[jira] [Work logged] (BEAM-7587) Spark portable runner: Streaming mode

[ASF GitHub Bot (Jira)]

     [ 
https://issues.apache.org/jira/browse/BEAM-7587?focusedWorklogId=473187&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-473187
 ]

ASF GitHub Bot logged work on BEAM-7587:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 21/Aug/20 03:48
            Start Date: 21/Aug/20 03:48
    Worklog Time Spent: 10m 
      Work Description: robertwb commented on a change in pull request #12157:
URL: https://github.com/apache/beam/pull/12157#discussion_r474389484



##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =
+        context.getStreamingContext().queueStream(rddQueue, true /* oneAtATime 
*/);
+
+    UnboundedDataset<byte[]> output =
+        new UnboundedDataset<>(
+            emptyStream, 
Collections.singletonList(emptyStream.inputDStream().id()));
+
+    // Add watermark to holder and advance to infinity to ensure future 
watermarks can be updated
+    GlobalWatermarkHolder.SparkWatermarks sparkWatermark =
+        new GlobalWatermarkHolder.SparkWatermarks(
+            GlobalWindow.INSTANCE.maxTimestamp(),
+            BoundedWindow.TIMESTAMP_MAX_VALUE,
+            context.getFirstTimestamp());
+    GlobalWatermarkHolder.add(output.getStreamSources().get(0), 
sparkWatermark);
+
+    context.pushDataset(getOutputId(transformNode), output);
+  }
+
+  private static <K, V> void translateGroupByKey(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.Components components = pipeline.getComponents();
+    String inputId = getInputId(transformNode);
+    UnboundedDataset<KV<K, V>> inputDataset =
+        (UnboundedDataset<KV<K, V>>) context.popDataset(inputId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<KV<K, V>>> dStream = inputDataset.getDStream();
+    WindowedValue.WindowedValueCoder<KV<K, V>> inputCoder =
+        getWindowedValueCoder(inputId, components);
+    KvCoder<K, V> inputKvCoder = (KvCoder<K, V>) inputCoder.getValueCoder();
+    Coder<K> inputKeyCoder = inputKvCoder.getKeyCoder();
+    Coder<V> inputValueCoder = inputKvCoder.getValueCoder();
+    final WindowingStrategy windowingStrategy = getWindowingStrategy(inputId, 
components);

Review comment:
       Be consistent on what's declared final vs. what's not. 

