yifan-c commented on code in PR #183: URL: https://github.com/apache/cassandra-analytics/pull/183#discussion_r2975941862
########## cassandra-analytics-integration-tests/src/test/java/org/apache/cassandra/analytics/BulkWriteComplexTypeTtlTest.java: ########## @@ -0,0 +1,201 @@ +/* + * 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.cassandra.analytics; + +import java.util.Arrays; +import java.util.List; +import java.util.concurrent.TimeUnit; +import java.util.stream.Collectors; +import java.util.stream.IntStream; + +import com.google.common.collect.ImmutableMap; +import com.google.common.collect.ImmutableSet; +import org.junit.jupiter.api.Test; + +import org.apache.cassandra.distributed.shared.Uninterruptibles; +import org.apache.cassandra.sidecar.testing.QualifiedName; +import org.apache.cassandra.spark.bulkwriter.TTLOption; +import org.apache.cassandra.spark.bulkwriter.WriterOptions; +import org.apache.cassandra.testing.ClusterBuilderConfiguration; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.RowFactory; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.types.Metadata; +import org.apache.spark.sql.types.StructField; +import org.apache.spark.sql.types.StructType; + +import static org.apache.cassandra.testing.TestUtils.DC1_RF3; +import static org.apache.cassandra.testing.TestUtils.TEST_KEYSPACE; +import static org.apache.spark.sql.types.DataTypes.IntegerType; +import static org.apache.spark.sql.types.DataTypes.StringType; +import static org.apache.spark.sql.types.DataTypes.createArrayType; +import static org.apache.spark.sql.types.DataTypes.createMapType; +import static org.apache.spark.sql.types.DataTypes.createStructType; +import static org.assertj.core.api.Assertions.assertThat; + +/** + * Tests that bulk writes with TTL work correctly for complex types (list, set, map, UDT). + * This ensures the expiring cell path is invoked correctly for collection and composite types. + * TODO: add tuple ttl test after adding support for writing tuples + */ +class BulkWriteComplexTypeTtlTest extends SharedClusterSparkIntegrationTestBase +{ + static final int ROW_COUNT = 100; + + static final QualifiedName LIST_TTL_TABLE = new QualifiedName(TEST_KEYSPACE, "test_list_ttl"); + static final QualifiedName SET_TTL_TABLE = new QualifiedName(TEST_KEYSPACE, "test_set_ttl"); + static final QualifiedName MAP_TTL_TABLE = new QualifiedName(TEST_KEYSPACE, "test_map_ttl"); + static final QualifiedName UDT_TTL_TABLE = new QualifiedName(TEST_KEYSPACE, "test_udt_ttl"); + + static final String SIMPLE_UDT_NAME = "simple_udt"; + + @Test + void testListWithTtl() + { + SparkSession spark = getOrCreateSparkSession(); + StructType schema = new StructType() + .add("id", IntegerType, false) + .add("listdata", createArrayType(IntegerType), false); + + List<Row> rows = IntStream.range(0, ROW_COUNT) + .mapToObj(i -> RowFactory.create(i, Arrays.asList(i, i + 1))) + .collect(Collectors.toList()); + Dataset<Row> df = spark.createDataFrame(rows, schema); + + bulkWriterDataFrameWriter(df, LIST_TTL_TABLE).option(WriterOptions.TTL.name(), TTLOption.constant(80)) + .save(); + + Dataset<Row> preExpiry = bulkReaderDataFrame(LIST_TTL_TABLE).load(); + assertThat(preExpiry.collectAsList()).hasSize(ROW_COUNT); + + Uninterruptibles.sleepUninterruptibly(80, TimeUnit.SECONDS); + Dataset<Row> postExpiry = bulkReaderDataFrame(LIST_TTL_TABLE).load(); + assertThat(postExpiry.collectAsList()).isEmpty(); + } + + @Test + void testSetWithTtl() + { + SparkSession spark = getOrCreateSparkSession(); + StructType schema = new StructType() + .add("id", IntegerType, false) + .add("setdata", createArrayType(StringType), false); + + List<Row> rows = IntStream.range(0, ROW_COUNT) + .mapToObj(i -> RowFactory.create(i, ImmutableSet.of("item" + i))) + .collect(Collectors.toList()); + Dataset<Row> df = spark.createDataFrame(rows, schema); + + bulkWriterDataFrameWriter(df, SET_TTL_TABLE).option(WriterOptions.TTL.name(), TTLOption.constant(80)) + .save(); + + Dataset<Row> preExpiry = bulkReaderDataFrame(SET_TTL_TABLE).load(); + assertThat(preExpiry.collectAsList()).hasSize(ROW_COUNT); + + Uninterruptibles.sleepUninterruptibly(80, TimeUnit.SECONDS); + Dataset<Row> postExpiry = bulkReaderDataFrame(SET_TTL_TABLE).load(); + assertThat(postExpiry.collectAsList()).isEmpty(); + } + + @Test + void testMapWithTtl() + { + SparkSession spark = getOrCreateSparkSession(); + StructType schema = new StructType() + .add("id", IntegerType, false) + .add("mapdata", createMapType(StringType, IntegerType), false); + + List<Row> rows = IntStream.range(0, ROW_COUNT) + .mapToObj(i -> RowFactory.create(i, ImmutableMap.of("key" + i, i))) + .collect(Collectors.toList()); + Dataset<Row> df = spark.createDataFrame(rows, schema); + + bulkWriterDataFrameWriter(df, MAP_TTL_TABLE).option(WriterOptions.TTL.name(), TTLOption.constant(80)) + .save(); + + Dataset<Row> preExpiry = bulkReaderDataFrame(MAP_TTL_TABLE).load(); + assertThat(preExpiry.collectAsList()).hasSize(ROW_COUNT); + + Uninterruptibles.sleepUninterruptibly(80, TimeUnit.SECONDS); + Dataset<Row> postExpiry = bulkReaderDataFrame(MAP_TTL_TABLE).load(); + assertThat(postExpiry.collectAsList()).isEmpty(); + } + + @Test + void testUdtWithTtl() + { + SparkSession spark = getOrCreateSparkSession(); + StructType udtType = createStructType(new StructField[]{ + new StructField("f1", StringType, true, Metadata.empty()), + new StructField("f2", IntegerType, true, Metadata.empty()) + }); + StructType schema = new StructType() + .add("id", IntegerType, false) + .add("udtfield", udtType, false); + + List<Row> rows = IntStream.range(0, ROW_COUNT) + .mapToObj(i -> RowFactory.create(i, RowFactory.create("course" + i, i))) + .collect(Collectors.toList()); + Dataset<Row> df = spark.createDataFrame(rows, schema); + + bulkWriterDataFrameWriter(df, UDT_TTL_TABLE).option(WriterOptions.TTL.name(), TTLOption.constant(80)) + .save(); + + Dataset<Row> preExpiry = bulkReaderDataFrame(UDT_TTL_TABLE).load(); + assertThat(preExpiry.collectAsList()).hasSize(ROW_COUNT); + + Uninterruptibles.sleepUninterruptibly(80, TimeUnit.SECONDS); Review Comment: Just to be clear, I was not arguing the test is not valuable :p The point is that we should not sleep for 80 seconds. Can you instead try to write data using a timestamp in the past? -- 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] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
