autophagy commented on code in PR #27928: URL: https://github.com/apache/flink/pull/27928#discussion_r3180023999
########## docs/content/docs/dev/table/testing/ptf_test_harness.md: ########## @@ -0,0 +1,361 @@ +--- +title: "Testing Process Table Functions" +weight: 10 +type: docs +--- +<!-- +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. +--> + +# Testing Process Table Functions + +The `ProcessTableFunctionTestHarness` provides a lightweight unit testing framework for Process Table +Functions (PTFs). It allows you to test PTF logic without starting a full Flink cluster. It is useful +for testing and validating PTF business logic, multi-table PTF behaviour and validating errors. + +For end-to-end integration testing with the full Flink planner and runtime, use integration tests +instead. + +{{< top >}} + +## Quick Start + +{{< tabs "quickstart" >}} +{{< tab "Java" >}} +```java +import org.apache.flink.table.annotation.*; +import org.apache.flink.table.api.DataTypes; +import org.apache.flink.table.functions.ProcessTableFunction; +import org.apache.flink.table.runtime.functions.ProcessTableFunctionTestHarness; +import org.apache.flink.types.Row; +import org.junit.jupiter.api.Test; + +import java.util.List; + +import static org.assertj.core.api.Assertions.assertThat; + +// PTF under test +@DataTypeHint("ROW<doubled INT>") +public class DoublePTF extends ProcessTableFunction<Row> { + public void eval(@ArgumentHint(ArgumentTrait.ROW_SEMANTIC_TABLE) Row input) { + int value = input.getFieldAs("value"); + collect(Row.of(value * 2)); + } +} + +// Test +@Test +void testDoublePTF() throws Exception { + try (ProcessTableFunctionTestHarness<Row> harness = + ProcessTableFunctionTestHarness.ofClass(DoublePTF.class) + .withTableArgument("input", DataTypes.of("ROW<value INT>")) + .build()) { + + harness.processElement(Row.of(5)); + harness.processElement(Row.of(10)); + + List<Row> output = harness.getOutput(); + assertThat(output).hasSize(2); + assertThat(output.get(0)).isEqualTo(Row.of(10)); + assertThat(output.get(1)).isEqualTo(Row.of(20)); + } +} +``` +{{< /tab >}} +{{< /tabs >}} + +{{< top >}} + +## Common Testing Scenarios + +### Testing Row-Semantic Tables + +Use `.withTableArgument()` to configure the input table schema: + +{{< tabs "row-semantic" >}} +{{< tab "Java" >}} +```java +@DataTypeHint("ROW<value INT>") +public class PassthroughPTF extends ProcessTableFunction<Row> { + public void eval(@ArgumentHint(ArgumentTrait.ROW_SEMANTIC_TABLE) Row input) { + collect(input); + } +} + +@Test +void testPassthrough() throws Exception { + try (ProcessTableFunctionTestHarness<Row> harness = + ProcessTableFunctionTestHarness.ofClass(PassthroughPTF.class) + .withTableArgument("input", DataTypes.of("ROW<value INT>")) + .build()) { + + harness.processElement(Row.of(42)); + harness.processElement(Row.of(100)); + + List<Row> output = harness.getOutput(); + assertThat(output).containsExactly(Row.of(42), Row.of(100)); + } +} +``` +{{< /tab >}} +{{< /tabs >}} + +### Testing Set-Semantic Tables with Partitioning + +For `SET_SEMANTIC_TABLE`, use `.withPartitionBy()` to configure partition columns: + +{{< tabs "set-semantic" >}} +{{< tab "Java" >}} +```java +@DataTypeHint("ROW<doubled INT>") +public class PartitionedPTF extends ProcessTableFunction<Row> { + public void eval(@ArgumentHint(ArgumentTrait.SET_SEMANTIC_TABLE) Row input) { + int value = input.getFieldAs("value"); + collect(Row.of(value * 2)); + } +} + +@Test +void testPartitionedPTF() throws Exception { + try (ProcessTableFunctionTestHarness<Row> harness = + ProcessTableFunctionTestHarness.ofClass(PartitionedPTF.class) + .withTableArgument("input", DataTypes.of("ROW<key