vertica select stament with groupby function doesn't work - subquery

Question

The query running well through vertica, but it doesn't work in jdbc "pyspark",
ERROR: Syntax error at or near "\"
Even after removing the \$condtion, it returns
"ERROR: Subquery in FROM must have an alias"
SELECT
min(date(time_stamp)) mindate
,max(date(time_stamp)) maxdate
,count (distinct date(time_stamp)) noofdays
, subscriber
, server_hostname
, sum(bytes_in) DL
, sum(bytes_out) UL
, sum(connections_out) conn
from traffic.stats
where \$CONDITIONS
and SUBSCRIBER like '41601%'
and date(time_stamp) between '2019-01-25' and '2019-01-29'
and signature_service_category = 'Web Browsing'
and (signature_service_name = 'SSL v3'
or signature_service_name = 'HTTP2 over TLS')
and server_hostname not like '%.googleapis.%'
and server_hostname not like '%.google.%'
and server_hostname <> 'doubleclick.net'
and server_hostname <> 'youtube.com'
and server_hostname <> 'googleadservices.com'
and server_hostname <> 'app-measurement.com'
and server_hostname <> 'gstatic.com'
and server_hostname <> 'googlesyndication.com'
and server_hostname <> 'google-analytics.com'
and server_hostname <> 'googleusercontent.com'
and server_hostname <> 'ggpht.com'
and server_hostname <> 'googletagmanager.com'
and server_hostname is not null
group by subscriber, server_hostname
I have tried the above query on pyspark 1.6
from pyspark import SparkContext, SparkConf
from pyspark.sql import functions as F
from pyspark.sql.types import StructType
from pyspark.sql.types import StructField
from pyspark.sql.types import StringType, IntegerType
from pyspark.sql import SQLContext, Row
from pyspark.storagelevel import StorageLevel
from pyspark.streaming import DStream
from pyspark.streaming.dstream import TransformedDStream
from pyspark.streaming.util import TransformFunction
from pyspark.rdd import RDD
from pyspark.sql import *
from pyspark.sql import SQLContext
from datetime import datetime
from pyspark.sql.types import DateType
from dateutil.parser import parse
from datetime import timedelta
from pyspark.sql import HiveContext
import string
import re
import sys,os
import pandas
conf = (SparkConf()
.setAppName("hivereader")
.setMaster("yarn-client")
.set("spark.dynamicAllocation.enabled", "false")
.set("spark.shuffle.service.enabled", "false")
.set("spark.io.compression.codec", "snappy")
.set("spark.rdd.compress", "true")
.set("spark.executor.instances", 7)
.set("spark.executor.cores" , 7)
.set("spark.sql.inMemoryStorage.compressed", "true")
.set("spark.sql.tungsten.enabled" , 'true')
.set("spark.port.maxRetries" , 200)
)
sc = SparkContext(conf=conf)
sqlContext = SQLContext(sc)
url = "jdbc:vertica*****************"
properties = {
"user": "********",
"password": "******",
"driver": "com.vertica.jdbc.Driver"
}
query = "SELECT MIN(date(time_stamp)) mindate, MAX(date(time_stamp)) maxdate,COUNT (distinct date(time_stamp)) noofdays, subscriber, server_hostname, SUM(bytes_in) DL, SUM(bytes_out) UL, SUM(connections_out) conn FROM traffic.stats t WHERE SUBSCRIBER LIKE '41601%' AND date(time_stamp) between '2019-01-25' and '2019-01-29'AND signature_service_category = 'Web Browsing' AND signature_service_name IN ('SSL v3', 'HTTP2 over TLS')AND server_hostname IS NOT NULL AND server_hostname NOT LIKE '%.googleapis.%' AND server_hostname NOT LIKE '%.google.%' AND server_hostname NOT IN ( 'doubleclick.net', 'youtube.com', 'googleadservices.com', 'app-measurement.com', 'gstatic.com', 'googlesyndication.com', 'google-analytics.com', 'googleusercontent.com', 'ggpht.com', 'googletagmanager.com') GROUP BY subscriber, server_hostname"
df = sqlContext.read.format("JDBC").options(
url = url,
dbtable="( " + query + " ) as temp",
**properties
).load()
df.show(50)
at the end of the query I have added "as x" and at the beginning "select * from(normal query)" its worked but without showing any result , spark 1.6 doesn't allow us to use direct query that's why I have tried to as temp db.table