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =
+        context.getStreamingContext().queueStream(rddQueue, true /* oneAtATime 
*/);
+
+    UnboundedDataset<byte[]> output =
+        new UnboundedDataset<>(
+            emptyStream, 
Collections.singletonList(emptyStream.inputDStream().id()));
+
+    // Add watermark to holder and advance to infinity to ensure future 
watermarks can be updated
+    GlobalWatermarkHolder.SparkWatermarks sparkWatermark =
+        new GlobalWatermarkHolder.SparkWatermarks(
+            GlobalWindow.INSTANCE.maxTimestamp(),
+            BoundedWindow.TIMESTAMP_MAX_VALUE,
+            context.getFirstTimestamp());
+    GlobalWatermarkHolder.add(output.getStreamSources().get(0), 
sparkWatermark);
+
+    context.pushDataset(getOutputId(transformNode), output);
+  }
+
+  private static <K, V> void translateGroupByKey(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.Components components = pipeline.getComponents();
+    String inputId = getInputId(transformNode);
+    UnboundedDataset<KV<K, V>> inputDataset =
+        (UnboundedDataset<KV<K, V>>) context.popDataset(inputId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<KV<K, V>>> dStream = inputDataset.getDStream();
+    WindowedValue.WindowedValueCoder<KV<K, V>> inputCoder =
+        getWindowedValueCoder(inputId, components);
+    KvCoder<K, V> inputKvCoder = (KvCoder<K, V>) inputCoder.getValueCoder();
+    Coder<K> inputKeyCoder = inputKvCoder.getKeyCoder();
+    Coder<V> inputValueCoder = inputKvCoder.getValueCoder();
+    final WindowingStrategy windowingStrategy = getWindowingStrategy(inputId, 
components);
+    final WindowFn<Object, BoundedWindow> windowFn = 
windowingStrategy.getWindowFn();
+    final WindowedValue.WindowedValueCoder<V> wvCoder =
+        WindowedValue.FullWindowedValueCoder.of(inputValueCoder, 
windowFn.windowCoder());
+
+    JavaDStream<WindowedValue<KV<K, Iterable<V>>>> outStream =
+        SparkGroupAlsoByWindowViaWindowSet.groupByKeyAndWindow(
+            dStream,
+            inputKeyCoder,
+            wvCoder,
+            windowingStrategy,
+            context.getSerializableOptions(),
+            streamSources,
+            transformNode.getId());
+
+    context.pushDataset(
+        getOutputId(transformNode), new UnboundedDataset<>(outStream, 
streamSources));
+  }
+
+  private static <InputT, OutputT, SideInputT> void translateExecutableStage(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.ExecutableStagePayload stagePayload;
+    try {
+      stagePayload =
+          RunnerApi.ExecutableStagePayload.parseFrom(
+              transformNode.getTransform().getSpec().getPayload());
+    } catch (IOException e) {
+      throw new RuntimeException(e);
+    }
+
+    String inputPCollectionId = stagePayload.getInput();
+    UnboundedDataset<InputT> inputDataset =
+        (UnboundedDataset<InputT>) context.popDataset(inputPCollectionId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<InputT>> inputDStream = 
inputDataset.getDStream();
+    Map<String, String> outputs = transformNode.getTransform().getOutputsMap();
+    BiMap<String, Integer> outputMap = createOutputMap(outputs.values());
+
+    RunnerApi.Components components = pipeline.getComponents();
+    Coder windowCoder =
+        getWindowingStrategy(inputPCollectionId, 
components).getWindowFn().windowCoder();
+
+    // TODO (BEAM-10712): handle side inputs.
+    ImmutableMap<
+            String, Tuple2<Broadcast<List<byte[]>>, 
WindowedValue.WindowedValueCoder<SideInputT>>>
+        broadcastVariables = ImmutableMap.copyOf(new HashMap<>());
+
+    SparkExecutableStageFunction<InputT, SideInputT> function =
+        new SparkExecutableStageFunction<>(
+            stagePayload,
+            context.jobInfo,
+            outputMap,
+            SparkExecutableStageContextFactory.getInstance(),
+            broadcastVariables,
+            MetricsAccumulator.getInstance(),
+            windowCoder);
+    JavaDStream<RawUnionValue> staged = inputDStream.mapPartitions(function);
+
+    String intermediateId = getExecutableStageIntermediateId(transformNode);
+    context.pushDataset(
+        intermediateId,
+        new Dataset() {
+          @Override
+          public void cache(String storageLevel, Coder<?> coder) {
+            StorageLevel level = StorageLevel.fromString(storageLevel);
+            staged.persist(level);
+          }
+
+          @Override
+          public void action() {
+            // Empty function to force computation of RDD.
+            staged.foreachRDD(TranslationUtils.emptyVoidFunction());
+          }
+
+          @Override
+          public void setName(String name) {
+            // ignore
+          }
+        });
+    // pop dataset to mark DStream as used
+    context.popDataset(intermediateId);
+
+    for (String outputId : outputs.values()) {
+      JavaDStream<WindowedValue<OutputT>> outStream =
+          staged.flatMap(new 
SparkExecutableStageExtractionFunction<>(outputMap.get(outputId)));
+      context.pushDataset(outputId, new UnboundedDataset<>(outStream, 
streamSources));
+    }
+
+    if (outputs.isEmpty()) {
+      // Add sink to ensure all outputs are computed

Review comment:
       In this case there are no outputs (per the above line). Perhaps just say 
something to the effect that we want to ensure the stage is executed. 

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =

Review comment:
       This stream isn't empty, is it? 

