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Reformat with 0.2.6 #2

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12 changes: 8 additions & 4 deletions ...s/PredictionIO/common/src/main/scala/io/prediction/authentication/KeyAuthentication.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -40,14 +40,18 @@ trait KeyAuthentication {
Future {

val passedKey = accessKeyParamOpt.getOrElse {
Left(AuthenticationFailedRejection(
AuthenticationFailedRejection.CredentialsRejected, List()))
Left(
AuthenticationFailedRejection(
AuthenticationFailedRejection.CredentialsRejected,
List()))
}

if (passedKey.equals(ServerKey.get)) Right(ctx.request)
else
Left(AuthenticationFailedRejection(
AuthenticationFailedRejection.CredentialsRejected, List()))
Left(
AuthenticationFailedRejection(
AuthenticationFailedRejection.CredentialsRejected,
List()))
}
}
}
7 changes: 4 additions & 3 deletions repos/PredictionIO/common/src/main/scala/io/prediction/configuration/SSLConfiguration.scala
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Expand Up @@ -62,9 +62,10 @@ trait SSLConfiguration {
// provide implicit SSLEngine with some protocols
implicit def sslEngineProvider: ServerSSLEngineProvider = {
ServerSSLEngineProvider { engine =>
engine.setEnabledCipherSuites(Array("TLS_RSA_WITH_AES_256_CBC_SHA",
"TLS_ECDH_ECDSA_WITH_RC4_128_SHA",
"TLS_RSA_WITH_AES_128_CBC_SHA"))
engine.setEnabledCipherSuites(
Array("TLS_RSA_WITH_AES_256_CBC_SHA",
"TLS_ECDH_ECDSA_WITH_RC4_128_SHA",
"TLS_RSA_WITH_AES_128_CBC_SHA"))
engine.setEnabledProtocols(Array("TLSv1", "TLSv1.2", "TLSv1.1"))
engine
}
Expand Down
224 changes: 117 additions & 107 deletions repos/PredictionIO/core/src/main/scala/io/prediction/controller/Engine.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -77,8 +77,8 @@ import scala.language.implicitConversions
* @group Engine
*/
class Engine[TD, EI, PD, Q, P, A](
val dataSourceClassMap: Map[
String, Class[_ <: BaseDataSource[TD, EI, Q, A]]],
val dataSourceClassMap: Map[String,
Class[_ <: BaseDataSource[TD, EI, Q, A]]],
val preparatorClassMap: Map[String, Class[_ <: BasePreparator[TD, PD]]],
val algorithmClassMap: Map[String, Class[_ <: BaseAlgorithm[PD, _, Q, P]]],
val servingClassMap: Map[String, Class[_ <: BaseServing[Q, P]]])
Expand Down Expand Up @@ -117,7 +117,8 @@ class Engine[TD, EI, PD, Q, P, A](
def this(dataSourceClass: Class[_ <: BaseDataSource[TD, EI, Q, A]],
preparatorClass: Class[_ <: BasePreparator[TD, PD]],
algorithmClassMap: _root_.java.util.Map[
String, Class[_ <: BaseAlgorithm[PD, _, Q, P]]],
String,
Class[_ <: BaseAlgorithm[PD, _, Q, P]]],
servingClass: Class[_ <: BaseServing[Q, P]]) = this(
Map("" -> dataSourceClass),
Map("" -> preparatorClass),
Expand Down Expand Up @@ -201,63 +202,62 @@ class Engine[TD, EI, PD, Q, P, A](
Doer(algorithmClassMap(algoName), algoParams)
}

val models =
if (persistedModels.exists(m => m.isInstanceOf[Unit.type])) {
// If any of persistedModels is Unit, we need to re-train the model.
logger.info("Some persisted models are Unit, need to re-train.")
val (dataSourceName, dataSourceParams) = engineParams.dataSourceParams
val dataSource = Doer(
dataSourceClassMap(dataSourceName), dataSourceParams)

val (preparatorName, preparatorParams) = engineParams.preparatorParams
val preparator = Doer(
preparatorClassMap(preparatorName), preparatorParams)

val td = dataSource.readTrainingBase(sc)
val pd = preparator.prepareBase(sc, td)

val models = algorithms.zip(persistedModels).map {
case (algo, m) =>
m match {
case Unit => algo.trainBase(sc, pd)
case _ => m
}
}
models
} else {
logger.info("Using persisted model")
persistedModels
val models = if (persistedModels.exists(m => m.isInstanceOf[Unit.type])) {
// If any of persistedModels is Unit, we need to re-train the model.
logger.info("Some persisted models are Unit, need to re-train.")
val (dataSourceName, dataSourceParams) = engineParams.dataSourceParams
val dataSource =
Doer(dataSourceClassMap(dataSourceName), dataSourceParams)

