Python Pyspark-Unicodeincoder错误:';ascii';编解码器可以';t编码字符'\ufffd&x27;位置124:序号不在范围内(128)
当我尝试使用以下代码在终端上显示spark数据帧时,我得到了“UnicodeEncodeError”:Python Pyspark-Unicodeincoder错误:';ascii';编解码器可以';t编码字符'\ufffd&x27;位置124:序号不在范围内(128),python,pyspark,unicode,encoding,non-ascii-characters,Python,Pyspark,Unicode,Encoding,Non Ascii Characters,当我尝试使用以下代码在终端上显示spark数据帧时,我得到了“UnicodeEncodeError”: from pyspark.sql.types import StructType,StructField, StringType, IntegerType import pyspark from elasticsearch import Elasticsearch from elasticsearch.exceptions import NotFoundError ### Creating S
from pyspark.sql.types import StructType,StructField, StringType, IntegerType
import pyspark
from elasticsearch import Elasticsearch
from elasticsearch.exceptions import NotFoundError
### Creating Spark Session
spark = SparkSession \
.builder \
.appName("test") \
.config("spark.executor.heartbeatInterval","60s") \
.getOrCreate()
spark.conf.set('spark.sql.session.timeZone', 'UTC')
spark.sparkContext.setLogLevel("ERROR")
es_server_ip = "elasticsearch"
es_server_port = "9200"
es_conn = Elasticsearch("http://user:password@elasticsearch:9200",use_ssl=False,verify_certs=True)
#function to read dataframe from Elastic Search index
def readFromES(esIndex,esQuery):
esDf = spark.read.format("org.elasticsearch.spark.sql") \
.option("es.nodes",es_server_ip ) \
.option("es.port",es_server_port) \
.option("es.net.http.auth.user", "user") \
.option("es.net.http.auth.pass", "password") \
.option("es.net.ssl","false") \
.option("es.net.ssl.cert.allow.self.signed","true") \
.option("es.read.metadata", "false") \
.option("es.mapping.date.rich", "false") \
.option("es.query",esQuery) \
.load(esIndex)
return esDf
#defining the elastic search query
q_ci = """{
"query": {
"match_all": {}
}
}"""
#invoking the function and saving the data to df1
df1 = readFromES("test_delete",q_ci)
df1.show(truncate=False)
错误:
df1.show(truncate=False)文件“/opt/spark/python/lib/pyspark.zip/pyspark/sql/dataframe.py”,第行 382,在show UnicodeEncodeError中:“ascii”编解码器无法对字符进行编码 位置124中的“\ufffd”:序号不在范围内(128) 我需要的输出如下
+--------------------+------+-----+
|hostname |kpi |value|
+--------------------+------+-----+
|host4 |cpu |95 |
|host3 |disk |90 |
|Apr�ngli |cpu |78 |
|host2 |memory|85 |
+--------------------+------+-----+
您可以使用下面的代码模拟数据帧
data1 = [("Apr�ngli","cpu",78),
("host2","memory",85),
("host3","disk",90),
("host4","cpu",95),
]
schema1= StructType([ \
StructField("hostname",StringType(),True), \
StructField("kpi",StringType(),True), \
StructField("value",IntegerType(),True)
])
df1 = spark.createDataFrame(data=data1,schema=schema1)
df1.printSchema()
df1.show(truncate=False)
我采取的步骤:
正如在其他stackoverflow回答中提到的,我做了以下操作,但仍然收到错误
export PYTHONIOENCODING=utf8
版本详情:
PYTHON_VERSION=3.6.8
Spark version 2.4.5
这是PySpark特有的吗?或者如果执行
打印('\ufffd')
,您是否会收到相同的异常?如果执行打印('\ufffd'),我会收到相同的错误。顺便说一句,仅供参考-我正在使用spark提交命令提交代码。\ufffd
是�(替换字符)�ngli“
。修复它并将脚本保存在utf-8中(可能使用兼行#-*-编码:utf-8-*-
)。@JosefZ实际上是这个角色� 来自弹性搜索。为了在这里进行模拟,我创建了一个数据帧。?