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https://issues.apache.org/jira/browse/SPARK-35461?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17348667#comment-17348667
]
Chao Sun commented on SPARK-35461:
----------------------------------
Actually this also fails when turning off the vectorized reader:
{code}
Caused by: java.lang.ClassCastException: class
org.apache.spark.sql.catalyst.expressions.MutableLong cannot be cast to class
org.apache.spark.sql.catalyst.expressions.MutableInt
(org.apache.spark.sql.catalyst.expressions.MutableLong and
org.apache.spark.sql.catalyst.expressions.MutableInt are in unnamed module of
loader 'app')
at
org.apache.spark.sql.catalyst.expressions.SpecificInternalRow.setInt(SpecificInternalRow.scala:253)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$RowUpdater.setInt(ParquetRowConverter.scala:178)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetPrimitiveConverter.addInt(ParquetRowConverter.scala:88)
at
org.apache.parquet.column.impl.ColumnReaderBase$2$3.writeValue(ColumnReaderBase.java:297)
at
org.apache.parquet.column.impl.ColumnReaderBase.writeCurrentValueToConverter(ColumnReaderBase.java:440)
at
org.apache.parquet.column.impl.ColumnReaderImpl.writeCurrentValueToConverter(ColumnReaderImpl.java:30)
at
org.apache.parquet.io.RecordReaderImplementation.read(RecordReaderImplementation.java:406)
at
org.apache.parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:229)
{code}
In this case parquet-mr is able to return the value but Spark won't be able to
handle it.
> Error when reading dictionary-encoded Parquet int column when read schema is
> bigint
> -----------------------------------------------------------------------------------
>
> Key: SPARK-35461
> URL: https://issues.apache.org/jira/browse/SPARK-35461
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.2, 3.1.1
> Reporter: Chao Sun
> Priority: Major
>
> When reading a dictionary-encoded integer column from a Parquet file, and
> users specify read schema to be bigint, Spark currently will fail with the
> following exception:
> {code}
> java.lang.UnsupportedOperationException:
> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainIntegerDictionary
> at org.apache.parquet.column.Dictionary.decodeToLong(Dictionary.java:49)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToLong(ParquetDictionary.java:50)
> at
> org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getLong(OnHeapColumnVector.java:364)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:344)
> {code}
> To reproduce:
> {code}
> val data = (0 to 10).flatMap(n => Seq.fill(10)(n)).map(i => (i,
> i.toString))
> withParquetFile(data) { path =>
> val readSchema = StructType(Seq(StructField("_1", LongType)))
> spark.read.schema(readSchema).parquet(path).first()
> }
> {code}
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