将 数据从数据库 直接通过 pyspark 读入到dataframe

from pyspark.sql import SparkSession
spark = SparkSession \
    .builder \
    .appName("Python Spark SQL basic example") \
    .master("local") \
    .enableHiveSupport() \
    .getOrCreate()
#try:
result = spark.sql("select * from dev.dev_jiadian_user_yuge limit 10")
#result.collect()
result.show()
#finally:
#    spark.stop()
#print "ends..."

+----------------+------------------+
|   user_log_acct|             label|
+----------------+------------------+
|    342523ZMD003|0.8407951425388679|
|        流行你的时尚潮流|0.8156848188447681|
|      a564494278|0.8128615895945835|
|jd_6381a0e5b63b5|0.7818056689527976|
|    weixiong07_m|0.7807439055758115|
|jd_56a7706a16617|0.7531679395767472|
|     long4868632|0.7504257196976702|
|        huanyi25| 0.745658097419349|
|         雪域翔鹰163|0.7359140647098181|
|          wjl368|0.7340991987507084|
+----------------+------------------+

result
result.take(5)
[Row(user_log_acct=u'342523ZMD003', label=0.8407951425388679),
 Row(user_log_acct=u'\u6d41\u884c\u4f60\u7684\u65f6\u5c1a\u6f6e\u6d41', label=0.8156848188447681),
 Row(user_log_acct=u'a564494278', label=0.8128615895945835),
 Row(user_log_acct=u'jd_6381a0e5b63b5', label=0.7818056689527976),
 Row(user_log_acct=u'weixiong07_m', label=0.7807439055758115)]

df
import pandas as pd
x = pd.DataFrame(result.take(5), columns=result.columns)

x
user_log_acct	label
0	342523ZMD003	0.840795
1	流行你的时尚潮流	0.815685
2	a564494278	0.812862
3	jd_6381a0e5b63b5	0.781806
4	weixiong07_m	0.780744