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[FLINK-22653][python][table-planner-blink] Support StreamExecPythonOv…
…erAggregate json serialization/deserialization This closes apache#15937.
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...rg/apache/flink/table/planner/plan/nodes/exec/stream/PythonOverAggregateJsonPlanTest.java
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| /* | ||
| * 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. | ||
| */ | ||
|
|
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| package org.apache.flink.table.planner.plan.nodes.exec.stream; | ||
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| import org.apache.flink.table.api.TableConfig; | ||
| import org.apache.flink.table.api.TableEnvironment; | ||
| import org.apache.flink.table.planner.runtime.utils.JavaUserDefinedAggFunctions.PandasAggregateFunction; | ||
| import org.apache.flink.table.planner.utils.StreamTableTestUtil; | ||
| import org.apache.flink.table.planner.utils.TableTestBase; | ||
|
|
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| import org.junit.Before; | ||
| import org.junit.Test; | ||
|
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| /** Test json serialization for over aggregate. */ | ||
| public class PythonOverAggregateJsonPlanTest extends TableTestBase { | ||
| private StreamTableTestUtil util; | ||
| private TableEnvironment tEnv; | ||
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| @Before | ||
| public void setup() { | ||
| util = streamTestUtil(TableConfig.getDefault()); | ||
| tEnv = util.getTableEnv(); | ||
| String srcTableDdl = | ||
| "CREATE TABLE MyTable (\n" | ||
| + " a int,\n" | ||
| + " b varchar,\n" | ||
| + " c int not null,\n" | ||
| + " rowtime timestamp(3),\n" | ||
| + " proctime as PROCTIME(),\n" | ||
| + " watermark for rowtime as rowtime" | ||
| + ") with (\n" | ||
| + " 'connector' = 'values',\n" | ||
| + " 'bounded' = 'false')"; | ||
| tEnv.executeSql(srcTableDdl); | ||
| tEnv.createTemporarySystemFunction("pyFunc", new PandasAggregateFunction()); | ||
| } | ||
|
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| @Test | ||
| public void testProcTimeBoundedPartitionedRangeOver() { | ||
| String sinkTableDdl = | ||
| "CREATE TABLE MySink (\n" | ||
| + " a bigint,\n" | ||
| + " b bigint\n" | ||
| + ") with (\n" | ||
| + " 'connector' = 'values',\n" | ||
| + " 'sink-insert-only' = 'false',\n" | ||
| + " 'table-sink-class' = 'DEFAULT')"; | ||
| tEnv.executeSql(sinkTableDdl); | ||
| String sql = | ||
| "insert into MySink SELECT a,\n" | ||
| + " pyFunc(c, c) OVER (PARTITION BY a ORDER BY proctime\n" | ||
| + " RANGE BETWEEN INTERVAL '2' HOUR PRECEDING AND CURRENT ROW)\n" | ||
| + "FROM MyTable"; | ||
| util.verifyJsonPlan(sql); | ||
| } | ||
|
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| @Test | ||
| public void testProcTimeBoundedNonPartitionedRangeOver() { | ||
| String sinkTableDdl = | ||
| "CREATE TABLE MySink (\n" | ||
| + " a bigint,\n" | ||
| + " b bigint\n" | ||
| + ") with (\n" | ||
| + " 'connector' = 'values',\n" | ||
| + " 'sink-insert-only' = 'false',\n" | ||
| + " 'table-sink-class' = 'DEFAULT')"; | ||
| tEnv.executeSql(sinkTableDdl); | ||
| String sql = | ||
| "insert into MySink SELECT a,\n" | ||
| + " pyFunc(c, c) OVER (ORDER BY proctime\n" | ||
| + " RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW)\n" | ||
| + " FROM MyTable"; | ||
| util.verifyJsonPlan(sql); | ||
| } | ||
|
|
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| @Test | ||
| public void testProcTimeUnboundedPartitionedRangeOver() { | ||
| String sinkTableDdl = | ||
| "CREATE TABLE MySink (\n" | ||
| + " a bigint,\n" | ||
| + " b bigint\n" | ||
| + ") with (\n" | ||
| + " 'connector' = 'values',\n" | ||
| + " 'sink-insert-only' = 'false',\n" | ||
| + " 'table-sink-class' = 'DEFAULT')"; | ||
| tEnv.executeSql(sinkTableDdl); | ||
| String sql = | ||
| "insert into MySink SELECT a,\n" | ||
| + " pyFunc(c, c) OVER (PARTITION BY a ORDER BY proctime RANGE UNBOUNDED PRECEDING)\n" | ||
| + "FROM MyTable"; | ||
| util.verifyJsonPlan(sql); | ||
| } | ||
|
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| @Test | ||
| public void testRowTimeBoundedPartitionedRowsOver() { | ||
| String sinkTableDdl = | ||
| "CREATE TABLE MySink (\n" | ||
| + " a bigint,\n" | ||
| + " b bigint\n" | ||
| + ") with (\n" | ||
| + " 'connector' = 'values',\n" | ||
| + " 'sink-insert-only' = 'false',\n" | ||
| + " 'table-sink-class' = 'DEFAULT')"; | ||
| tEnv.executeSql(sinkTableDdl); | ||
| String sql = | ||
| "insert into MySink SELECT a,\n" | ||
| + " pyFunc(c, c) OVER (PARTITION BY a ORDER BY rowtime\n" | ||
| + " ROWS BETWEEN 5 preceding AND CURRENT ROW)\n" | ||
| + "FROM MyTable"; | ||
| util.verifyJsonPlan(sql); | ||
| } | ||
|
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| @Test | ||
| public void testProcTimeBoundedPartitionedRowsOverWithBuiltinProctime() { | ||
| String sinkTableDdl = | ||
| "CREATE TABLE MySink (\n" | ||
| + " a bigint,\n" | ||
| + " b bigint\n" | ||
| + ") with (\n" | ||
| + " 'connector' = 'values',\n" | ||
| + " 'sink-insert-only' = 'false',\n" | ||
| + " 'table-sink-class' = 'DEFAULT')"; | ||
| tEnv.executeSql(sinkTableDdl); | ||
| String sql = | ||
| "insert into MySink SELECT a, " | ||
| + " pyFunc(c, c) OVER (" | ||
| + " PARTITION BY a ORDER BY proctime() ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) " | ||
| + "FROM MyTable"; | ||
| util.verifyJsonPlan(sql); | ||
| } | ||
| } |
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