适用于不同类型映射器的Django Elasticsearch DSL TransportError

时间:2018-11-14 06:34:17

标签: python django elasticsearch elasticsearch-dsl elasticsearch-dsl-py

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!

1 个答案:

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。