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =
+        context.getStreamingContext().queueStream(rddQueue, true /* oneAtATime 
*/);
+
+    UnboundedDataset<byte[]> output =
+        new UnboundedDataset<>(
+            emptyStream, 
Collections.singletonList(emptyStream.inputDStream().id()));
+
+    // Add watermark to holder and advance to infinity to ensure future 
watermarks can be updated
+    GlobalWatermarkHolder.SparkWatermarks sparkWatermark =
+        new GlobalWatermarkHolder.SparkWatermarks(
+            GlobalWindow.INSTANCE.maxTimestamp(),
+            BoundedWindow.TIMESTAMP_MAX_VALUE,
+            context.getFirstTimestamp());
+    GlobalWatermarkHolder.add(output.getStreamSources().get(0), 
sparkWatermark);
+
+    context.pushDataset(getOutputId(transformNode), output);
+  }
+
+  private static <K, V> void translateGroupByKey(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.Components components = pipeline.getComponents();
+    String inputId = getInputId(transformNode);
+    UnboundedDataset<KV<K, V>> inputDataset =
+        (UnboundedDataset<KV<K, V>>) context.popDataset(inputId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<KV<K, V>>> dStream = inputDataset.getDStream();
+    WindowedValue.WindowedValueCoder<KV<K, V>> inputCoder =
+        getWindowedValueCoder(inputId, components);
+    KvCoder<K, V> inputKvCoder = (KvCoder<K, V>) inputCoder.getValueCoder();
+    Coder<K> inputKeyCoder = inputKvCoder.getKeyCoder();
+    Coder<V> inputValueCoder = inputKvCoder.getValueCoder();
+    final WindowingStrategy windowingStrategy = getWindowingStrategy(inputId, 
components);
+    final WindowFn<Object, BoundedWindow> windowFn = 
windowingStrategy.getWindowFn();
+    final WindowedValue.WindowedValueCoder<V> wvCoder =
+        WindowedValue.FullWindowedValueCoder.of(inputValueCoder, 
windowFn.windowCoder());
+
+    JavaDStream<WindowedValue<KV<K, Iterable<V>>>> outStream =
+        SparkGroupAlsoByWindowViaWindowSet.groupByKeyAndWindow(
+            dStream,
+            inputKeyCoder,
+            wvCoder,
+            windowingStrategy,
+            context.getSerializableOptions(),
+            streamSources,
+            transformNode.getId());
+
+    context.pushDataset(
+        getOutputId(transformNode), new UnboundedDataset<>(outStream, 
streamSources));
+  }
+
+  private static <InputT, OutputT, SideInputT> void translateExecutableStage(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.ExecutableStagePayload stagePayload;
+    try {
+      stagePayload =
+          RunnerApi.ExecutableStagePayload.parseFrom(
+              transformNode.getTransform().getSpec().getPayload());
+    } catch (IOException e) {
+      throw new RuntimeException(e);
+    }
+
+    String inputPCollectionId = stagePayload.getInput();
+    UnboundedDataset<InputT> inputDataset =
+        (UnboundedDataset<InputT>) context.popDataset(inputPCollectionId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<InputT>> inputDStream = 
inputDataset.getDStream();

Review comment:
       Nit: I'm noticing the pattern of assigning a huge number of locals at 
the top of a function and then only using them once below. Often (not always) 
the code would be more concise if the declarations were used inline (e.g. use 
`inputDataset.getDStream()` rather than assign to an intermediate 
`inputDStream`). 

