { def is = |
| "PredictionIO ParamGenInfos Specification" ^ |
| p^ |
| "ParamGenInfos can be implemented by:" ^ endp^ |
| "1. MongoParamGenInfos" ^ mongoParamGenInfos^end |
| |
| def mongoParamGenInfos = p^ |
| "MongoParamGenInfos should" ^ |
| "behave like any ParamGenInfos implementation" ^ paramGenInfos(newMongoParamGenInfos)^ |
| Step(MongoConnection()(mongoDbName).dropDatabase()) |
| |
| def paramGenInfos(paramGenInfos: ParamGenInfos) = { t^ |
| "create and get a parameter generator info" ! insertAndGet(paramGenInfos)^ |
| "update a parameter generator info" ! update(paramGenInfos)^ |
| "delete a parameter generator info" ! delete(paramGenInfos)^ |
| "backup and restore parameter generator info" ! backuprestore(paramGenInfos)^ |
| bt |
| } |
| |
| val mongoDbName = "predictionio_mongoparamgeninfos_test" |
| def newMongoParamGenInfos = new mongodb.MongoParamGenInfos(MongoConnection()(mongoDbName)) |
| |
| def insertAndGet(paramGenInfos: ParamGenInfos) = { |
| val mapk = ParamGenInfo( |
| id = "map-k", |
| name = "Mean Average Precision", |
| description = None, |
| commands = Some(Seq( |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtKDataPreparator --hdfs --test_dbType $appdataTestDbType$ --test_dbName $appdataTestDbName$ --test_dbHost $appdataTestDbHost$ --test_dbPort $appdataTestDbPort$ --training_dbType $appdataTrainingDbType$ --training_dbName $appdataTrainingDbName$ --training_dbHost $appdataTrainingDbHost$ --training_dbPort $appdataTrainingDbPort$ --modeldata_dbType $modeldataTrainingDbType$ --modeldata_dbName $modeldataTrainingDbName$ --modeldata_dbHost $modeldataTrainingDbHost$ --modeldata_dbPort $modeldataTrainingDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$ --goalParam $goalParam$", |
| "java -Dio.prediction.base=$base$ $configFile$ -Devalid=$evalid$ -Dalgoid=$algoid$ -Dk=$kParam$ -Dmetricid=$metricid$ -Dhdfsroot=$hdfsRoot$ -jar $topkJar$", |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtK --hdfs --dbType $settingsDbType$ --dbName $settingsDbName$ --dbHost $settingsDbHost$ --dbPort $settingsDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$")), |
| paramdefaults = Map("k" -> 20), |
| paramnames = Map("k" -> "k"), |
| paramdescription = Map("k" -> "Averaging window size"), |
| paramorder = Seq("k")) |
| paramGenInfos.insert(mapk) |
| paramGenInfos.get("map-k") must beSome(mapk) |
| } |
| |
| def update(paramGenInfos: ParamGenInfos) = { |
| val mapk = ParamGenInfo( |
| id = "u-map-k", |
| name = "Mean Average Precision", |
| description = None, |
| commands = Some(Seq( |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtKDataPreparator --hdfs --test_dbType $appdataTestDbType$ --test_dbName $appdataTestDbName$ --test_dbHost $appdataTestDbHost$ --test_dbPort $appdataTestDbPort$ --training_dbType $appdataTrainingDbType$ --training_dbName $appdataTrainingDbName$ --training_dbHost $appdataTrainingDbHost$ --training_dbPort $appdataTrainingDbPort$ --modeldata_dbType $modeldataTrainingDbType$ --modeldata_dbName $modeldataTrainingDbName$ --modeldata_dbHost $modeldataTrainingDbHost$ --modeldata_dbPort $modeldataTrainingDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$ --goalParam $goalParam$", |
| "java -Dio.prediction.base=$base$ $configFile$ -Devalid=$evalid$ -Dalgoid=$algoid$ -Dk=$kParam$ -Dmetricid=$metricid$ -Dhdfsroot=$hdfsRoot$ -jar $topkJar$", |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtK --hdfs --dbType $settingsDbType$ --dbName $settingsDbName$ --dbHost $settingsDbHost$ --dbPort $settingsDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$")), |
| paramdefaults = Map("k" -> 20), |
| paramnames = Map("k" -> "k"), |
| paramdescription = Map("k" -> "Averaging window size"), |
| paramorder = Seq("k")) |
