通过scala/javaapi，我们可以访问hivemetastore并获得分区列名org.apache.hadoop.hive.metastore.hivemetastoreclient

val conf = new Configuration()
conf.set("hive.metastore.uris","thrift://hdppmgt02.domain.com:9083")
val hiveConf = new HiveConf(conf, classOf[HiveConf])
val metastoreClient = new HiveMetaStoreClient(hiveConf)

metastoreClient.getTable(db, tbl).getPartitionKeys.foreach(x=>println("Keys : "+x))

# use python pyhive:

import hive_client

def get_partition_column(table_name):
    #hc=hive connection
    hc=hive_client.HiveClient()
    cur=hc.query("desc "+table_name)
    return cur[len(cur)-1][0]

################# 

hive_client.py

from pyhive import hive
default_encoding = 'utf-8'
host_name = 'localhost'
port = 10000
database="xxx"

class HiveClient:
    def __init__(self):
        self.conn = hive.Connection(host=host_name,port=port,username='hive',database=database)
    def query(self, sql):
        cursor = self.conn.cursor()
        #with self.conn.cursor() as cursor:
        cursor.execute(sql)
        return cursor.fetchall()

    def execute(self,sql):
        #with self.conn.cursor() as cursor:
        cursor = self.conn.cursor()
        cursor.execute(sql)

    def close(self):`enter code here`
        self.conn.close()

可能不是最好的方法，但还有一种方法是使用descripe命令
创建表：

create table employee ( id int, name string ) PARTITIONED BY (city string);

命令：

hive -e 'describe formatted employee'  | awk '/Partition/ {p=1}; p; /Detailed/ {p=0}'

输出：

# Partition Information

# col_name              data_type               comment

city                    string

你可以根据需要改进它。
另一个我不得不探索的选项是通过查询元存储库表来获取表的分区列信息。