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =
+        context.getStreamingContext().queueStream(rddQueue, true /* oneAtATime 
*/);
+
+    UnboundedDataset<byte[]> output =
+        new UnboundedDataset<>(
+            emptyStream, 
Collections.singletonList(emptyStream.inputDStream().id()));
+
+    // Add watermark to holder and advance to infinity to ensure future 
watermarks can be updated
+    GlobalWatermarkHolder.SparkWatermarks sparkWatermark =
+        new GlobalWatermarkHolder.SparkWatermarks(
+            GlobalWindow.INSTANCE.maxTimestamp(),
+            BoundedWindow.TIMESTAMP_MAX_VALUE,
+            context.getFirstTimestamp());
+    GlobalWatermarkHolder.add(output.getStreamSources().get(0), 
sparkWatermark);
+
+    context.pushDataset(getOutputId(transformNode), output);
+  }
+
+  private static <K, V> void translateGroupByKey(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.Components components = pipeline.getComponents();
+    String inputId = getInputId(transformNode);
+    UnboundedDataset<KV<K, V>> inputDataset =
+        (UnboundedDataset<KV<K, V>>) context.popDataset(inputId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<KV<K, V>>> dStream = inputDataset.getDStream();
+    WindowedValue.WindowedValueCoder<KV<K, V>> inputCoder =
+        getWindowedValueCoder(inputId, components);
+    KvCoder<K, V> inputKvCoder = (KvCoder<K, V>) inputCoder.getValueCoder();
+    Coder<K> inputKeyCoder = inputKvCoder.getKeyCoder();
+    Coder<V> inputValueCoder = inputKvCoder.getValueCoder();
+    final WindowingStrategy windowingStrategy = getWindowingStrategy(inputId, 
components);
+    final WindowFn<Object, BoundedWindow> windowFn = 
windowingStrategy.getWindowFn();
+    final WindowedValue.WindowedValueCoder<V> wvCoder =
+        WindowedValue.FullWindowedValueCoder.of(inputValueCoder, 
windowFn.windowCoder());
+
+    JavaDStream<WindowedValue<KV<K, Iterable<V>>>> outStream =
+        SparkGroupAlsoByWindowViaWindowSet.groupByKeyAndWindow(
+            dStream,
+            inputKeyCoder,
+            wvCoder,
+            windowingStrategy,
+            context.getSerializableOptions(),
+            streamSources,
+            transformNode.getId());
+
+    context.pushDataset(
+        getOutputId(transformNode), new UnboundedDataset<>(outStream, 
streamSources));
+  }
+
+  private static <InputT, OutputT, SideInputT> void translateExecutableStage(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.ExecutableStagePayload stagePayload;
+    try {
+      stagePayload =
+          RunnerApi.ExecutableStagePayload.parseFrom(
+              transformNode.getTransform().getSpec().getPayload());
+    } catch (IOException e) {
+      throw new RuntimeException(e);
+    }
+
+    String inputPCollectionId = stagePayload.getInput();
+    UnboundedDataset<InputT> inputDataset =
+        (UnboundedDataset<InputT>) context.popDataset(inputPCollectionId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<InputT>> inputDStream = 
inputDataset.getDStream();
+    Map<String, String> outputs = transformNode.getTransform().getOutputsMap();
+    BiMap<String, Integer> outputMap = createOutputMap(outputs.values());
+
+    RunnerApi.Components components = pipeline.getComponents();
+    Coder windowCoder =
+        getWindowingStrategy(inputPCollectionId, 
components).getWindowFn().windowCoder();
+
+    // TODO (BEAM-10712): handle side inputs.
+    ImmutableMap<
+            String, Tuple2<Broadcast<List<byte[]>>, 
WindowedValue.WindowedValueCoder<SideInputT>>>
+        broadcastVariables = ImmutableMap.copyOf(new HashMap<>());
+
+    SparkExecutableStageFunction<InputT, SideInputT> function =
+        new SparkExecutableStageFunction<>(
+            stagePayload,
+            context.jobInfo,
+            outputMap,
+            SparkExecutableStageContextFactory.getInstance(),
+            broadcastVariables,
+            MetricsAccumulator.getInstance(),
+            windowCoder);
+    JavaDStream<RawUnionValue> staged = inputDStream.mapPartitions(function);
+
+    String intermediateId = getExecutableStageIntermediateId(transformNode);
+    context.pushDataset(
+        intermediateId,
+        new Dataset() {
+          @Override
+          public void cache(String storageLevel, Coder<?> coder) {
+            StorageLevel level = StorageLevel.fromString(storageLevel);
+            staged.persist(level);
+          }
+
+          @Override
+          public void action() {
+            // Empty function to force computation of RDD.
+            staged.foreachRDD(TranslationUtils.emptyVoidFunction());
+          }
+
+          @Override
+          public void setName(String name) {
+            // ignore
+          }
+        });
+    // pop dataset to mark DStream as used
+    context.popDataset(intermediateId);
+
+    for (String outputId : outputs.values()) {
+      JavaDStream<WindowedValue<OutputT>> outStream =
+          staged.flatMap(new 
SparkExecutableStageExtractionFunction<>(outputMap.get(outputId)));
+      context.pushDataset(outputId, new UnboundedDataset<>(outStream, 
streamSources));
+    }
+
+    if (outputs.isEmpty()) {
+      // Add sink to ensure all outputs are computed
+      JavaDStream<WindowedValue<OutputT>> outStream =
+          staged.flatMap((rawUnionValue) -> Collections.emptyIterator());
+      context.pushDataset(
+          String.format("EmptyOutputSink_%d", context.nextSinkId()),
+          new UnboundedDataset<>(outStream, streamSources));
+    }
+  }
+
+  private static <T> void translateFlatten(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    Map<String, String> inputsMap = 
transformNode.getTransform().getInputsMap();
+    JavaDStream<WindowedValue<T>> unifiedStreams;
+    final List<Integer> streamSources = new ArrayList<>();
+
+    if (inputsMap.isEmpty()) {
+      Queue<JavaRDD<WindowedValue<T>>> q = new LinkedBlockingQueue<>();
+      q.offer(context.getSparkContext().emptyRDD());
+      unifiedStreams = context.getStreamingContext().queueStream(q);
+    } else {
+      final List<JavaDStream<WindowedValue<T>>> dStreams = new ArrayList<>();
+      for (String inputId : inputsMap.values()) {
+        Dataset dataset = context.popDataset(inputId);
+        if (dataset instanceof UnboundedDataset) {
+          UnboundedDataset<T> unboundedDataset = (UnboundedDataset<T>) dataset;
+          streamSources.addAll(unboundedDataset.getStreamSources());
+          dStreams.add(unboundedDataset.getDStream());
+        } else {
+          // create a single RDD stream.
+          Queue<JavaRDD<WindowedValue<T>>> q = new LinkedBlockingQueue<>();
+          q.offer(((BoundedDataset) dataset).getRDD());
+          // TODO: this is not recoverable from checkpoint!

