[GitHub] [beam] lukecwik commented on a change in pull request #11331: [BEAM-9646] Add Google Cloud vision integration transform

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lukecwik commented on a change in pull request #11331:
URL: https://github.com/apache/beam/pull/11331#discussion_r425314660



##########
File path: sdks/java/extensions/ml/src/main/java/org/apache/beam/sdk/extensions/ml/AnnotateImages.java
##########
@@ -0,0 +1,209 @@
+/*
+ * 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.sdk.extensions.ml;
+
+import com.google.cloud.vision.v1.AnnotateImageRequest;
+import com.google.cloud.vision.v1.AnnotateImageResponse;
+import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
+import com.google.cloud.vision.v1.Feature;
+import com.google.cloud.vision.v1.ImageAnnotatorClient;
+import com.google.cloud.vision.v1.ImageContext;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+import java.util.Random;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.GroupIntoBatches;
+import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.PCollectionView;
+
+/**
+ * Parent class for transform utilizing Cloud Vision API.
+ *
+ * @param <T> Type of input PCollection.
+ */
+public abstract class AnnotateImages<T>
+    extends PTransform<PCollection<T>, PCollection<List<AnnotateImageResponse>>> {
+
+  private static final Long MIN_BATCH_SIZE = 1L;
+  private static final Long MAX_BATCH_SIZE = 5L;
+
+  protected final PCollectionView<Map<T, ImageContext>> contextSideInput;
+  protected final List<Feature> featureList;
+  private long batchSize;
+
+  public AnnotateImages(
+      PCollectionView<Map<T, ImageContext>> contextSideInput,
+      List<Feature> featureList,
+      long batchSize) {
+    this.contextSideInput = contextSideInput;
+    this.featureList = featureList;
+    checkBatchSizeCorrectness(batchSize);
+    this.batchSize = batchSize;
+  }
+
+  public AnnotateImages(List<Feature> featureList, long batchSize) {
+    contextSideInput = null;
+    this.featureList = featureList;
+    checkBatchSizeCorrectness(batchSize);
+    this.batchSize = batchSize;
+  }
+
+  private void checkBatchSizeCorrectness(long batchSize) {
+    if (batchSize > MAX_BATCH_SIZE) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Max batch size exceeded.\n" + "Batch size needs to be equal or smaller than %d",
+              MAX_BATCH_SIZE));
+    } else if (batchSize < MIN_BATCH_SIZE) {
+      throw new IllegalArgumentException(
+          String.format(
+              "Min batch size not reached.\n" + "Batch size needs to be larger than %d",
+              MIN_BATCH_SIZE));
+    }
+  }
+
+  /**
+   * Applies all necessary transforms to call the Vision API. In order to group requests into
+   * batches, we assign keys to the requests, as {@link GroupIntoBatches} works only on {@link KV}s.
+   */
+  @Override
+  public PCollection<List<AnnotateImageResponse>> expand(PCollection<T> input) {
+    ParDo.SingleOutput<T, AnnotateImageRequest> inputToRequestMapper;
+    if (contextSideInput != null) {
+      inputToRequestMapper =
+          ParDo.of(new MapInputToRequest(contextSideInput)).withSideInputs(contextSideInput);
+    } else {
+      inputToRequestMapper = ParDo.of(new MapInputToRequest(null));
+    }
+    return input
+        .apply(inputToRequestMapper)
+        .apply(ParDo.of(new AssignRandomKeys()))
+        .apply(GroupIntoBatches.ofSize(batchSize))
+        .apply(ParDo.of(new ExtractValues()))
+        .apply(ParDo.of(new PerformImageAnnotation()));
+  }
+
+  /**
+   * Input type to {@link AnnotateImageRequest} mapper. Needs to be implemented by child classes
+   *
+   * @param input Input element.
+   * @param ctx optional image context.
+   * @return A valid {@link AnnotateImageRequest} object.
+   */
+  public abstract AnnotateImageRequest mapToRequest(T input, ImageContext ctx);
+
+  /**
+   * The {@link DoFn} performing the calls to Cloud Vision API. Input PCollection contains lists of
+   * {@link AnnotateImageRequest}s ready for batching.
+   */
+  public static class PerformImageAnnotation
+      extends DoFn<List<AnnotateImageRequest>, List<AnnotateImageResponse>> {
+
+    private ImageAnnotatorClient imageAnnotatorClient;
+
+    public PerformImageAnnotation() {}
+
+    /**
+     * Parametrized constructor to make mock injection easier in testing.
+     *
+     * @param imageAnnotatorClient
+     */
+    public PerformImageAnnotation(ImageAnnotatorClient imageAnnotatorClient) {
+      this.imageAnnotatorClient = imageAnnotatorClient;
+    }
+
+    @StartBundle
+    public void startBundle() throws IOException {
+      imageAnnotatorClient = ImageAnnotatorClient.create();
+    }
+
+    @Teardown
+    public void teardown() {
+      imageAnnotatorClient.close();
+    }
+
+    @ProcessElement
+    public void processElement(ProcessContext context) {
+      context.output(getResponse(context.element()));
+    }
+
+    /**
+     * Performs the call itself. Default access for testing.
+     *
+     * @param requests request list.
+     * @return response list.
+     */
+    List<AnnotateImageResponse> getResponse(List<AnnotateImageRequest> requests) {
+      BatchAnnotateImagesResponse batchAnnotateImagesResponse =
+          imageAnnotatorClient.batchAnnotateImages(requests);
+      return batchAnnotateImagesResponse.getResponsesList();
+    }
+  }
+
+  /** A transform that converts input elements to {@link KV}s for grouping. */
+  private static class AssignRandomKeys
+      extends DoFn<AnnotateImageRequest, KV<Long, AnnotateImageRequest>> {
+    private Random random;
+
+    @Setup
+    public void setup() {
+      random = new Random();
+    }
+
+    @ProcessElement
+    public void processElement(ProcessContext context) {
+      context.output(KV.of(random.nextLong(), context.element()));

Review comment:
       I can't as this is IO dependent and I don't know what the QPS expectations for a pipeline for this API are. For example 50 made sense for BigQuery but it was doing 1000s of QPS.




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