| paramGenInfos.insert(mapk) |
| val updatedMapk = mapk.copy( |
| paramdefaults = mapk.paramdefaults ++ Map("f" -> 20), |
| paramnames = mapk.paramnames ++ Map("f" -> "Foo"), |
| paramdescription = mapk.paramdescription ++ Map("f" -> "FooBar"), |
| paramorder = Seq("f", "k")) |
| paramGenInfos.update(updatedMapk) |
| paramGenInfos.get("u-map-k") must beSome(updatedMapk) |
| } |
| |
| def delete(paramGenInfos: ParamGenInfos) = { |
| val mapk = ParamGenInfo( |
| id = "foo", |
| name = "Mean Average Precision", |
| description = None, |
| commands = Some(Seq( |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtKDataPreparator --hdfs --test_dbType $appdataTestDbType$ --test_dbName $appdataTestDbName$ --test_dbHost $appdataTestDbHost$ --test_dbPort $appdataTestDbPort$ --training_dbType $appdataTrainingDbType$ --training_dbName $appdataTrainingDbName$ --training_dbHost $appdataTrainingDbHost$ --training_dbPort $appdataTrainingDbPort$ --modeldata_dbType $modeldataTrainingDbType$ --modeldata_dbName $modeldataTrainingDbName$ --modeldata_dbHost $modeldataTrainingDbHost$ --modeldata_dbPort $modeldataTrainingDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$ --goalParam $goalParam$", |
| "java -Dio.prediction.base=$base$ $configFile$ -Devalid=$evalid$ -Dalgoid=$algoid$ -Dk=$kParam$ -Dmetricid=$metricid$ -Dhdfsroot=$hdfsRoot$ -jar $topkJar$", |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtK --hdfs --dbType $settingsDbType$ --dbName $settingsDbName$ --dbHost $settingsDbHost$ --dbPort $settingsDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$")), |
| paramdefaults = Map("k" -> 20), |
| paramnames = Map("k" -> "k"), |
| paramdescription = Map("k" -> "Averaging window size"), |
| paramorder = Seq("k")) |
| paramGenInfos.insert(mapk) |
| paramGenInfos.delete("foo") |
| paramGenInfos.get("foo") must beNone |
| } |
| |
| def backuprestore(paramGenInfos: ParamGenInfos) = { |
| val mapkbk = ParamGenInfo( |
| id = "backup", |
| name = "Mean Average Precision", |
| description = None, |
| commands = Some(Seq( |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtKDataPreparator --hdfs --test_dbType $appdataTestDbType$ --test_dbName $appdataTestDbName$ --test_dbHost $appdataTestDbHost$ --test_dbPort $appdataTestDbPort$ --training_dbType $appdataTrainingDbType$ --training_dbName $appdataTrainingDbName$ --training_dbHost $appdataTrainingDbHost$ --training_dbPort $appdataTrainingDbPort$ --modeldata_dbType $modeldataTrainingDbType$ --modeldata_dbName $modeldataTrainingDbName$ --modeldata_dbHost $modeldataTrainingDbHost$ --modeldata_dbPort $modeldataTrainingDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$ --goalParam $goalParam$", |
| "java -Dio.prediction.base=$base$ $configFile$ -Devalid=$evalid$ -Dalgoid=$algoid$ -Dk=$kParam$ -Dmetricid=$metricid$ -Dhdfsroot=$hdfsRoot$ -jar $topkJar$", |
| "$hadoop$ jar $pdioEvalJar$ io.prediction.metrics.scalding.itemrec.map.MAPAtK --hdfs --dbType $settingsDbType$ --dbName $settingsDbName$ --dbHost $settingsDbHost$ --dbPort $settingsDbPort$ --hdfsRoot $hdfsRoot$ --appid $appid$ --engineid $engineid$ --evalid $evalid$ --metricid $metricid$ --algoid $algoid$ --kParam $kParam$")), |
| paramdefaults = Map("k" -> 20), |
| paramnames = Map("k" -> "k"), |
| paramdescription = Map("k" -> "Averaging window size"), |
| paramorder = Seq("k")) |
| paramGenInfos.insert(mapkbk) |
| val fn = "paramgeninfos.bin" |
| val fos = new java.io.FileOutputStream(fn) |
| try { |
| fos.write(paramGenInfos.backup()) |
| } finally { |
| fos.close() |
| } |
| paramGenInfos.restore(scala.io.Source.fromFile(fn)(scala.io.Codec.ISO8859).map(_.toByte).toArray) map { data => |
| data must contain(mapkbk) |
| } getOrElse 1 === 2 |
| } |
| } |