Review comment:
       File and reference a JIRA. 

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))

Review comment:
       You could even defer the singleton iterable wrapping to here and use 
`windowCoder.encode(...)` rather than use `CoderHelpers.toByteArrays`.

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =
+        context.getStreamingContext().queueStream(rddQueue, true /* oneAtATime 
*/);
+
+    UnboundedDataset<byte[]> output =
+        new UnboundedDataset<>(
+            emptyStream, 
Collections.singletonList(emptyStream.inputDStream().id()));
+
+    // Add watermark to holder and advance to infinity to ensure future 
watermarks can be updated
+    GlobalWatermarkHolder.SparkWatermarks sparkWatermark =
+        new GlobalWatermarkHolder.SparkWatermarks(
+            GlobalWindow.INSTANCE.maxTimestamp(),
+            BoundedWindow.TIMESTAMP_MAX_VALUE,
+            context.getFirstTimestamp());
+    GlobalWatermarkHolder.add(output.getStreamSources().get(0), 
sparkWatermark);

Review comment:
       I have to admit I'm a bit fuzzy on how this holds back (or doesn't) the 
watermark. 

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =

Review comment:
       It seems it'd be easier construct this with
   
   ```
   Collections.singletonList(
       WindowedValue.of(...));
   ```
   
   rather than use an intermediate timestamped value list.

