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在PostgreSQL / SQLAlchemy中加快JSONB全文搜索

[英]Speed up JSONB full text search in PostgreSQL/SQLAlchemy

The performance of my JSONB full text search is awfully slow using PostgreSQL and SQLAlchemy. 使用PostgreSQL和SQLAlchemy,我的JSONB全文搜索的性能非常慢。 How can I speed it up? 我如何加快速度?

Model 模型

class Book(Base):
    __tablename__ = "book"
    id = Column(Integer, primary_key=True)
    jsondata = Column(JSONB)
    __table_args__ = (Index('index_jsondesc',
                      text("(jsondata->'description') jsonb_path_ops"),
                      postgresql_using="gin"),)

Full text search in the JSONB column JSONB列中的全文本搜索

class BookSearch:
    def __init__(self):
        pass
    def search(keyword):
        self.query = self.query.filter(Book.jsondata['description'].cast(Unicode).match(keyword))

booksearch = BookSearch()
booksearch.search("Python")

Given selective enough queries, speeding up full text search queries means having the proper index in place. 给定足够的选择性查询,加快全文搜索查询的速度就意味着要有适当的索引。 jsonb_path_ops do not benefit full text search: jsonb_path_ops不利于全文搜索:

The non-default GIN operator class jsonb_path_ops supports indexing the @> operator only. 非默认GIN运算符类jsonb_path_ops支持对@>运算符进行索引。

Instead you need (for example) a functional index for explicit to_tsvector() : 相反,您需要(例如) 显式to_tsvector()功能索引

class Book(Base):
    __tablename__ = "book"
    id = Column(Integer, primary_key=True)
    jsondata = Column(JSONB)
    __table_args__ = (
        Index('index_jsondesc',
              func.to_tsvector('english', jsondata['description'].astext),
              postgresql_using="gin"),
    )

Note that you must choose the configuration to use when defining the index. 请注意,在定义索引时,必须选择要使用的配置。 Your query must then match the configuration used in the index: 然后,您的查询必须与索引中使用的配置匹配:

def search(keyword):
    tsvector = func.to_tsvector('english', Book.jsondata['description'].astext)
    self.query = self.query.filter(tsvector.match(keyword))

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