feat(samples): add all feature values samples #981

sai-chaithu · 2022-06-28T09:18:56Z

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Fixes #945 ☕️

generated-files-bot · 2022-06-28T09:19:01Z

Warning: This pull request is touching the following templated files:

samples/install-without-bom/pom.xml
samples/snapshot/pom.xml
samples/snippets/pom.xml

snippet-bot · 2022-06-28T09:19:01Z

Here is the summary of changes.

You are about to add 5 region tags.

samples/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java:24, tag aiplatform_batch_create_features_sample
samples/snippets/src/main/java/aiplatform/BatchReadFeatureValuesSample.java:25, tag aiplatform_batch_read_feature_values_sample
samples/snippets/src/main/java/aiplatform/ExportFeatureValuesSample.java:24, tag aiplatform_export_feature_values_sample
samples/snippets/src/main/java/aiplatform/ExportFeatureValuesSnapshotSample.java:24, tag aiplatform_export_feature_values_snapshot_sample
samples/snippets/src/main/java/aiplatform/ImportFeatureValuesSample.java:24, tag aiplatform_import_feature_values_sample

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gkc2104 · 2022-07-08T02:34:40Z

samples/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java

+          .setParent(EntityTypeName.of(project, location, featurestoreId, entityTypeId).toString())
+          .addAllRequests(createFeatureRequests).build();
+
+      OperationFuture<BatchCreateFeaturesResponse, BatchCreateFeaturesOperationMetadata> future =


Name the operationFutures consistently across the files, maybe use batchCreateFeaturesOperationFuture or just future, but use same across.

ok, will use same across

gkc2104 · 2022-07-08T02:36:54Z

samples/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java

+      List<CreateFeatureRequest> createFeatureRequests = new ArrayList<>();
+
+      Feature titleFeature = Feature.newBuilder().setDescription("The title of the movie")
+          .setValueType(ValueType.valueOf("STRING")).build();


Use the ENUM directly here and in other places as well.

Sure, will update to ENUM type everywhere as below,

Suggested change

.setValueType(ValueType.valueOf("STRING")).build();

.setValueType(ValueType.STRING).build();

gkc2104 · 2022-07-08T02:39:31Z

samples/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java

+
+      Feature titleFeature = Feature.newBuilder().setDescription("The title of the movie")
+          .setValueType(ValueType.valueOf("STRING")).build();
+      Feature genresFeature = Feature.newBuilder().setDescription("The genres of the movie")


nit: change to singular genre, to me genres represents an array of genres.

Using the same features as https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/feature_store/gapic-feature-store.ipynb sample tutorial provided in SOW.
So thought it is ok, should we change it here?

Oh I see, let's retain it for now. It was a minor nit.

gkc2104 · 2022-07-08T02:40:34Z

samples/snippets/src/main/java/aiplatform/BatchCreateFeaturesSample.java

+      System.out.format("Operation name: %s%n", future.getInitialFuture().get().getName());
+      System.out.println("Waiting for operation to finish...");
+      BatchCreateFeaturesResponse batchCreateFeaturesResponse =
+          future.get(timeout, TimeUnit.SECONDS);


just to confirm, is the behavior here to wait the 300 sec and timeout otherwise. If there is a response available, it's returned.

yes, if the response is not received in 300 sec it will throw timeout

gkc2104 · 2022-07-08T02:41:54Z

samples/snippets/src/main/java/aiplatform/BatchReadFeatureValuesSample.java

+              .setCsvReadInstances(CsvSource.newBuilder().setGcsSource(gcsSource))
+              .setDestination(
+                  FeatureValueDestination.newBuilder().setBigqueryDestination(bigQueryDestination))
+              // .addAllPassThroughFields(passThroughFieldsList)


should we include this as well, if possible ?

removing that as there are no passThroughFields for the movie prediction example.

gkc2104 · 2022-07-08T02:42:59Z

samples/snippets/src/main/java/aiplatform/ExportFeatureValuesSample.java

+      List<String> ids = new ArrayList<>();
+      ids.add("*");
+      FeatureSelector featureSelector = FeatureSelector.newBuilder()
+          .setIdMatcher(IdMatcher.newBuilder().addAllIds(ids).build()).build();


nit: inline something like addAllIds(ArrayList.of()...), or make a class variable if intended for developer to update.

ok, will add inline as below,

Suggested change

.setIdMatcher(IdMatcher.newBuilder().addAllIds(ids).build()).build();

.setIdMatcher(IdMatcher.newBuilder().addAllIds(Arrays.asList("title","genres","average_rating")).build()).build();

I feel it's better to make it one of the variables the developer has to update and pass it down here.

updated code to pass the feature selector ids as a list object

…and list variable

dizcology

Please make sure sample tests pass before merging.

