Neo4j full-text search

The basic concept of full-text search

• Search
  Search this behavior is a process user interaction with the search engines, you need to find some data, he provided a number of constraints to the search engine search engine to extract some of the results to the user through the constraints
• Search engine
  exists to search engines store, find and retrieve data using search engines is .Neo4jLucene
• Document
  search software, the document is a first-class citizens. Store, search, display document are based on the core. Documents can be understood as simply a row of data in the database, but this line of data includes a field name.
• Inverted index
  inverted index search engine is the core data structure. In short, all the documents will become something like a book behind vocabularies. Be able to quickly find a word document from this data structure
• Lucene search syntax

Query implementation	Purpose	Example
TermQuery	Word Match	Neo4j
PhraseQuery	Phrase match	"graph database"
RangeQuery	Range matching	[A to Z] {A to Z}
WildcardQuery	Regular match	g*p?, d??abase
PrefixQuery	Prefix match	something*
FuzzyQuery	Suffix match	cipher~
BooleanQuery	Query polymerization	graph AND "shortest path"

Preparing the Environment

• Container starts Neo4j
  docker run -p 17687:7687 -p 17474:7474 --name=neo4j-test neo4j:3.5.3
• Create data, use test data.
  :play northwind-graph

Neo4j full-text search

Neo4j full-text search has the following characteristics, but with the down I feel is most important to create an index statement is really just founded to name the control . Neo4j from start to default on 2.2.x era node_auto_indexing=true. Inverted index at the time of data insertion has been created . create an index / delete an index of the cost is very small

• Support index relationship with the node
• It supports popular analyzersextensions
• You can use lucene querythe statement
• Ratings can return query results
• Automatic updating of indexes
• Any single index number of documents

Index creation and deletion

The establishment of two indexes, one Productindex of the label. In addition a full database of full-text search index

call db.index.fulltext.createNodeIndex("all",['Product', 'Category', 'Supplier'],['reorderLevel', 'unitsInStock', 'unitPrice', 'supplierID', 'productID', 'discontinued', 'quantityPerUnit', 'categoryID', 'unitsOnOrder', 'productName', 'description', 'categoryName', 'picture', 'country', 'address', 'contactTitle', 'city', 'phone', 'contactName', 'postalCode', 'companyName', 'fax', 'region', 'homePage'])

call db.index.fulltext.createNodeIndex("product",['Product'],['reorderLevel', 'unitsInStock', 'unitPrice', 'supplierID', 'productID', 'quantityPerUnit', 'discontinued', 'productName', 'unitsOnOrder', 'categoryID'])

Delete Index

call db.index.fulltext.drop("all")

You can get all the tags and attributes through the function

call db.propertyKeys
call db.labels

Inquire

There's a very simple query. Just remember that a statement will be able to deal with most scenes

call db.index.fulltext.queryNodes(
    'all',        //这里索引名
    'Av'          // lucene查询语句
) yield node
where node.address contains "12"   // where语句
return node 
order by node.address  // order skip limit
skip 0
limit 1

The basic concept of full-text search

• Search
  Search this behavior is a process user interaction with the search engines, you need to find some data, he provided a number of constraints to the search engine search engine to extract some of the results to the user through the constraints
• Search engine
  exists to search engines store, find and retrieve data using search engines is .Neo4jLucene
• Document
  search software, the document is a first-class citizens. Store, search, display document are based on the core. Documents can be understood as simply a row of data in the database, but this line of data includes a field name.
• Inverted index
  inverted index search engine is the core data structure. In short, all the documents will become something like a book behind vocabularies. Be able to quickly find a word document from this data structure
• Lucene search syntax

Query implementation	Purpose	Example
TermQuery	Word Match	Neo4j
PhraseQuery	Phrase match	"graph database"
RangeQuery	Range matching	[A to Z] {A to Z}
WildcardQuery	Regular match	g*p?, d??abase
PrefixQuery	Prefix match	something*
FuzzyQuery	Suffix match	cipher~
BooleanQuery	Query polymerization	graph AND "shortest path"

Preparing the Environment

• Container starts Neo4j
  docker run -p 17687:7687 -p 17474:7474 --name=neo4j-test neo4j:3.5.3
• Create data, use test data.
  :play northwind-graph

Neo4j full-text search

Neo4j full-text search has the following characteristics, but with the down I feel is most important to create an index statement is really just founded to name the control . Neo4j from start to default on 2.2.x era node_auto_indexing=true. Inverted index at the time of data insertion has been created . create an index / delete an index of the cost is very small

• Support index relationship with the node
• It supports popular analyzersextensions
• You can use lucene querythe statement
• Ratings can return query results
• Automatic updating of indexes
• Any single index number of documents

Index creation and deletion

The establishment of two indexes, one Productindex of the label. In addition a full database of full-text search index

call db.index.fulltext.createNodeIndex("all",['Product', 'Category', 'Supplier'],['reorderLevel', 'unitsInStock', 'unitPrice', 'supplierID', 'productID', 'discontinued', 'quantityPerUnit', 'categoryID', 'unitsOnOrder', 'productName', 'description', 'categoryName', 'picture', 'country', 'address', 'contactTitle', 'city', 'phone', 'contactName', 'postalCode', 'companyName', 'fax', 'region', 'homePage'])

call db.index.fulltext.createNodeIndex("product",['Product'],['reorderLevel', 'unitsInStock', 'unitPrice', 'supplierID', 'productID', 'quantityPerUnit', 'discontinued', 'productName', 'unitsOnOrder', 'categoryID'])

Delete Index

call db.index.fulltext.drop("all")

You can get all the tags and attributes through the function

call db.propertyKeys
call db.labels

Inquire

There's a very simple query. Just remember that a statement will be able to deal with most scenes

call db.index.fulltext.queryNodes(
    'all',        //这里索引名
    'Av'          // lucene查询语句
) yield node
where node.address contains "12"   // where语句
return node 
order by node.address  // order skip limit
skip 0
limit 1