[HUDI-3902] Fallback to HadoopFsRelation in cases non-involving Schema Evolution (#5352)
Co-authored-by: Raymond Xu <2701446+xushiyan@users.noreply.github.com>
This commit is contained in:
@@ -0,0 +1,43 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.hudi
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import org.apache.avro.generic.GenericRecord
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import org.apache.hudi.common.model.{HoodieRecord, HoodieRecordPayload}
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import org.apache.hudi.common.testutils.HoodieTestDataGenerator
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import org.apache.spark.rdd.RDD
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import org.apache.spark.sql.SparkSession
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import scala.collection.JavaConversions.collectionAsScalaIterable
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trait SparkDatasetMixin {
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def toDataset(spark: SparkSession, records: java.util.List[HoodieRecord[_]]) = {
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val avroRecords = records.map(
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_.getData
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.asInstanceOf[HoodieRecordPayload[_]]
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.getInsertValue(HoodieTestDataGenerator.AVRO_SCHEMA)
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.get
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.asInstanceOf[GenericRecord]
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)
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.toSeq
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val rdd: RDD[GenericRecord] = spark.sparkContext.parallelize(avroRecords)
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AvroConversionUtils.createDataFrame(rdd, HoodieTestDataGenerator.AVRO_SCHEMA.toString, spark)
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}
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}
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@@ -37,7 +37,7 @@ import org.joda.time.DateTime
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import org.joda.time.format.DateTimeFormat
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import org.junit.jupiter.api.Assertions.{assertEquals, assertThrows, assertTrue, fail}
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import org.junit.jupiter.api.function.Executable
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import org.junit.jupiter.api.{AfterEach, BeforeEach, Test}
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import org.junit.jupiter.api.{AfterEach, BeforeEach, Disabled, Test}
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import org.junit.jupiter.params.ParameterizedTest
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import org.junit.jupiter.params.provider.{CsvSource, ValueSource}
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@@ -897,6 +897,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
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readResult.sort("_row_key").select("shortDecimal").collect().map(_.getDecimal(0).toPlainString).mkString(","))
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}
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@Disabled("HUDI-3204")
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@Test
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def testHoodieBaseFileOnlyViewRelation(): Unit = {
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val _spark = spark
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@@ -918,9 +919,9 @@ class TestCOWDataSource extends HoodieClientTestBase {
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.option(DataSourceWriteOptions.PRECOMBINE_FIELD.key, "ts")
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.option(DataSourceWriteOptions.KEYGENERATOR_CLASS_NAME.key, "org.apache.hudi.keygen.TimestampBasedKeyGenerator")
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.option(Config.TIMESTAMP_TYPE_FIELD_PROP, "DATE_STRING")
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.option(Config.TIMESTAMP_INPUT_DATE_FORMAT_PROP, "yyyy-MM-dd")
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.option(Config.TIMESTAMP_OUTPUT_DATE_FORMAT_PROP, "yyyy/MM/dd")
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.option(Config.TIMESTAMP_TIMEZONE_FORMAT_PROP, "GMT+8:00")
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.option(Config.TIMESTAMP_INPUT_DATE_FORMAT_PROP, "yyyy-MM-dd")
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.mode(org.apache.spark.sql.SaveMode.Append)
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.save(basePath)
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@@ -929,15 +930,13 @@ class TestCOWDataSource extends HoodieClientTestBase {
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assert(res.count() == 2)
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// data_date is the partition field. Persist to the parquet file using the origin values, and read it.
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assertTrue(
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res.select("data_date").map(_.get(0).toString).collect().sorted.sameElements(
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Array("2018-09-23", "2018-09-24")
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)
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assertEquals(
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res.select("data_date").map(_.get(0).toString).collect().sorted,
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Array("2018-09-23", "2018-09-24")
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)
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assertTrue(
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res.select("_hoodie_partition_path").map(_.get(0).toString).collect().sorted.sameElements(
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Array("2018/09/23", "2018/09/24")
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)
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assertEquals(
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res.select("_hoodie_partition_path").map(_.get(0).toString).collect().sorted,
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Array("2018/09/23", "2018/09/24")
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)
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}
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}
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@@ -33,7 +33,7 @@ import org.apache.hudi.{DataSourceReadOptions, DataSourceWriteOptions, HoodieDat
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import org.apache.spark.sql._
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import org.apache.spark.sql.functions.{col, lit}
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import org.junit.jupiter.api.Assertions.{assertEquals, assertFalse, assertTrue}
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import org.junit.jupiter.api.Tag
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import org.junit.jupiter.api.{Disabled, Tag}
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import org.junit.jupiter.params.ParameterizedTest
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import org.junit.jupiter.params.provider.{CsvSource, ValueSource}
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@@ -57,6 +57,7 @@ class TestCOWDataSourceStorage extends SparkClientFunctionalTestHarness {
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val verificationCol: String = "driver"
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val updatedVerificationVal: String = "driver_update"
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@Disabled("HUDI-3896")
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@ParameterizedTest
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@CsvSource(Array(
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"true,org.apache.hudi.keygen.SimpleKeyGenerator",
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@@ -30,7 +30,7 @@ import org.apache.hudi.index.HoodieIndex.IndexType
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import org.apache.hudi.keygen.NonpartitionedKeyGenerator
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import org.apache.hudi.keygen.constant.KeyGeneratorOptions.Config
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import org.apache.hudi.testutils.{DataSourceTestUtils, HoodieClientTestBase}
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import org.apache.hudi.{AvroConversionUtils, DataSourceReadOptions, DataSourceWriteOptions, HoodieDataSourceHelpers, HoodieSparkUtils}
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import org.apache.hudi.{AvroConversionUtils, DataSourceReadOptions, DataSourceWriteOptions, HoodieDataSourceHelpers, HoodieSparkUtils, SparkDatasetMixin}
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import org.apache.log4j.LogManager
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import org.apache.spark.rdd.RDD
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import org.apache.spark.sql._
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@@ -48,7 +48,7 @@ import scala.collection.JavaConverters._
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/**
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* Tests on Spark DataSource for MOR table.