STRING, value INT>")) + .withPartitionBy("input", "key") + .build()) { + + harness.processElement(Row.of("A", 10)); + harness.processElement(Row.of("B", 20)); + + List<Row> output = harness.getOutput(); + assertThat(output.get(0)).isEqualTo(Row.of("A", 20)); + assertThat(output.get(1)).isEqualTo(Row.of("B", 40)); + } +} +``` +{{< /tab >}} +{{< /tabs >}} + +### Testing Multiple Table Arguments + +Use `processElementForTable()` to specify which table receives each row: + +{{< tabs "multi-table" >}} +{{< tab "Java" >}} +```java +@DataTypeHint("ROW<output STRING>") +public class JoinPTF extends ProcessTableFunction<Row> { + public void eval( + @ArgumentHint(ArgumentTrait.SET_SEMANTIC_TABLE) Row left, + @ArgumentHint(ArgumentTrait.SET_SEMANTIC_TABLE) Row right) { + if (left != null) { + collect(Row.of("LEFT: " + left)); + } + if (right != null) { + collect(Row.of("RIGHT: " + right)); + } + } +} + +@Test +void testMultiTable() throws Exception { + try (ProcessTableFunctionTestHarness<Row> harness = + ProcessTableFunctionTestHarness.ofClass(JoinPTF.class) + .withTableArgument("left", DataTypes.of("ROW<id INT, name STRING>")) + .withPartitionBy("left", "id") + .withTableArgument("right", DataTypes.of("ROW<id INT, city STRING>")) + .withPartitionBy("right", "id") + .build()) { + + // Use processElementForTable() to target specific tables + harness.processElementForTable("left", Row.of(1, "Alice")); + harness.processElementForTable("right", Row.of(1, "Berlin")); + + List<Row> output = harness.getOutput(); + assertThat(output.get(0)).isEqualTo(Row.of(1, null, "LEFT: +I[1, Alice]")); + assertThat(output.get(1)).isEqualTo(Row.of(null, 1, "RIGHT: +I[1, Berlin]")); + } +} +``` +{{< /tab >}} +{{< /tabs >}} + +### Testing with Scalar Arguments + +Use `.withScalarArgument()` to configure scalar parameter values: + +{{< tabs "scalar-args" >}} +{{< tab "Java" >}} +```java +@DataTypeHint("ROW<value INT>") +public class FilterPTF extends ProcessTableFunction<Row> { + public void eval( + @ArgumentHint(ArgumentTrait.ROW_SEMANTIC_TABLE) Row input, + @ArgumentHint(ArgumentTrait.SCALAR) int threshold) { + int value = input.getFieldAs("value"); + if (value > threshold) { + collect(Row.of(value)); + } + } +} + +@Test +void testFilter() throws Exception { + try (ProcessTableFunctionTestHarness<Row> harness = + ProcessTableFunctionTestHarness.ofClass(FilterPTF.class) + .withTableArgument("input", DataTypes.of("ROW<value INT>")) + .withScalarArgument("threshold", 50) // Configure scalar value + .build()) { + + harness.processElement(Row.of(30)); + harness.processElement(Row.of(70)); + + List<Row> output = harness.getOutput(); + assertThat(output).containsExactly(Row.of(70)); + } +} +``` +{{< /tab >}} +{{< /tabs >}} + +**Scalar-Only PTFs**: For PTFs with only scalar arguments, use `invoke()` to trigger evaluation: + +{{< tabs "scalar-only" >}} +{{< tab "Java" >}} +```java +@DataTypeHint("ROW<sum INT>") +public class AddPTF extends ProcessTableFunction<Row> { + public void eval( + @ArgumentHint(ArgumentTrait.SCALAR) int a, + @ArgumentHint(ArgumentTrait.SCALAR) int b) { + collect(Row.of(a + b)); + } +} + +@Test +void testScalarOnly() throws Exception { + try (ProcessTableFunctionTestHarness<Row> harness = + ProcessTableFunctionTestHarness.ofClass(AddPTF.class) + .withScalarArgument("a", 5) + .withScalarArgument("b", 7) + .build()) { + + harness.invoke(); // Use invoke() instead of processElement() Review Comment: It throws an invalid state exception, with `process() is only for scalar-only PTFs. This PTF has table arguments. Use processElement() or processElementForTable() instead.` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