##########
File path: 
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkStreamingPortablePipelineTranslator.java
##########
@@ -0,0 +1,366 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.spark.translation;
+
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.createOutputMap;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getExecutableStageIntermediateId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getInputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getOutputId;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowedValueCoder;
+import static 
org.apache.beam.runners.fnexecution.translation.PipelineTranslatorUtils.getWindowingStrategy;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Queue;
+import java.util.Set;
+import java.util.concurrent.LinkedBlockingQueue;
+import java.util.stream.Collectors;
+import java.util.stream.StreamSupport;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import 
org.apache.beam.runners.core.construction.graph.PipelineNode.PTransformNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.fnexecution.provisioning.JobInfo;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.coders.CoderHelpers;
+import org.apache.beam.runners.spark.metrics.MetricsAccumulator;
+import 
org.apache.beam.runners.spark.stateful.SparkGroupAlsoByWindowViaWindowSet;
+import org.apache.beam.runners.spark.translation.streaming.UnboundedDataset;
+import org.apache.beam.runners.spark.util.GlobalWatermarkHolder;
+import org.apache.beam.runners.spark.util.SparkCompat;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.PaneInfo;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.BiMap;
+import 
org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.storage.StorageLevel;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaInputDStream;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import scala.Tuple2;
+
+/** Translates an unbounded portable pipeline into a Spark job. */
+public class SparkStreamingPortablePipelineTranslator
+    implements 
SparkPortablePipelineTranslator<SparkStreamingTranslationContext> {
+
+  private static final Logger LOG =
+      LoggerFactory.getLogger(SparkStreamingPortablePipelineTranslator.class);
+
+  private final ImmutableMap<String, PTransformTranslator> 
urnToTransformTranslator;
+
+  interface PTransformTranslator {
+
+    /** Translates transformNode from Beam into the Spark context. */
+    void translate(
+        PTransformNode transformNode,
+        RunnerApi.Pipeline pipeline,
+        SparkStreamingTranslationContext context);
+  }
+
+  @Override
+  public Set<String> knownUrns() {
+    return urnToTransformTranslator.keySet();
+  }
+
+  public SparkStreamingPortablePipelineTranslator() {
+    ImmutableMap.Builder<String, PTransformTranslator> translatorMap = 
ImmutableMap.builder();
+    translatorMap.put(
+        PTransformTranslation.IMPULSE_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateImpulse);
+    translatorMap.put(
+        PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateGroupByKey);
+    translatorMap.put(
+        ExecutableStage.URN, 
SparkStreamingPortablePipelineTranslator::translateExecutableStage);
+    translatorMap.put(
+        PTransformTranslation.FLATTEN_TRANSFORM_URN,
+        SparkStreamingPortablePipelineTranslator::translateFlatten);
+    translatorMap.put(
+        PTransformTranslation.RESHUFFLE_URN,
+        SparkStreamingPortablePipelineTranslator::translateReshuffle);
+    this.urnToTransformTranslator = translatorMap.build();
+  }
+
+  /** Translates pipeline from Beam into the Spark context. */
+  @Override
+  public void translate(
+      final RunnerApi.Pipeline pipeline, SparkStreamingTranslationContext 
context) {
+    QueryablePipeline p =
+        QueryablePipeline.forTransforms(
+            pipeline.getRootTransformIdsList(), pipeline.getComponents());
+    for (PipelineNode.PTransformNode transformNode : 
p.getTopologicallyOrderedTransforms()) {
+      urnToTransformTranslator
+          .getOrDefault(
+              transformNode.getTransform().getSpec().getUrn(),
+              SparkStreamingPortablePipelineTranslator::urnNotFound)
+          .translate(transformNode, pipeline, context);
+    }
+  }
+
+  private static void urnNotFound(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    throw new IllegalArgumentException(
+        String.format(
+            "Transform %s has unknown URN %s",
+            transformNode.getId(), 
transformNode.getTransform().getSpec().getUrn()));
+  }
+
+  private static void translateImpulse(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+
+    TimestampedValue<byte[]> tsValue = TimestampedValue.atMinimumTimestamp(new 
byte[0]);
+    Iterable<TimestampedValue<byte[]>> timestampedValues = 
Collections.singletonList(tsValue);
+    Iterable<WindowedValue<byte[]>> windowedValues =
+        StreamSupport.stream(timestampedValues.spliterator(), false)
+            .map(
+                timestampedValue ->
+                    WindowedValue.of(
+                        timestampedValue.getValue(),
+                        timestampedValue.getTimestamp(),
+                        GlobalWindow.INSTANCE,
+                        PaneInfo.NO_FIRING))
+            .collect(Collectors.toList());
+
+    ByteArrayCoder coder = ByteArrayCoder.of();