val (preparatorName, preparatorParams) = engineParams.preparatorParams
val preparator =
Doer(preparatorClassMap(preparatorName), preparatorParams)

val td = dataSource.readTrainingBase(sc)
val pd = preparator.prepareBase(sc, td)

val models = algorithms.zip(persistedModels).map {
case (algo, m) =>
m match {
case Unit => algo.trainBase(sc, pd)
case _ => m
}
}
models
} else {
logger.info("Using persisted model")
persistedModels
}

models.zip(algorithms).zip(algoParamsList).zipWithIndex.map {
case (((model, algo), (algoName, algoParams)), ax) => {
model match {
case modelManifest: PersistentModelManifest => {
logger.info("Custom-persisted model detected for algorithm " +
algo.getClass.getName)
SparkWorkflowUtils.getPersistentModel(
modelManifest,
Seq(engineInstanceId, ax, algoName).mkString("-"),
algoParams,
Some(sc),
getClass.getClassLoader)
}
case m => {
try {
logger.info(
s"Loaded model ${m.getClass.getName} for algorithm " +
s"${algo.getClass.getName}")
sc.stop
m
} catch {
case e: NullPointerException =>
logger.warn(
s"Null model detected for algorithm ${algo.getClass.getName}")
m
}
}
} // model match
}
model match {
case modelManifest: PersistentModelManifest => {
logger.info("Custom-persisted model detected for algorithm " +
algo.getClass.getName)
SparkWorkflowUtils.getPersistentModel(
modelManifest,
Seq(engineInstanceId, ax, algoName).mkString("-"),
algoParams,
Some(sc),
getClass.getClassLoader)
}
case m => {
try {
logger.info(
s"Loaded model ${m.getClass.getName} for algorithm " +
s"${algo.getClass.getName}")
sc.stop
m
} catch {
case e: NullPointerException =>
logger.warn(
s"Null model detected for algorithm ${algo.getClass.getName}")
m
}
}
} // model match
}
}
}

Expand Down Expand Up @@ -319,25 +319,26 @@ class Engine[TD, EI, PD, Q, P, A](

val algorithms = algoParamsList.map {
case (algoName, algoParams) => {
try {
Doer(algorithmClassMap(algoName), algoParams)
} catch {
case e: NoSuchElementException => {
if (algoName == "") {
logger.error(
"Empty algorithm name supplied but it could not " +
"match with any algorithm in the engine's definition. " +
"Existing algorithm name(s) are: " +
s"${algorithmClassMap.keys.mkString(", ")}. Aborting.")
} else {
logger.error(s"$algoName cannot be found in the engine's " +
"definition. Existing algorithm name(s) are: " +
s"${algorithmClassMap.keys.mkString(", ")}. Aborting.")
}
sys.exit(1)
}
try {
Doer(algorithmClassMap(algoName), algoParams)
} catch {
case e: NoSuchElementException => {
if (algoName == "") {
logger.error(
"Empty algorithm name supplied but it could not " +
"match with any algorithm in the engine's definition. " +
"Existing algorithm name(s) are: " +
s"${algorithmClassMap.keys.mkString(", ")}. Aborting.")
} else {
logger.error(
s"$algoName cannot be found in the engine's " +
"definition. Existing algorithm name(s) are: " +
s"${algorithmClassMap.keys.mkString(", ")}. Aborting.")
}
sys.exit(1)
}
}
}
}

