python - CSV转换为带有python SerializationError的elasticsearch

当我尝试将bulk_data发送到本地elasticsearch时，由于SerializationError导致未加载我的数据。
我已经尝试填充csv文件中的空白单元格，但这不是解决方案。

from elasticsearch import Elasticsearch

bulk_data = []
header = []
count = 0
for row in csv_file_object:
    if count > 0 :
        data_dict = {}
        for i in range(len(row)):
            row = row.rstrip()
            data_dict[header[i]] = row[i]
        op_dict = {
            "index": {
                "_index": INDEX_NAME,
                "_type": TYPE_NAME,
            }
        }
        bulk_data.append(op_dict)
        bulk_data.append(data_dict)
    else:
        header = row
    count = count+1

# create ES client, create index
es = Elasticsearch(hosts = [ES_HOST])
if es.indices.exists(INDEX_NAME):
    print("deleting '%s' index..." % (INDEX_NAME))
    res = es.indices.delete(index = INDEX_NAME)

res = es.bulk(index = INDEX_NAME, body = bulk_data, refresh = True)

请参阅图像以获取SerializationError和bulk_data值:

请注意:\ n由序列化过程本身添加。

最佳答案

我试图回复您，但我听不懂一件事。如何从数据中检索字段名称？在您的代码中，我看到您从名为header的列表中检索到它为空？我不明白您如何看待这个值(value)。.检查我的答案我不知道我是否理解得很好

from elasticsearch import Elasticsearch
from elasticsearch import helpers


index_name = "your_index_name"
doc_type = "your_doc_type"
esConnector = Elasticsearch(["http://192.168.1.1:9200/"])
# change your ip here
count = 0

def generate_data(csv_file_object)
    with open(csv_file_object, "r") as f:
        for line in f:
           line = line.split(",").rstrip()
           data_dict = {header[count]: line}
           obj={
            '_op_type': 'index',
            '_index': index_name,
            '_type': doc_type,
            '_id': count+1,
            '_source': data_dict
                }
            count +=1
            yield obj


for success, info in helpers.parallel_bulk(client=esConnector, actions=generate_data(csv_file_object), thread_count=4):
    if not success:
        print 'Doc failed', info

关于python - CSV转换为带有python SerializationError的elasticsearch，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/50002053/