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fix: Upgrade Spark 3.2.x and 3.3.x and fix parquet schema conversion
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README.md

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@@ -80,7 +80,7 @@ mvn clean javadoc:aggregate -Pjavadocs
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### Build with different Spark versions
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The default Spark 2.x version supported is 2.4.4. The default Spark 3.x version, corresponding to `spark3` profile is 3.3.1.
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The default Spark 2.x version supported is 2.4.4. The default Spark 3.x version, corresponding to `spark3` profile is 3.3.4.
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Refer to the table below for building with different Spark and Scala versions.
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| Maven build options | Expected Spark bundle jar name | Notes |

hudi-spark-datasource/hudi-spark3.2plus-common/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/Spark32PlusHoodieParquetFileFormat.scala

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@@ -95,6 +95,9 @@ class Spark32PlusHoodieParquetFileFormat(private val shouldAppendPartitionValues
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hadoopConf.setBoolean(
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SQLConf.PARQUET_INT96_AS_TIMESTAMP.key,
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sparkSession.sessionState.conf.isParquetINT96AsTimestamp)
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hadoopConf.setBoolean(
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SQLConf.LEGACY_PARQUET_NANOS_AS_LONG.key,
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sparkSession.sessionState.conf.legacyParquetNanosAsLong)
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val internalSchemaStr = hadoopConf.get(SparkInternalSchemaConverter.HOODIE_QUERY_SCHEMA)
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// For Spark DataSource v1, there's no Physical Plan projection/schema pruning w/in Spark itself,

pom.xml

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<flink.hadoop.compatibility.artifactId>flink-hadoop-compatibility_2.12</flink.hadoop.compatibility.artifactId>
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<rocksdbjni.version>5.17.2</rocksdbjni.version>
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<spark31.version>3.1.3</spark31.version>
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<spark32.version>3.2.3</spark32.version>
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<spark33.version>3.3.1</spark33.version>
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<spark32.version>3.2.4</spark32.version>
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<spark33.version>3.3.4</spark33.version>
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<hudi.spark.module>hudi-spark2</hudi.spark.module>
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<!-- NOTE: Different Spark versions might require different number of shared
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modules being incorporated, hence we're creating multiple placeholders

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