Apache-Drill 查询镶木地板文件：镶木地板记录读取器出错

我使用 Pyarrow 创建了一个镶木地板文件，可以使用 Pyspark 查询它。然而，它不能使用最近安装的 Apache-drill(1.14) 进行查询，它可以处理其他数据格式，包括 csv、json 和 RDB。有人可以帮助我解决问题所在，我该如何解决？谢谢！

（我能够运行 count(*) 查询，但无法运行下面的查询）

这是我的查询和错误消息：

select * from dfs.`C:/Apache_Spark/sample_Sends_2017.parquet` limit 20;

查询执行失败

原因：

SQL Error: INTERNAL_ERROR ERROR: Error in parquet record reader.
Message: Failure in setting up reader
Parquet Metadata: ParquetMetaData{FileMetaData{schema: message schema {
optional int64 SendsID;
optional int64 SendJobsID;
optional int64 SendID;
optional binary EncryptIndivID (UTF8);
optional int64 SendDate (TIMESTAMP_MICROS);
optional int64 __index_level_0__;
}

, metadata: {pandas={"index_columns": ["__index_level_0__"], "column_indexes": [{"name": null, "field_name": null, "pandas_type": "unicode", "numpy_type": "object", "metadata": {"encoding": "UTF-8"}}], "columns": [{"name": "SendsID", "field_name": "SendsID", "pandas_type": "int64", "numpy_type": "int64", "metadata": null}, {"name": "SendJobsID", "field_name": "SendJobsID", "pandas_type": "int64", "numpy_type": "int64", "metadata": null}, {"name": "SendID", "field_name": "SendID", "pandas_type": "int64", "numpy_type": "int64", "metadata": null}, {"name": "EncryptIndivID", "field_name": "EncryptIndivID", "pandas_type": "unicode", "numpy_type": "object", "metadata": null}, {"name": "SendDate", "field_name": "SendDate", "pandas_type": "datetime", "numpy_type": "datetime64[ns]", "metadata": null}, {"name": null, "field_name": "__index_level_0__", "pandas_type": "int64", "numpy_type": "int64", "metadata": null}], "pandas_version": "0.23.0"}}}, blocks: [BlockMetaData{1000, 46321 [ColumnMetaData{SNAPPY [SendsID] optional int64 SendsID  [PLAIN_DICTIONARY, RLE, PLAIN], 4917}, ColumnMetaData{SNAPPY [SendJobsID] optional int64 SendJobsID  [PLAIN_DICTIONARY, RLE, PLAIN], 6342}, ColumnMetaData{SNAPPY [SendID] optional int64 SendID  [PLAIN_DICTIONARY, RLE, PLAIN], 6568}, ColumnMetaData{SNAPPY [EncryptIndivID] optional binary EncryptIndivID (UTF8)  [PLAIN_DICTIONARY, RLE, PLAIN], 39530}, ColumnMetaData{SNAPPY [SendDate] optional int64 SendDate (TIMESTAMP_MICROS)  [PLAIN_DICTIONARY, RLE, PLAIN], 41195}, ColumnMetaData{SNAPPY [__index_level_0__] optional int64 __index_level_0__  [PLAIN_DICTIONARY, RLE, PLAIN], 45450}]}]}
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