我正在使用Python(3.6),Django(2.1),ElasticSearch(5.1.1)和Elasticsearch-dsl(5.4.0)开发一个项目,在其中我需要实现搜索功能。
这是我尝试过的:
来自models.py:
class searchdatamodel(models.Model):
id = models.IntegerField(null=False, primary_key=True)
company_name = models.TextField(blank=True, null=True)
city = models.TextField(blank=True, null=True)
state = models.TextField(blank=True, null=True)
zip_codes = models.TextField(blank=True, null=True)
street_address = models.TextField(blank=True, null=True)
street_address_zip = models.TextField(blank=True, null=True)
county = models.TextField(blank=True, null=True)
phone_number = models.DecimalField(max_digits=65535, decimal_places=65535, blank=True, null=True)
fax_number = models.DecimalField(max_digits=65535, decimal_places=65535, blank=True, null=True)
web_address = models.TextField(blank=True, null=True)
last_name = models.TextField(blank=True, null=True)
first_name = models.TextField(blank=True, null=True)
contact_title = models.TextField(blank=True, null=True)
contact_gender = models.TextField(blank=True, null=True)
actual_employee_size = models.IntegerField(blank=True, null=True)
employee_size_range = models.TextField(blank=True, null=True)
actual_sales_volume = models.IntegerField(blank=True, null=True)
sales_volume_range = models.TextField(blank=True, null=True)
primary_sic = models.IntegerField(blank=True, null=True)
primary_sic_description = models.TextField(blank=True, null=True)
secondary_sic_1 = models.IntegerField(blank=True, null=True)
secondary_sic_description_1 = models.TextField(blank=True, null=True)
secondary_sic_2 = models.IntegerField(blank=True, null=True)
secondary_sic_description_2 = models.TextField(blank=True, null=True)
credit_alpha_score = models.TextField(blank=True, null=True)
credit_numeric_score = models.IntegerField(blank=True, null=True)
headquarters_branch = models.TextField(blank=True, null=True)
square_footage = models.TextField(blank=True, null=True)
registry_date = models.IntegerField(blank=True, null=True)
class Meta:
managed = False
db_table = 'searchdatamodel'
# Implement indexing for SearchDataModel model
def indexing(self):
SearchDataIndex.init()
obj = SearchDataIndex(
id=self.id,
company_name=self.company_name,
city=self.city,
state=self.state,
zip_code=self.zip_codes,
street_address=self.street_address,
street_address_zip=self.street_address_zip,
county=self.county,
phone_number=self.phone_number,
fax_number=self.fax_number,
web_address=self.web_address,
last_name=self.last_name,
first_name=self.first_name,
contact_title=self.contact_title,
contact_gender=self.contact_gender,
actual_employee_size=self.actual_employee_size,
actual_sales_volume=self.actual_sales_volume,
primary_sic=self.primary_sic,
primary_sic_description=self.primary_sic_description,
registry_date=self.registry_date
)
obj.save()
return obj.to_dict(include_meta=True)
来自serach.py:
class SearchDataIndex(DocType):
id = Integer()
company_name = Text()
city = Text()
state = Text()
zip_codes = Text()
street_address = Text()
street_address_zip = Integer()
county = Text()
phone_number = Text()
fax_number = Text()
web_address = Text()
last_name = Text()
first_name = Text()
contact_title = Text()
contact_gender = Text()
actual_employee_size = Integer()
actual_sales_volume = Text()
primary_sic = Text()
primary_sic_description = Text()
registry_date = Date()
class Meta:
index = 'data-search'
# A method for bulk indexing
def bulk_indexing():
SearchDataIndex.init()
es = Elasticsearch()
bulk(client=es, actions=(b.indexing() for b in
models.searchdatamodel.objects.all().iterator()))
当我尝试运行bulk_indexing函数时,它返回如下错误:
文件“ /Users/abdul/PycharmProjects/Dmitry/DVirEnv/lib/python3.6/site-packages/elasticsearch/connection/base.py”,第125行,位于_raise_error中 引发HTTP_EXCEPTIONS.get(状态代码,传输错误)(状态代码,错误消息,其他信息)
elasticsearch.exceptions.RequestError:TransportError(400,'illegal_argument_exception','不同类型的映射器[zip_codes],current_type [integer],merged_type [text]')
我尝试通过将模型中的zip_code
类型更改为IntegerField
来尝试,但是没有成功。
这有什么问题吗?
谢谢!
答案 0 :(得分:0)
不幸的是,您不能像这样更改类型。您必须重新映射索引,只需删除索引,然后再次运行映射函数即可。
要删除索引,请运行
es = Elasticsearch()
es.indices.delete(index='data-search')
然后通过再次运行批量索引器来映射索引。
注意:任何现有数据都将保留旧的数据类型,因此,如果您需要保存数据但更改数据类型,则这与蠕虫完全不同,其中包括制作新版本的索引并读取旧数据。