[GitHub] [beam] matthiasa4 commented on a change in pull request #13645: [BEAM-11289] [Java] Integrate Google Cloud Recommendations AI functio…

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matthiasa4 commented on a change in pull request #13645:
URL: https://github.com/apache/beam/pull/13645#discussion_r584644845



##########
File path: sdks/java/extensions/ml/src/main/java/org/apache/beam/sdk/extensions/ml/RecommendationAIImportCatalogItems.java
##########
@@ -0,0 +1,166 @@
+/*
+ * 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.api.client.json.GenericJson;
+import com.google.api.gax.rpc.ApiException;
+import com.google.auto.value.AutoValue;
+import com.google.cloud.recommendationengine.v1beta1.CatalogInlineSource;
+import com.google.cloud.recommendationengine.v1beta1.CatalogItem;
+import com.google.cloud.recommendationengine.v1beta1.CatalogName;
+import com.google.cloud.recommendationengine.v1beta1.CatalogServiceClient;
+import com.google.cloud.recommendationengine.v1beta1.ImportCatalogItemsRequest;
+import com.google.cloud.recommendationengine.v1beta1.ImportCatalogItemsResponse;
+import com.google.cloud.recommendationengine.v1beta1.InputConfig;
+import com.google.protobuf.util.JsonFormat;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.concurrent.ExecutionException;
+import org.apache.beam.sdk.transforms.DoFn;
+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.PCollectionTuple;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.beam.sdk.values.TupleTagList;
+import org.checkerframework.checker.nullness.qual.Nullable;
+import org.json.JSONObject;
+
+/**
+ * A {@link PTransform} connecting to the Recommendations AI API
+ * (https://cloud.google.com/recommendations) and creating {@link CatalogItem}s. *
+ *
+ * <p>Batch size defines how many items are created at once per batch (max: 5000).
+ *
+ * <p>The transform consumes {@link KV} of {@link String} and {@link GenericJson}s (assumed to be
+ * the catalog item id as key and contents as value) and outputs a PCollectionTuple which will
+ * contain the successfully created and failed catalog items.
+ *
+ * <p>It is possible to provide a catalog name to which you want to add the catalog item (defaults
+ * to "default_catalog").
+ */
+@AutoValue
+@SuppressWarnings({"nullness"})
+public abstract class RecommendationAIImportCatalogItems
+    extends PTransform<PCollection<KV<String, GenericJson>>, PCollectionTuple> {
+
+  public static final TupleTag<CatalogItem> SUCCESS_TAG = new TupleTag<CatalogItem>() {};
+  public static final TupleTag<CatalogItem> FAILURE_TAG = new TupleTag<CatalogItem>() {};
+
+  public static Builder newBuilder() {
+    return new AutoValue_RecommendationAIImportCatalogItems.Builder();
+  }
+
+  /** @return ID of Google Cloud project to be used for creating catalog items. */
+  public abstract String projectId();
+
+  /** @return Name of the catalog where the catalog items will be created. */
+  public abstract @Nullable String catalogName();
+
+  /** @return Size of input elements batch to be sent to Cloud DLP service in one request. */
+  public abstract Integer batchSize();
+
+  /**
+   * The transform converts the contents of input PCollection into {@link CatalogItem}s and then
+   * calls the Recommendation AI service to create the catalog item.
+   *
+   * @param input input PCollection
+   * @return PCollection after transformations
+   */
+  @Override
+  public PCollectionTuple expand(PCollection<KV<String, GenericJson>> input) {
+    return input
+        .apply("Batch Contents", ParDo.of(new BatchRequestForRecommendationAI(batchSize())))

Review comment:
       Agreed. I replaced the transform with `GroupIntoBatches` and left the BufferingDuration to be set by the user (in case they want to play around with it or if there are changes to the API in the future that affect this in some way). 




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