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https://issues.apache.org/jira/browse/SPARK-30996?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-30996:
------------------------------------
Assignee: Apache Spark
> Able to write parquet file subsequently unable to read
> ------------------------------------------------------
>
> Key: SPARK-30996
> URL: https://issues.apache.org/jira/browse/SPARK-30996
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.4.4
> Environment: spark-shell 2.4.4
> Reporter: Nathan Grand
> Assignee: Apache Spark
> Priority: Major
>
> {code:java}
> case class StructKey(i: Int)
> case class StructValue(l: Long)
> case class Outer(m: Map[StructKey, StructValue])
> val data = Seq(Seq(Outer(Map(StructKey(0) -> StructValue(1L)))))
> val ds = data.toDS
> ds.write.mode("overwrite").parquet("ds.parquet")
> val in = spark.read.parquet("ds.parquet")
> ds.printSchema
> root
> |-- value: array (nullable = true)
> | |-- element: struct (containsNull = true)
> | | |-- m: map (nullable = true)
> | | | |-- key: struct
> | | | | |-- i: integer (nullable = false)
> | | | |-- value: struct (valueContainsNull = true)
> | | | | |-- l: long (nullable = false)
> ds.show(false)
> +----------------+
> |value |
> +----------------+
> |[[[[0] -> [1]]]]|
> +----------------+
> in.printSchema
> root
> |-- value: array (nullable = true)
> | |-- element: struct (containsNull = true)
> | | |-- m: map (nullable = true)
> | | | |-- key: struct
> | | | | |-- i: integer (nullable = true)
> | | | |-- value: struct (valueContainsNull = true)
> | | | | |-- l: long (nullable = true)
> in.show(false)
> Caused by: org.apache.spark.sql.AnalysisException: Map key type is expected
> to be a primitive type, but found: required group key {
> required int32 i;
> };
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkConversionRequirement(ParquetSchemaConverter.scala:583)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetToSparkSchemaConverter$$anonfun$convertGroupField$2.apply(ParquetSchemaConverter.scala:228)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetToSparkSchemaConverter$$anonfun$convertGroupField$2.apply(ParquetSchemaConverter.scala:183)
> at scala.Option.fold(Option.scala:158)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetToSparkSchemaConverter.convertGroupField(ParquetSchemaConverter.scala:183)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetToSparkSchemaConverter.convertField(ParquetSchemaConverter.scala:90)
> {code}
> You should not be able to write something you subsequently can't read; if
> attempting to write invalid parquet it should error at write, otherwise it
> should successfully read.
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