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🤖 I have created a release *beep* *boop* --- ## [3.2.0](v3.1.0...v3.2.0) (2022-08-09) ### Features * add a DeploymentResourcePool API resource_definition ([#997](#997)) ([f3e6d4f](f3e6d4f)) * add DeploymentResourcePool in aiplatform v1beta1 deployment_resource_pool.proto ([#998](#998)) ([49fb069](49fb069)) * add DeploymentResourcePoolService in aiplatform v1beta1 deployment_resource_pool_service.proto ([49fb069](49fb069)) * add shared_resources for supported prediction_resources ([f3e6d4f](f3e6d4f)) * add SHARED_RESOURCES to DeploymentResourcesType in aiplatform v1beta1 model.proto ([49fb069](49fb069)) * added SHARED_RESOURCES enum to aiplatform v1 model.proto ([3935d8f](3935d8f)) * DeploymentResourcePool and DeployementResourcePoolService added to aiplatform v1beta1 model.proto (cl/463147866) ([3935d8f](3935d8f)) * making network arg optional in aiplatform v1 custom_job.proto ([#999](#999)) ([3935d8f](3935d8f)) * making network arg optional in aiplatform v1beta1 custom_job.proto ([3935d8f](3935d8f)) * **samples:** add all feature samples ([#980](#980)) ([a932cf8](a932cf8)) * **samples:** add all feature values samples ([#981](#981)) ([818acab](818acab)) ### Bug Fixes * declaring test-scope artifact as runtime ([#1014](#1014)) ([f90cc12](f90cc12)) ### Documentation * doc edits to aiplatform v1 dataset_service.proto, job_service.proto, model_service.proto, pipeline_service.proto, saved_query.proto, study.proto, types.proto ([3935d8f](3935d8f)) * doc edits to aiplatform v1beta1 job_service.proto, model_service.proto, pipeline_service.proto, saved_query.proto, study.proto, types.proto ([3935d8f](3935d8f)) ### Dependencies * update dependency com.google.api.grpc:proto-google-cloud-aiplatform-v1beta1 to v0.17.0 ([#1003](#1003)) ([c2b98d9](c2b98d9)) * update dependency com.google.cloud:google-cloud-bigquery to v2.14.1 ([#1006](#1006)) ([2c959b9](2c959b9)) * update dependency com.google.cloud:google-cloud-bigquery to v2.14.3 ([#1009](#1009)) ([b170504](b170504)) * update dependency com.google.cloud:google-cloud-shared-dependencies to v3 ([#1000](#1000)) ([6fb1534](6fb1534)) * update dependency com.google.cloud:google-cloud-storage to v2.10.0 ([#1004](#1004)) ([b6e2ab4](b6e2ab4)) * update dependency com.google.cloud:google-cloud-storage to v2.11.0 ([#1005](#1005)) ([26391a3](26391a3)) * update dependency com.google.cloud:google-cloud-storage to v2.11.1 ([#1008](#1008)) ([cba42d1](cba42d1)) * update dependency com.google.cloud:google-cloud-storage to v2.11.2 ([#1010](#1010)) ([4f35eed](4f35eed)) * update dependency com.google.code.gson:gson to v2.9.1 ([#1001](#1001)) ([f12c313](f12c313)) --- This PR was generated with [Release Please](https://github.com/googleapis/release-please). See [documentation](https://github.com/googleapis/release-please#release-please).

