[GitHub] [hudi] alexeykudinkin commented on a diff in pull request #6734: [HUDI-3478][HUDI-4887] Use Avro as the format of persisted cdc data

[GitBox <gi...@apache.org>]

alexeykudinkin commented on code in PR #6734:
URL: https://github.com/apache/hudi/pull/6734#discussion_r977061910


##########
hudi-common/src/main/java/org/apache/hudi/avro/AvroSchemaUtils.java:
##########
@@ -109,6 +109,11 @@ public static Schema createNullableSchema(Schema.Type avroType) {
     return Schema.createUnion(Schema.create(Schema.Type.NULL), Schema.create(avroType));

Review Comment:
   Let's rebase this one onto new one you're adding



##########
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/cdc/TestCDCDataFrameSuite.scala:
##########
@@ -0,0 +1,238 @@
+/*
+ * 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.hudi.functional.cdc
+
+import org.apache.avro.Schema
+import org.apache.avro.generic.IndexedRecord
+
+import org.apache.hadoop.fs.Path
+
+import org.apache.hudi.DataSourceWriteOptions._
+import org.apache.hudi.common.config.HoodieMetadataConfig
+import org.apache.hudi.common.model.{HoodieCommitMetadata, HoodieLogFile}
+import org.apache.hudi.common.table.cdc.{HoodieCDCSupplementalLoggingMode, HoodieCDCUtils}
+import org.apache.hudi.common.table.log.HoodieLogFormat
+import org.apache.hudi.common.table.log.block.{HoodieDataBlock, HoodieLogBlock}
+import org.apache.hudi.common.table.{HoodieTableConfig, HoodieTableMetaClient, TableSchemaResolver}
+import org.apache.hudi.common.table.timeline.HoodieInstant
+import org.apache.hudi.common.testutils.RawTripTestPayload.{deleteRecordsToStrings, recordsToStrings}
+import org.apache.hudi.config.{HoodieCleanConfig, HoodieWriteConfig}
+import org.apache.hudi.testutils.HoodieClientTestBase
+
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.SaveMode
+
+import org.junit.jupiter.api.{AfterEach, BeforeEach}
+import org.junit.jupiter.api.Assertions.{assertEquals, assertFalse, assertTrue}
+import org.junit.jupiter.params.ParameterizedTest
+import org.junit.jupiter.params.provider.CsvSource
+
+import scala.collection.JavaConversions._
+import scala.collection.JavaConverters._
+
+class TestCDCDataFrameSuite extends HoodieClientTestBase {
+
+  var spark: SparkSession = _
+
+  val commonOpts = Map(
+    HoodieTableConfig.CDC_ENABLED.key -> "true",
+    "hoodie.insert.shuffle.parallelism" -> "4",
+    "hoodie.upsert.shuffle.parallelism" -> "4",
+    "hoodie.bulkinsert.shuffle.parallelism" -> "2",
+    "hoodie.delete.shuffle.parallelism" -> "1",
+    RECORDKEY_FIELD.key -> "_row_key",
+    PRECOMBINE_FIELD.key -> "timestamp",
+    HoodieWriteConfig.TBL_NAME.key -> "hoodie_test",
+    HoodieMetadataConfig.COMPACT_NUM_DELTA_COMMITS.key -> "1",
+    HoodieCleanConfig.AUTO_CLEAN.key -> "false"
+  )
+
+  @BeforeEach override def setUp(): Unit = {
+    setTableName("hoodie_test")
+    initPath()
+    initSparkContexts()
+    spark = sqlContext.sparkSession
+    initTestDataGenerator()
+    initFileSystem()
+  }
+
+  @AfterEach override def tearDown(): Unit = {
+    cleanupSparkContexts()
+    cleanupTestDataGenerator()
+    cleanupFileSystem()
+  }
+
+  @ParameterizedTest
+  @CsvSource(Array("cdc_op_key", "cdc_data_before", "cdc_data_before_after"))
+  def testCOWDataSourceWrite(cdcSupplementalLoggingMode: String): Unit = {
+    val options = commonOpts ++ Map(
+      HoodieTableConfig.CDC_SUPPLEMENTAL_LOGGING_MODE.key -> cdcSupplementalLoggingMode
+    )
+
+    // Insert Operation
+    val records1 = recordsToStrings(dataGen.generateInserts("000", 100)).toList
+    val inputDF1 = spark.read.json(spark.sparkContext.parallelize(records1, 2))
+    inputDF1.write.format("org.apache.hudi")
+      .options(options)
+      .mode(SaveMode.Overwrite)
+      .save(basePath)
+
+    // init meta client
+    metaClient = HoodieTableMetaClient.builder()
+      .setBasePath(basePath)
+      .setConf(spark.sessionState.newHadoopConf)
+      .build()
+    val instant1 = metaClient.reloadActiveTimeline.lastInstant().get()
+    assertEquals(spark.read.format("hudi").load(basePath).count(), 100)
+    // all the data is new-coming, it will write out cdc log files.
+    assertFalse(hasCDCLogFile(instant1))
+
+    val schemaResolver = new TableSchemaResolver(metaClient)
+    val dataSchema = schemaResolver.getTableAvroSchema(false)
+    val cdcSchema = HoodieCDCUtils.schemaBySupplementalLoggingMode(
+      HoodieCDCSupplementalLoggingMode.parse(cdcSupplementalLoggingMode), dataSchema)
+
+    // Upsert Operation
+    val records2 = recordsToStrings(dataGen.generateUniqueUpdates("001", 50)).toList
+    val inputDF2 = spark.read.json(spark.sparkContext.parallelize(records2, 2))
+    inputDF2.write.format("org.apache.hudi")
+      .options(options)
+      .mode(SaveMode.Append)
+      .save(basePath)
+    val instant2 = metaClient.reloadActiveTimeline.lastInstant().get()
+    assertEquals(spark.read.format("hudi").load(basePath).count(), 100)
+
+    // part of data are updated, it will write out cdc log files
+    assertTrue(hasCDCLogFile(instant2))
+    val cdcData2 = getCDCLogFIle(instant2).flatMap(readCDCLogFile(_, cdcSchema))
+    assertEquals(cdcData2.size, 50)

Review Comment:
   Let's make sure we add test (either modifying this one or adding a new one) that will be asserting log-files contents as well



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