Merge pull request #4 from ancasarb/update_mleap_version

update mleap dependency version with 0.13.0

Author: orchidmajumder

.gitignore

@@ -0,0 +1,4 @@
+/.idea
+.idea/
+target/
+*.iml

CHANGELOG.md

@@ -1,4 +1,9 @@
 2.2
 ===
 
-Initial release of sagemaker-sparkml-serving-container, supporting Spark major version 2.2.
+Initial release of sagemaker-sparkml-serving-container, supporting Spark major version 2.2.
+
+2.3
+===
+
+Release of sagemaker-sparkml-serving-container, supporting Spark major version 2.3.

Dockerfile

@@ -9,7 +9,7 @@ WORKDIR /sagemaker-sparkml-model-server
 
 RUN mvn clean package
 
-RUN cp ./target/sparkml-serving-2.2.jar /usr/local/lib/sparkml-serving-2.2.jar
+RUN cp ./target/sparkml-serving-2.3.jar /usr/local/lib/sparkml-serving-2.3.jar
 RUN cp ./serve.sh /usr/local/bin/serve.sh
 
 RUN chmod a+x /usr/local/bin/serve.sh

README.md

@@ -22,7 +22,7 @@ SageMaker SparkML Serving Container is primarily built on the underlying Spring
 Supported Spark/MLeap version
 =============================
 
-Currently SageMaker SparkML Serving is powered by MLeap 0.9.6 and it is tested with Spark major version - 2.2.
+Currently SageMaker SparkML Serving is powered by MLeap 0.13.0 and it is tested with Spark major version - 2.3.
 
 Table of Contents
 =================

ci/buildspec.yml

@@ -9,10 +9,10 @@ phases:
     commands:
     - echo Build started on `date`
     - echo Building the Docker image...
-    - docker build -t sagemaker-sparkml-serving:2.2 .
-    - docker tag sagemaker-sparkml-serving:2.2 515193369038.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:2.2
+    - docker build -t sagemaker-sparkml-serving:2.3 .
+    - docker tag sagemaker-sparkml-serving:2.3 515193369038.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:2.3
   post_build:
     commands:
     - echo Build completed on `date`
     - echo Pushing the Docker image...
-    - docker push 515193369038.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:2.2
+    - docker push 515193369038.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:2.3

pom.xml

@@ -24,7 +24,7 @@
   <modelVersion>4.0.0</modelVersion>
   <groupId>org.amazonaws.sagemaker</groupId>
   <artifactId>sparkml-serving</artifactId>
-  <version>2.2</version>
+  <version>2.3</version>
   <build>
     <plugins>
       <plugin>
@@ -154,7 +154,7 @@
     <dependency>
       <groupId>ml.combust.mleap</groupId>
       <artifactId>mleap-runtime_2.11</artifactId>
-      <version>0.9.6</version>
+      <version>0.13.0</version>
     </dependency>
     <dependency>
       <groupId>org.apache.commons</groupId>

serve.sh

@@ -1,3 +1,3 @@
 #!/bin/bash
 # This is needed to make sure Java correctly detects CPU/Memory set by the container limits
-java -XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap -jar /usr/local/lib/sparkml-serving-2.2.jar
+java -XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap -jar /usr/local/lib/sparkml-serving-2.3.jar

src/main/java/com/amazonaws/sagemaker/controller/ServingController.java

@@ -94,7 +94,7 @@ public ResponseEntity performShallowHealthCheck() {
     public ResponseEntity returnBatchExecutionParameter() throws JsonProcessingException {
         final BatchExecutionParameter batchParam = new BatchExecutionParameter(SystemUtils.getNumberOfThreads(1),
             "SINGLE_RECORD", 5);
-        final String responseStr = new ObjectMapper().writeValueAsString(batchParam);
+        final String responseStr = mapper.writeValueAsString(batchParam);
         return ResponseEntity.ok(responseStr);
     }
 

src/main/java/com/amazonaws/sagemaker/utils/ScalaUtils.java

@@ -23,16 +23,18 @@
 import ml.combust.mleap.runtime.frame.DefaultLeapFrame;
 import ml.combust.mleap.runtime.frame.Row;
 import ml.combust.mleap.runtime.frame.Transformer;
+import ml.combust.mleap.runtime.javadsl.LeapFrameSupport;
 import org.apache.commons.lang3.StringUtils;
 import scala.collection.JavaConverters;
-import scala.collection.Seq;
 
 /**
  * Utility class for dealing with Scala to Java conversion related issues. These functionalities are moved to this
  * class so that they can be easily mocked out by PowerMockito.mockStatic while testing the actual classes.
  */
 public class ScalaUtils {
 
+    private final static LeapFrameSupport leapFrameSupport = new LeapFrameSupport();
+
     /**
      * Invokes MLeap transformer object with DefaultLeapFrame and returns DefaultLeapFrame from MLeap helper Try Monad
      *
@@ -53,9 +55,7 @@ public static DefaultLeapFrame transformLeapFrame(final Transformer transformer,
      * @return the DefaultLeapFrame in helper
      */
     public static DefaultLeapFrame selectFromLeapFrame(final DefaultLeapFrame leapFrame, final String key) {
-        final Seq<String> predictionColumnSelectionArgs = JavaConverters
-            .asScalaIteratorConverter(Collections.singletonList(key).iterator()).asScala().toSeq();
-        return leapFrame.select(predictionColumnSelectionArgs).get();
+        return leapFrameSupport.select(leapFrame, Collections.singletonList(key));
     }
 
     /**
@@ -66,8 +66,7 @@ public static DefaultLeapFrame selectFromLeapFrame(final DefaultLeapFrame leapFr
      * @return ArrayRow which can be used to retrieve the original output
      */
     public static ArrayRow getOutputArrayRow(final DefaultLeapFrame leapFrame) {
-        final Iterator<Row> rowIterator = JavaConverters.asJavaIterableConverter(leapFrame.collect()).asJava()
-            .iterator();
+        final Iterator<Row> rowIterator = leapFrameSupport.collect(leapFrame).iterator();
         // SageMaker input structure only allows to call MLeap transformer for single data point
         return (ArrayRow) (rowIterator.next());
     }