val (servingName, servingParams) = engineParams.servingParams
Expand Down Expand Up @@ -419,8 +420,9 @@ class Engine[TD, EI, PD, Q, P, A](
val (name, params) =
read[(String, JValue)](engineInstance.dataSourceParams)
if (!dataSourceClassMap.contains(name)) {
logger.error(s"Unable to find datasource class with name '$name'" +
" defined in Engine.")
logger.error(
s"Unable to find datasource class with name '$name'" +
" defined in Engine.")
sys.exit(1)
}
val extractedParams = WorkflowUtils.extractParams(
Expand All @@ -435,8 +437,9 @@ class Engine[TD, EI, PD, Q, P, A](
val (name, params) =
read[(String, JValue)](engineInstance.preparatorParams)
if (!preparatorClassMap.contains(name)) {
logger.error(s"Unable to find preparator class with name '$name'" +
" defined in Engine.")
logger.error(
s"Unable to find preparator class with name '$name'" +
" defined in Engine.")
sys.exit(1)
}
val extractedParams = WorkflowUtils.extractParams(
Expand All @@ -461,8 +464,9 @@ class Engine[TD, EI, PD, Q, P, A](
val servingParamsWithName: (String, Params) = {
val (name, params) = read[(String, JValue)](engineInstance.servingParams)
if (!servingClassMap.contains(name)) {
logger.error(s"Unable to find serving class with name '$name'" +
" defined in Engine.")
logger.error(
s"Unable to find serving class with name '$name'" +
" defined in Engine.")
sys.exit(1)
}
val extractedParams = WorkflowUtils.extractParams(
Expand Down Expand Up @@ -633,22 +637,24 @@ object Engine {
case e: StorageClientException =>
logger.error(
s"Error occured reading from data source. (Reason: " +
e.getMessage + ") Please see the log for debugging details.",
e.getMessage + ") Please see the log for debugging details.",
e)
sys.exit(1)
}

if (!params.skipSanityCheck) {
td match {
case sanityCheckable: SanityCheck => {
logger.info(s"${td.getClass.getName} supports data sanity" +
logger.info(
s"${td.getClass.getName} supports data sanity" +
" check. Performing check.")
sanityCheckable.sanityCheck()
}
sanityCheckable.sanityCheck()
}
case _ => {
logger.info(s"${td.getClass.getName} does not support" +
logger.info(
s"${td.getClass.getName} does not support" +
" data sanity check. Skipping check.")
}
}
}
}

Expand All @@ -662,14 +668,16 @@ object Engine {
if (!params.skipSanityCheck) {
pd match {
case sanityCheckable: SanityCheck => {
logger.info(s"${pd.getClass.getName} supports data sanity" +
logger.info(
s"${pd.getClass.getName} supports data sanity" +
" check. Performing check.")
sanityCheckable.sanityCheck()
}
sanityCheckable.sanityCheck()
}
case _ => {
logger.info(s"${pd.getClass.getName} does not support" +
logger.info(
s"${pd.getClass.getName} does not support" +
" data sanity check. Skipping check.")
}
}
}
}

Expand All @@ -685,14 +693,16 @@ object Engine {
{
model match {
case sanityCheckable: SanityCheck => {
logger.info(s"${model.getClass.getName} supports data sanity" +
logger.info(
s"${model.getClass.getName} supports data sanity" +
" check. Performing check.")
sanityCheckable.sanityCheck()
}
sanityCheckable.sanityCheck()
}
case _ => {
logger.info(s"${model.getClass.getName} does not support" +
logger.info(
s"${model.getClass.getName} does not support" +
" data sanity check. Skipping check.")
}
}
}
}
}
Expand Down Expand Up @@ -777,8 +787,8 @@ object Engine {
algo.batchPredictBase(sc, model, qs)
val predicts: RDD[(QX, (AX, P))] = rawPredicts.map {
case (qx, p) => {
(qx, (ax, p))
}
(qx, (ax, p))
}
}
predicts
}
Expand All @@ -800,18 +810,18 @@ object Engine {

val servingQPAMap: Map[EX, RDD[(Q, P, A)]] = algoPredictsMap.map {
case (ex, psMap) => {
// The query passed to serving.serve is the original one, not
// supplemented.
val qasMap: RDD[(QX, (Q, A))] = evalQAsMap(ex)
val qpsaMap: RDD[(QX, Q, Seq[P], A)] = psMap.join(qasMap).map {
case (qx, t) => (qx, t._2._1, t._1, t._2._2)
}
// The query passed to serving.serve is the original one, not
// supplemented.
val qasMap: RDD[(QX, (Q, A))] = evalQAsMap(ex)
val qpsaMap: RDD[(QX, Q, Seq[P], A)] = psMap.join(qasMap).map {
case (qx, t) => (qx, t._2._1, t._1, t._2._2)
}

val qpaMap: RDD[(Q, P, A)] = qpsaMap.map {
case (qx, q, ps, a) => (q, serving.serveBase(q, ps), a)
}
(ex, qpaMap)
val qpaMap: RDD[(Q, P, A)] = qpsaMap.map {
case (qx, q, ps, a) => (q, serving.serveBase(q, ps), a)
}
(ex, qpaMap)
}
}

(0 until evalCount).map { ex =>
Expand Down
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