| /* |
| * 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.examples.cookbook; |
| |
| import com.google.api.services.bigquery.model.TableRow; |
| import org.apache.beam.examples.cookbook.BigQueryTornadoes.ExtractTornadoesFn; |
| import org.apache.beam.examples.cookbook.BigQueryTornadoes.FormatCountsFn; |
| import org.apache.beam.sdk.testing.PAssert; |
| import org.apache.beam.sdk.testing.TestPipeline; |
| import org.apache.beam.sdk.testing.ValidatesRunner; |
| import org.apache.beam.sdk.transforms.Create; |
| 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.TypeDescriptor; |
| import org.apache.beam.vendor.guava.v20_0.com.google.common.collect.ImmutableList; |
| import org.junit.Rule; |
| import org.junit.Test; |
| import org.junit.experimental.categories.Category; |
| import org.junit.runner.RunWith; |
| import org.junit.runners.JUnit4; |
| |
| /** Test case for {@link BigQueryTornadoes}. */ |
| @RunWith(JUnit4.class) |
| public class BigQueryTornadoesTest { |
| @Rule public TestPipeline p = TestPipeline.create(); |
| |
| @Test |
| @Category(ValidatesRunner.class) |
| public void testExtractTornadoes() { |
| TableRow row = new TableRow().set("month", "6").set("tornado", true); |
| PCollection<TableRow> input = p.apply(Create.of(ImmutableList.of(row))); |
| PCollection<Integer> result = input.apply(ParDo.of(new ExtractTornadoesFn())); |
| PAssert.that(result).containsInAnyOrder(6); |
| p.run().waitUntilFinish(); |
| } |
| |
| @Test |
| @Category(ValidatesRunner.class) |
| public void testNoTornadoes() { |
| TableRow row = new TableRow().set("month", 6).set("tornado", false); |
| PCollection<TableRow> inputs = p.apply(Create.of(ImmutableList.of(row))); |
| PCollection<Integer> result = inputs.apply(ParDo.of(new ExtractTornadoesFn())); |
| PAssert.that(result).empty(); |
| p.run().waitUntilFinish(); |
| } |
| |
| @Test |
| @Category(ValidatesRunner.class) |
| public void testEmpty() { |
| PCollection<KV<Integer, Long>> inputs = |
| p.apply(Create.empty(new TypeDescriptor<KV<Integer, Long>>() {})); |
| PCollection<TableRow> result = inputs.apply(ParDo.of(new FormatCountsFn())); |
| PAssert.that(result).empty(); |
| p.run().waitUntilFinish(); |
| } |
| |
| @Test |
| @Category(ValidatesRunner.class) |
| public void testFormatCounts() { |
| PCollection<KV<Integer, Long>> inputs = |
| p.apply(Create.of(KV.of(3, 0L), KV.of(4, Long.MAX_VALUE), KV.of(5, Long.MIN_VALUE))); |
| PCollection<TableRow> result = inputs.apply(ParDo.of(new FormatCountsFn())); |
| PAssert.that(result) |
| .containsInAnyOrder( |
| new TableRow().set("month", 3).set("tornado_count", 0), |
| new TableRow().set("month", 4).set("tornado_count", Long.MAX_VALUE), |
| new TableRow().set("month", 5).set("tornado_count", Long.MIN_VALUE)); |
| p.run().waitUntilFinish(); |
| } |
| } |