找到了一种通过 Spark ```
data = sqlContext.sql("SELECT * FROM orc.<HDFS_path>");
data.printSchema()

这将以下面的格式打印输出，即我想从hdfs上的orc文件中提取的信息：

root
|-- <column_name1>: (nullable = <true/false>)
|-- <column_name2>: (nullable = <true/false>)
|-- <column_name3>: (nullable = <true/false>)
|-- <column_name4>: (nullable = <true/false>)
|-- <column_name5>: (nullable = <true/false>)

Hive兽人转储命令将解决你的目的

hive --orcfiledump /DATA/UNIVERSITY/DEPT/STUDENT/part-00000

您将获得列、它们的类型、最小值、最大值、计数或记录以及其他更多的统计信息，如下所示

Rows: 6 .
Compression: ZLIB .
Compression size: 262144 .
Type: struct<_col0:string,_col1:string> .

Stripe Statistics:
Stripe 1:
Column 0: count: 6 .
Column 1: count: 6 min: abc max: mno sum: 17 .
Column 2: count: 6 min: def max: tre sum: 18 .

File Statistics:
Column 0: count: 6 .
Column 1: count: 6 min: abc max: mno sum: 17 .
Column 2: count: 6 min: def max: tre sum: 18 .

Stripes:
Stripe: offset: 3 data: 58 rows: 6 tail: 49 index: 67 .
Stream: column 0 section ROW_INDEX start: 3 length 9 .
Stream: column 1 section ROW_INDEX start: 12 length 29 .
Stream: column 2 section ROW_INDEX start: 41 length 29 .
Stream: column 1 section DATA start: 70 length 20 .
Stream: column 1 section LENGTH start: 90 length 12 .
Stream: column 2 section DATA start: 102 length 21 .
Stream: column 2 section LENGTH start: 123 length 5 .
Encoding column 0: DIRECT .
Encoding column 1: DIRECT_V2 .
Encoding column 2: DIRECT_V2 .