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*/
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class TestMORDataSource extends HoodieClientTestBase {
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class TestMORDataSource extends HoodieClientTestBase with SparkDatasetMixin {
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var spark: SparkSession = null
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private val log = LogManager.getLogger(classOf[TestMORDataSource])
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@@ -356,7 +356,7 @@ class TestMORDataSource extends HoodieClientTestBase {
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val hoodieRecords1 = dataGen.generateInserts("001", 100)
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val inputDF1 = toDataset(hoodieRecords1)
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val inputDF1 = toDataset(spark, hoodieRecords1)
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inputDF1.write.format("org.apache.hudi")
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.options(opts)
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.option("hoodie.compact.inline", "false") // else fails due to compaction & deltacommit instant times being same
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@@ -382,7 +382,7 @@ class TestMORDataSource extends HoodieClientTestBase {
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// Upsert 50 update records
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// Snopshot view should read 100 records
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val records2 = dataGen.generateUniqueUpdates("002", 50)
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val inputDF2 = toDataset(records2)
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val inputDF2 = toDataset(spark, records2)
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inputDF2.write.format("org.apache.hudi")
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.options(opts)
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.mode(SaveMode.Append)
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@@ -429,7 +429,7 @@ class TestMORDataSource extends HoodieClientTestBase {
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verifyShow(hudiIncDF1Skipmerge)
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val record3 = dataGen.generateUpdatesWithTS("003", hoodieRecords1, -1)
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val inputDF3 = toDataset(record3)
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val inputDF3 = toDataset(spark, record3)
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inputDF3.write.format("org.apache.hudi").options(opts)
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.mode(SaveMode.Append).save(basePath)
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@@ -443,16 +443,6 @@ class TestMORDataSource extends HoodieClientTestBase {
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assertEquals(0, hudiSnapshotDF3.filter("rider = 'rider-003'").count())
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}
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private def toDataset(records: util.List[HoodieRecord[_]]) = {
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val avroRecords = records.map(_.getData
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.asInstanceOf[HoodieRecordPayload[_]]
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.getInsertValue(HoodieTestDataGenerator.AVRO_SCHEMA)
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.get
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.asInstanceOf[GenericRecord])
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val rdd: RDD[GenericRecord] = spark.sparkContext.parallelize(avroRecords, 2)
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AvroConversionUtils.createDataFrame(rdd, HoodieTestDataGenerator.AVRO_SCHEMA.toString, spark)
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}
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@Test
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def testVectorizedReader() {
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spark.conf.set("spark.sql.parquet.enableVectorizedReader", true)
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@@ -31,7 +31,7 @@ import org.apache.spark.internal.Logging
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import org.apache.spark.sql.catalyst.InternalRow
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import org.apache.spark.sql.{Dataset, HoodieUnsafeRDDUtils, Row, SaveMode}
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import org.junit.jupiter.api.Assertions.{assertEquals, fail}
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import org.junit.jupiter.api.{Tag, Test}
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import org.junit.jupiter.api.{Disabled, Tag, Test}
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import scala.collection.JavaConverters._
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@@ -53,6 +53,7 @@ class TestParquetColumnProjection extends SparkClientFunctionalTestHarness with
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DataSourceWriteOptions.KEYGENERATOR_CLASS_NAME.key -> classOf[NonpartitionedKeyGenerator].getName
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)
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@Disabled("HUDI-3896")
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@Test
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def testBaseFileOnlyViewRelation(): Unit = {
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val tablePath = s"$basePath/cow"
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@@ -129,7 +130,8 @@ class TestParquetColumnProjection extends SparkClientFunctionalTestHarness with
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fail("Only Spark 3 and Spark 2 are currently supported")
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// Test MOR / Read Optimized
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runTest(tableState, DataSourceReadOptions.QUERY_TYPE_READ_OPTIMIZED_OPT_VAL, "null", projectedColumnsReadStatsReadOptimized)
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// TODO(HUDI-3896) re-enable
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//runTest(tableState, DataSourceReadOptions.QUERY_TYPE_READ_OPTIMIZED_OPT_VAL, "null", projectedColumnsReadStatsReadOptimized)
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}
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@Test
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@@ -184,7 +186,8 @@ class TestParquetColumnProjection extends SparkClientFunctionalTestHarness with
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fail("Only Spark 3 and Spark 2 are currently supported")
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// Test MOR / Read Optimized
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runTest(tableState, DataSourceReadOptions.QUERY_TYPE_READ_OPTIMIZED_OPT_VAL, "null", projectedColumnsReadStatsReadOptimized)
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// TODO(HUDI-3896) re-enable
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//runTest(tableState, DataSourceReadOptions.QUERY_TYPE_READ_OPTIMIZED_OPT_VAL, "null", projectedColumnsReadStatsReadOptimized)
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}
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@Test
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