diff --git a/src/main/java/org/apache/sysds/runtime/instructions/spark/MultiReturnParameterizedBuiltinSPInstruction.java b/src/main/java/org/apache/sysds/runtime/instructions/spark/MultiReturnParameterizedBuiltinSPInstruction.java
index df5f16b..5dd7b7f 100644
--- a/src/main/java/org/apache/sysds/runtime/instructions/spark/MultiReturnParameterizedBuiltinSPInstruction.java
+++ b/src/main/java/org/apache/sysds/runtime/instructions/spark/MultiReturnParameterizedBuiltinSPInstruction.java
@@ -254,9 +254,11 @@
 			throws Exception 
 		{
 			//build meta data (e.g., recode maps)
-			if( _raEncoder != null )
+			if( _raEncoder != null ) {
+				_raEncoder.prepareBuildPartial();
 				while( iter.hasNext() )
 					_raEncoder.buildPartial(iter.next()._2());
+			}
 			
 			//output recode maps as columnID - token pairs
 			ArrayList<Tuple2<Integer,Object>> ret = new ArrayList<>();
diff --git a/src/main/java/org/apache/sysds/runtime/transform/encode/EncoderRecode.java b/src/main/java/org/apache/sysds/runtime/transform/encode/EncoderRecode.java
index e195835..d8d524a 100644
--- a/src/main/java/org/apache/sysds/runtime/transform/encode/EncoderRecode.java
+++ b/src/main/java/org/apache/sysds/runtime/transform/encode/EncoderRecode.java
@@ -121,14 +121,16 @@
 	protected void putCode(HashMap<String,Long> map, String key) {
 		map.put(key, Long.valueOf(map.size()+1));
 	}
+	
+	public void prepareBuildPartial() {
+		//ensure allocated partial recode map
+		if( _rcdMapsPart == null )
+			_rcdMapsPart = new HashMap<>();
+	}
 
 	public void buildPartial(FrameBlock in) {
 		if( !isApplicable() )
 			return;
-
-		//ensure allocated partial recode map
-		if( _rcdMapsPart == null )
-			_rcdMapsPart = new HashMap<>();
 		
 		//construct partial recode map (tokens w/o codes)
 		//iterate over columns for sequential access
diff --git a/src/test/java/org/apache/sysds/test/functions/builtin/BuiltinMiceTest.java b/src/test/java/org/apache/sysds/test/functions/builtin/BuiltinMiceTest.java
index a647918..ab76824 100644
--- a/src/test/java/org/apache/sysds/test/functions/builtin/BuiltinMiceTest.java
+++ b/src/test/java/org/apache/sysds/test/functions/builtin/BuiltinMiceTest.java
@@ -51,42 +51,34 @@
 		runMiceNominalTest(mask, 1, false, LopProperties.ExecType.CP);
 	}
 
-//	@Test
-//	public void testMiceMixSpark() {
-//		double[][] mask = {{ 0.0, 0.0, 1.0, 1.0, 0.0}};
-//		runMiceNominalTest(mask, 1, LopProperties.ExecType.SPARK);
-//	}
-
 	@Test
 	public void testMiceNumberCP() {
 		double[][] mask = {{ 0.0, 0.0, 0.0, 0.0, 0.0}};
 		runMiceNominalTest(mask, 2, false, LopProperties.ExecType.CP);
 	}
 
-//	@Test
-//	public void testMiceNumberSpark() {
-//		double[][] mask = {{ 0.0, 0.0, 0.0, 0.0, 0.0}};
-//		runMiceNominalTest(mask, 2, LopProperties.ExecType.SPARK);
-//	}
-
 	@Test
 	public void testMiceCategoricalCP() {
 		double[][] mask = {{ 1.0, 1.0, 1.0, 1.0, 1.0}};
 		runMiceNominalTest(mask, 3, false, LopProperties.ExecType.CP);
 	}
 
-//	@Test
-//	public void testMiceCategoricalSpark() {
-//		double[][] mask = {{ 1.0, 1.0, 1.0, 1.0, 1.0}};
-//		runMiceNominalTest(mask, 3, LopProperties.ExecType.SPARK);
-//	}
-
 	@Test
 	public void testMiceMixLineageReuseCP() {
 		double[][] mask = {{ 0.0, 0.0, 1.0, 1.0, 0.0}};
 		runMiceNominalTest(mask, 1, true, LopProperties.ExecType.CP);
 	}
 
+	//added a single, relatively-fast spark test, others seem infeasible
+	//as forcing every operation to spark takes too long for complex,
+	//composite builtins like mice.
+
+	@Test
+	public void testMiceNumberSpark() {
+		double[][] mask = {{ 0.0, 0.0, 0.0, 0.0, 0.0}};
+		runMiceNominalTest(mask, 2, false, LopProperties.ExecType.SPARK);
+	}
+	
 	private void runMiceNominalTest(double[][] mask, int testType, boolean lineage, LopProperties.ExecType instType) {
 		Types.ExecMode platformOld = setExecMode(instType);
 		try {
@@ -94,10 +86,10 @@
 			String HOME = SCRIPT_DIR + TEST_DIR;
 			fullDMLScriptName = HOME + TEST_NAME + ".dml";
 			programArgs = new String[]{"-nvargs", "X=" + DATASET, "Mask="+input("M"), 
-					"iteration=" + iter, "dataN=" + output("N"), "dataC=" + output("C")};
+				"iteration=" + iter, "dataN=" + output("N"), "dataC=" + output("C")};
 			if (lineage) {
-				String[] lin = new String[] {"-stats","-lineage", ReuseCacheType.REUSE_HYBRID.name().toLowerCase()};
-				programArgs = (String[]) ArrayUtils.addAll(programArgs, lin);
+				programArgs = (String[]) ArrayUtils.addAll(programArgs, new String[] {
+					"-stats","-lineage", ReuseCacheType.REUSE_HYBRID.name().toLowerCase()});
 			}
 			writeInputMatrixWithMTD("M", mask, true);
 
@@ -125,18 +117,16 @@
 		}
 	}
 
-	private void testNumericOutput()
-	{
+	private void testNumericOutput() {
 		//compare matrices
 		HashMap<MatrixValue.CellIndex, Double> dmlfileN = readDMLMatrixFromHDFS("N");
 		HashMap<MatrixValue.CellIndex, Double> rfileN  = readRMatrixFromFS("N");
 
 		// compare numerical imputations
 		TestUtils.compareMatrices(dmlfileN, rfileN, eps, "Stat-DML", "Stat-R");
-
 	}
-	private void testCategoricalOutput()
-	{
+
+	private void testCategoricalOutput() {
 		HashMap<MatrixValue.CellIndex, Double> dmlfileC = readDMLMatrixFromHDFS("C");
 		HashMap<MatrixValue.CellIndex, Double> rfileC  = readRMatrixFromFS("C");
 
@@ -154,4 +144,4 @@
 		else
 			Assert.fail("categorical test fails, the true value count is less than 98%");
 	}
-}
\ No newline at end of file
+}