是否可以在impala中同时执行多个查询?如果是,impala如何处理它?</ p>
答案 0 :(得分:1)
Impala可以同时执行多个查询,只要它没有达到内存上限。
答案 1 :(得分:1)
您可以发出类似impala-shell -f <<file_name>>
的命令,其中文件有多个查询,每个查询用分号分隔(;)
答案 2 :(得分:1)
如果你是一个python极客,你甚至可以尝试使用impyla包创建多个连接并立即运行所有查询。
pip install impyla
答案 3 :(得分:1)
我肯定会自己做一些测试,但是我无法执行多个查询: 我正在使用Impala连接,并从.sql文件中读取查询。这适用于单个命令。
from impala.dbapi import connect
# actual server and port changed for this post for security
conn=connect(host='impala server', port=11111,auth_mechanism="GSSAPI")
cursor = conn.cursor()
cursor.execute((open("sandbox/z_temp.sql").read()))
这是我收到的错误。
HiveServer2Error: AnalysisException: Syntax error in line 2:
这就是SQL在.sql文件中的样子。
Select * FROM database1.table1;
Select * FROM database1.table2;
我能够在单独的.sql文件中使用SQL命令运行多个命令,迭代指定文件夹中的所有.sql文件。
#Create list of file names for recon .sql files this will be sorted
#Numbers at begining of filename are important to sort so that files will be executed in correct order
file_names = glob.glob('folder/.sql')
asc_names = sorted(file_names, reverse = False)
filename = ""
for file_name in asc_names:
str_filename = str(file_name)
print(filename)
query = (open(str_filename).read())
cursor = conn.cursor()
# creates an error log dataframe to print, or write to file at end of job.
try:
# Each SQL command must be executed seperately
cursor.execute(query)
df_id= pd.DataFrame([{'test_name': str_filename[-40:], 'test_status': 'PASS'}])
df_log = df_log.append(df_id, ignore_index=True)
except:
df_id= pd.DataFrame([{'test_name': str_filename[-40:], 'test_status': 'FAIL'}])
df_log = df_log.append(df_id, ignore_index=True)
continue
另一种方法是将一个.sql文件中的所有SQL语句分隔开;然后循环通过.sql文件拆分语句;一次运行一个。
from impala.dbapi import connect
from impala.util import as_pandas
conn=connect(host='impalaserver', port=11111, auth_mechanism='GSSAPI')
cursor = conn.cursor()
# split SQL statements from one file seperated by ';', Note: last command will not have semicolon at end.
sql_file = open("sandbox/temp.sql").read()
sql = sql_file.split(';')
for cmd in sql:
# This gets rid of the non printing characters you may have
cmd = cmd.replace('/r','')
cmd = cmd.replace('/n','')
# This runs your SQL commands one at a time.
cursor.execute(cmd)
print(cmd)