+    WindowedValue.FullWindowedValueCoder<byte[]> windowCoder =
+        WindowedValue.FullWindowedValueCoder.of(coder, 
GlobalWindow.Coder.INSTANCE);
+    JavaRDD<WindowedValue<byte[]>> emptyByteArrayRDD =
+        context
+            .getSparkContext()
+            .parallelize(CoderHelpers.toByteArrays(windowedValues, 
windowCoder))
+            .map(CoderHelpers.fromByteFunction(windowCoder));
+
+    Queue<JavaRDD<WindowedValue<byte[]>>> rddQueue = new 
LinkedBlockingQueue<>();
+    rddQueue.offer(emptyByteArrayRDD);
+    JavaInputDStream<WindowedValue<byte[]>> emptyStream =
+        context.getStreamingContext().queueStream(rddQueue, true /* oneAtATime 
*/);
+
+    UnboundedDataset<byte[]> output =
+        new UnboundedDataset<>(
+            emptyStream, 
Collections.singletonList(emptyStream.inputDStream().id()));
+
+    // Add watermark to holder and advance to infinity to ensure future 
watermarks can be updated
+    GlobalWatermarkHolder.SparkWatermarks sparkWatermark =
+        new GlobalWatermarkHolder.SparkWatermarks(
+            GlobalWindow.INSTANCE.maxTimestamp(),
+            BoundedWindow.TIMESTAMP_MAX_VALUE,
+            context.getFirstTimestamp());
+    GlobalWatermarkHolder.add(output.getStreamSources().get(0), 
sparkWatermark);
+
+    context.pushDataset(getOutputId(transformNode), output);
+  }
+
+  private static <K, V> void translateGroupByKey(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.Components components = pipeline.getComponents();
+    String inputId = getInputId(transformNode);
+    UnboundedDataset<KV<K, V>> inputDataset =
+        (UnboundedDataset<KV<K, V>>) context.popDataset(inputId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<KV<K, V>>> dStream = inputDataset.getDStream();
+    WindowedValue.WindowedValueCoder<KV<K, V>> inputCoder =
+        getWindowedValueCoder(inputId, components);
+    KvCoder<K, V> inputKvCoder = (KvCoder<K, V>) inputCoder.getValueCoder();
+    Coder<K> inputKeyCoder = inputKvCoder.getKeyCoder();
+    Coder<V> inputValueCoder = inputKvCoder.getValueCoder();
+    final WindowingStrategy windowingStrategy = getWindowingStrategy(inputId, 
components);
+    final WindowFn<Object, BoundedWindow> windowFn = 
windowingStrategy.getWindowFn();
+    final WindowedValue.WindowedValueCoder<V> wvCoder =
+        WindowedValue.FullWindowedValueCoder.of(inputValueCoder, 
windowFn.windowCoder());
+
+    JavaDStream<WindowedValue<KV<K, Iterable<V>>>> outStream =
+        SparkGroupAlsoByWindowViaWindowSet.groupByKeyAndWindow(
+            dStream,
+            inputKeyCoder,
+            wvCoder,
+            windowingStrategy,
+            context.getSerializableOptions(),
+            streamSources,
+            transformNode.getId());
+
+    context.pushDataset(
+        getOutputId(transformNode), new UnboundedDataset<>(outStream, 
streamSources));
+  }
+
+  private static <InputT, OutputT, SideInputT> void translateExecutableStage(
+      PTransformNode transformNode,
+      RunnerApi.Pipeline pipeline,
+      SparkStreamingTranslationContext context) {
+    RunnerApi.ExecutableStagePayload stagePayload;
+    try {
+      stagePayload =
+          RunnerApi.ExecutableStagePayload.parseFrom(
+              transformNode.getTransform().getSpec().getPayload());
+    } catch (IOException e) {
+      throw new RuntimeException(e);
+    }
+
+    String inputPCollectionId = stagePayload.getInput();
+    UnboundedDataset<InputT> inputDataset =
+        (UnboundedDataset<InputT>) context.popDataset(inputPCollectionId);
+    List<Integer> streamSources = inputDataset.getStreamSources();
+    JavaDStream<WindowedValue<InputT>> inputDStream = 
inputDataset.getDStream();
+    Map<String, String> outputs = transformNode.getTransform().getOutputsMap();
+    BiMap<String, Integer> outputMap = createOutputMap(outputs.values());
+
+    RunnerApi.Components components = pipeline.getComponents();
+    Coder windowCoder =
+        getWindowingStrategy(inputPCollectionId, 
components).getWindowFn().windowCoder();
+
+    // TODO (BEAM-10712): handle side inputs.

Review comment:
       Trow a clear exception here if the executable stage declares itself as 
having side inputs. 




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Issue Time Tracking
-------------------

    Worklog Id:     (was: 473187)
    Time Spent: 3h 50m  (was: 3h 40m)

> Spark portable runner: Streaming mode
> -------------------------------------
>
>                 Key: BEAM-7587
>                 URL: https://issues.apache.org/jira/browse/BEAM-7587
>             Project: Beam
>          Issue Type: Wish
>          Components: runner-spark
>            Reporter: Kyle Weaver
>            Assignee: Anna Qin
>            Priority: P2
>              Labels: portability-spark
>          Time Spent: 3h 50m
>  Remaining Estimate: 0h
>
> So far all work on the Spark portable runner has been in batch mode. This is 
> intended as an uber-issue for tracking progress on adding support for 
> streaming.
> -It might be advantageous to wait for the structured streaming (non-portable) 
> runner to be completed (to some reasonable extent) before undertaking this, 
> rather than using the DStream API.- Since work on the structured streaming 
> runner is blocked by SPARK-26655, we should implement this using DStreams 
> instead.



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