使用 PostgreSQL 索引的 Django 全文搜索

Question

解决了我在this question中询问的问题后，我正在尝试使用索引优化 FTS 的性能。我在我的数据库上发出命令：

CREATE INDEX my_table_idx ON my_table USING gin(to_tsvector('italian', very_important_field), to_tsvector('italian', also_important_field), to_tsvector('italian', not_so_important_field), to_tsvector('italian', not_important_field), to_tsvector('italian', tags));

然后我编辑了模型的 Meta class 如下：

class MyEntry(models.Model):
    very_important_field = models.TextField(blank=True, null=True)
    also_important_field = models.TextField(blank=True, null=True)
    not_so_important_field = models.TextField(blank=True, null=True)
    not_important_field = models.TextField(blank=True, null=True)
    tags = models.TextField(blank=True, null=True)

    class Meta:
        managed = False
        db_table = 'my_table'
        indexes = [
            GinIndex(
                fields=['very_important_field', 'also_important_field', 'not_so_important_field', 'not_important_field', 'tags'],
                name='my_table_idx'
            )
        ]

但似乎什么都没有改变。查找所需的时间与以前完全相同。

这是查找脚本：

from django.contrib.postgres.search import SearchQuery, SearchRank, SearchVector

# other unrelated stuff here
vector = SearchVector("very_important_field", weight="A") + \
             SearchVector("tags", weight="A") + \
             SearchVector("also_important_field", weight="B") + \
             SearchVector("not_so_important_field", weight="C") + \
             SearchVector("not_important_field", weight="D")
query = SearchQuery(search_string, config="italian")
rank = SearchRank(vector, query, weights=[0.4, 0.6, 0.8, 1.0]). # D, C, B, A
full_text_search_qs = MyEntry.objects.annotate(rank=rank).filter(rank__gte=0.4).order_by("-rank")

我做错了什么？

编辑：

上面的查找包含在一个函数中，我在时间上使用了装饰器。该函数实际上returns一个列表，像这样：

@timeit
def search(search_string):
    # the above code here
    qs = list(full_text_search_qs)
    return qs

这可能是问题所在吗？

Answer 1

我不确定，但根据 postgresql 文档 (https://www.postgresql.org/docs/9.5/static/textsearch-tables.html#TEXTSEARCH-TABLES-INDEX)：

Because the two-argument version of to_tsvector was used in the index above, only a query reference that uses the 2-argument version of to_tsvector with the same configuration name will use that index. That is, WHERE to_tsvector('english', body) @@ 'a & b' can use the index, but WHERE to_tsvector(body) @@ 'a & b' cannot. This ensures that an index will be used only with the same configuration used to create the index entries.

我不知道 django 使用什么配置，但你可以尝试删除第一个参数

Answer 2

您需要将 SearchVectorField 添加到您的 MyEntry，根据您的实际文本字段对其进行更新，然后对该字段执行搜索。但是，更新只能在记录保存到数据库后才能执行。

本质上：

from django.contrib.postgres.indexes import GinIndex
from django.contrib.postgres.search import SearchVector, SearchVectorField

class MyEntry(models.Model):
    # The fields that contain the raw data.
    very_important_field = models.TextField(blank=True, null=True)
    also_important_field = models.TextField(blank=True, null=True)
    not_so_important_field = models.TextField(blank=True, null=True)
    not_important_field = models.TextField(blank=True, null=True)
    tags = models.TextField(blank=True, null=True)

    # The field we actually going to search.
    # Must be null=True because we cannot set it immediately during create()
    search_vector = SearchVectorField(editable=False, null=True)  

    class Meta:
        # The search index pointing to our actual search field.
        indexes = [GinIndex(fields=["search_vector"])]

然后您可以照常创建普通实例，例如：

# Does not set MyEntry.search_vector yet.
my_entry = MyEntry.objects.create(
    very_important_field="something very important",  # Fake Italien text ;-)
    also_important_field="something different but equally important"
    not_so_important_field="this one matters less"
    not_important_field="we don't care are about that one at all"
    tags="things, stuff, whatever"

现在条目已存在于数据库中，您可以使用各种选项更新 search_vector 字段。例如 weight 指定重要性，config 使用一种默认语言配置。您也可以完全省略不想搜索的字段：

# Update search vector on existing database record.
my_entry.search_vector = (
    SearchVector("very_important_field", weight="A", config="italien")
    + SearchVector("also_important_field", weight="A", config="italien")
    + SearchVector("not_so_important_field", weight="C", config="italien")
    + SearchVector("tags", weight="B", config="italien")
)
my_entry.save()

每次某些文本字段更改时手动更新 search_vector 字段可能容易出错，因此您可以考虑添加一个 SQL 触发器来使用 Django 迁移为您执行此操作。有关如何执行此操作的示例，请参阅有关 Full-text Search with Django and PostgreSQL.

的博客文章

要使用索引在 MyEntry 中实际搜索，您需要按 search_vector 字段进行过滤和排名。 SearchQuery 的 config 应与上面的 SearchVector 之一匹配（使用相同的停用词、词干提取等）。

例如：

from django.contrib.postgres.search import SearchQuery, SearchRank
from django.core.exceptions import ValidationError
from django.db.models import F, QuerySet

search_query = SearchQuery("important", search_type="websearch", config="italien")
search_rank = SearchRank(F("search_vector"), search_query)
my_entries_found = (
    MyEntry.objects.annotate(rank=search_rank)
    .filter(search_vector=search_query)  # Perform full text search on index.
    .order_by("-rank")  # Yield most relevant entries first.
)

使用 PostgreSQL 索引的 Django 全文搜索

Django full text search using indexes with PostgreSQL

python

django

postgresql

full-text-search

full-text-indexing

编辑：