🤖 I have created a release *beep* *boop* --- ## [3.2.0](googleapis/java-aiplatform@v3.1.0...v3.2.0) (2022-08-09) ### Features * add a DeploymentResourcePool API resource_definition ([#997](googleapis/java-aiplatform#997)) ([82551d8](googleapis/java-aiplatform@82551d8)) * add DeploymentResourcePool in aiplatform v1beta1 deployment_resource_pool.proto ([#998](googleapis/java-aiplatform#998)) ([76dc64f](googleapis/java-aiplatform@76dc64f)) * add DeploymentResourcePoolService in aiplatform v1beta1 deployment_resource_pool_service.proto ([76dc64f](googleapis/java-aiplatform@76dc64f)) * add shared_resources for supported prediction_resources ([82551d8](googleapis/java-aiplatform@82551d8)) * add SHARED_RESOURCES to DeploymentResourcesType in aiplatform v1beta1 model.proto ([76dc64f](googleapis/java-aiplatform@76dc64f)) * added SHARED_RESOURCES enum to aiplatform v1 model.proto ([301cfb0](googleapis/java-aiplatform@301cfb0)) * DeploymentResourcePool and DeployementResourcePoolService added to aiplatform v1beta1 model.proto (cl/463147866) ([301cfb0](googleapis/java-aiplatform@301cfb0)) * making network arg optional in aiplatform v1 custom_job.proto ([#999](googleapis/java-aiplatform#999)) ([301cfb0](googleapis/java-aiplatform@301cfb0)) * making network arg optional in aiplatform v1beta1 custom_job.proto ([301cfb0](googleapis/java-aiplatform@301cfb0)) * **samples:** add all feature samples ([#980](googleapis/java-aiplatform#980)) ([8c2a485](googleapis/java-aiplatform@8c2a485)) * **samples:** add all feature values samples ([#981](googleapis/java-aiplatform#981)) ([2d4e6fe](googleapis/java-aiplatform@2d4e6fe)) ### Bug Fixes * declaring test-scope artifact as runtime ([#1014](googleapis/java-aiplatform#1014)) ([6c47c65](googleapis/java-aiplatform@6c47c65)) ### Documentation * doc edits to aiplatform v1 dataset_service.proto, job_service.proto, model_service.proto, pipeline_service.proto, saved_query.proto, study.proto, types.proto ([301cfb0](googleapis/java-aiplatform@301cfb0)) * doc edits to aiplatform v1beta1 job_service.proto, model_service.proto, pipeline_service.proto, saved_query.proto, study.proto, types.proto ([301cfb0](googleapis/java-aiplatform@301cfb0)) ### Dependencies * update dependency com.google.api.grpc:proto-google-cloud-aiplatform-v1beta1 to v0.17.0 ([#1003](googleapis/java-aiplatform#1003)) ([b793732](googleapis/java-aiplatform@b793732)) * update dependency com.google.cloud:google-cloud-bigquery to v2.14.1 ([#1006](googleapis/java-aiplatform#1006)) ([6bb8982](googleapis/java-aiplatform@6bb8982)) * update dependency com.google.cloud:google-cloud-bigquery to v2.14.3 ([#1009](googleapis/java-aiplatform#1009)) ([8cca8b5](googleapis/java-aiplatform@8cca8b5)) * update dependency com.google.cloud:google-cloud-shared-dependencies to v3 ([#1000](googleapis/java-aiplatform#1000)) ([c93de30](googleapis/java-aiplatform@c93de30)) * update dependency com.google.cloud:google-cloud-storage to v2.10.0 ([#1004](googleapis/java-aiplatform#1004)) ([dd52cad](googleapis/java-aiplatform@dd52cad)) * update dependency com.google.cloud:google-cloud-storage to v2.11.0 ([#1005](googleapis/java-aiplatform#1005)) ([60e2f76](googleapis/java-aiplatform@60e2f76)) * update dependency com.google.cloud:google-cloud-storage to v2.11.1 ([#1008](googleapis/java-aiplatform#1008)) ([9a2fe64](googleapis/java-aiplatform@9a2fe64)) * update dependency com.google.cloud:google-cloud-storage to v2.11.2 ([#1010](googleapis/java-aiplatform#1010)) ([3c2ac16](googleapis/java-aiplatform@3c2ac16)) * update dependency com.google.code.gson:gson to v2.9.1 ([#1001](googleapis/java-aiplatform#1001)) ([a6ffed4](googleapis/java-aiplatform@a6ffed4)) --- This PR was generated with [Release Please](https://github.com/googleapis/release-please). See [documentation](https://github.com/googleapis/release-please#release-please).

sai-chaithu added 2 commits June 28, 2022 14:15

feat(samples): add all feature values samples

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feat(samples): update all feature values samples

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feat(samples): update big query dependency in pom.xml

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Merge branch 'googleapis:main' into FeatureValuesSamples

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feat(samples): code review changes

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Merge branch 'googleapis:main' into FeatureValuesSamples

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feat(samples): updated feature values samples with close method call …

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…and list variable

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feat(samples): add all feature values samples #981

feat(samples): add all feature values samples #981

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	.setValueType(ValueType.valueOf("STRING")).build();
	.setValueType(ValueType.STRING).build();

	.setIdMatcher(IdMatcher.newBuilder().addAllIds(ids).build()).build();
	.setIdMatcher(IdMatcher.newBuilder().addAllIds(Arrays.asList("title","genres","average_rating")).build()).build();

feat(samples): add all feature values samples #981

feat(samples): add all feature values samples #981

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