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apoc.import.graphml

从本地文件导入需要将 apoc.import.file.enabled=true 设置在 apoc.conf 中。 Aura 不支持此功能。因此，Aura 实例仅限于导入公共托管文件。
详情

语法

apoc.import.graphml(urlOrBinaryFile, config) :: (file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data)

描述

从提供的 GraphML 文件导入图。

输入参数

名称

类型

描述

urlOrBinaryFile

ANY

要导入数据的文件名或二进制数据。

config

MAP

{ readLabels = false :: BOOLEAN, defaultRelationshipType = "RELATED" :: STRING, storeNodeIds = false :: BOOLEAN, batchSize = 20000 :: INTEGER, compression = "NONE" :: ["NONE", "BYTES", "GZIP", "BZIP2", "DEFLATE", "BLOCK_LZ4", "FRAMED_SNAPPY"], source = {} :: MAP, target = {} :: MAP }

返回参数

名称

类型

描述

file

STRING

导入数据的文件名。

source

STRING

导入数据的来源：“file”、“binary”或“file/binary”。

format

STRING

文件格式：["csv", "graphml", "json"]。

nodes

INTEGER

导入的节点数量。

relationships

INTEGER

导入的关系数量。

properties

INTEGER

导入的属性数量。

time

INTEGER

导入持续时间。

rows

INTEGER

返回的行数。

batchSize

INTEGER

导入运行时批处理的大小。

batches

INTEGER

导入运行的批次数量。

done

BOOLEAN

导入是否成功运行。

data

ANY

导入返回的数据。

配置参数

该存储过程支持以下配置参数

配置参数
名称 类型 默认值 描述

readLabels

BOOLEAN

false

根据节点元素的 labels 属性中的值创建节点标签

defaultRelationshipType

STRING

RELATED

如果 GraphML 文件中未指定关系类型，则使用的默认关系类型

storeNodeIds

BOOLEAN

false

存储节点元素的 id 属性

batchSize

INTEGER

20000

每个事务处理的元素数量

compression

Enum[NONE, BYTES, GZIP, BZIP2, DEFLATE, BLOCK_LZ4, FRAMED_SNAPPY]

null

允许接收二进制数据，未压缩（值：NONE）或已压缩（其他值）

source

MAP<STRING,STRING>

空映射

见下文

target

MAP<STRING,STRING>

空映射

见下文

源/目标配置

允许在源节点和/或目标节点不在文件中时导入关系，通过自定义标签和属性搜索节点。为此，我们可以在配置映射中插入 source: {label: '<MY_SOURCE_LABEL>', id: ’<MY_SOURCE_ID>'}` 和/或 source: {label: '<MY_TARGET_LABEL>', id: ’<MY_TARGET_ID>'}`。通过这种方式，我们可以通过 edge 标签的 source 和 end 属性搜索起始节点和结束节点。

例如，使用配置映射 {source: {id: 'myId', label: 'Foo'}, target: {id: 'other', label: 'Bar'}} 和类似 <edge id="e0" source="n0" target="n1" label="KNOWS"><data key="label">KNOWS</data></edge> 的边行，我们搜索源节点 (:Foo {myId: 'n0'}) 和结束节点 (:Bar {other: 'n1'})。id 键是可选的（默认值为 'id'）。

输出参数

名称 类型

file

STRING

source

STRING

format

STRING

nodes

INTEGER

relationships

INTEGER

properties

INTEGER

time

INTEGER

rows

INTEGER

batchSize

INTEGER

batches

INTEGER

done

BOOLEAN

data

STRING

从文件读取

默认情况下，从文件系统导入是禁用的。我们可以通过在 apoc.conf 中设置以下属性来启用它

apoc.conf
apoc.import.file.enabled=true

如果我们尝试使用任何导入过程而未首先设置此属性，我们将收到以下错误消息

Failed to invoke procedure: Caused by: java.lang.RuntimeException: Import from files not enabled, please set apoc.import.file.enabled=true in your apoc.conf

导入文件从 import 目录读取，该目录由 server.directories.import 属性定义。这意味着我们提供的任何文件路径都是相对于此目录的。如果尝试从绝对路径（例如 /tmp/filename）读取，我们将收到类似于以下内容的错误消息

Failed to invoke procedure: Caused by: java.lang.RuntimeException: Can’t read url or key file:/path/to/neo4j/import/tmp/filename as json: /path/to/neo4j//import/tmp/filename (No such file or directory)

我们可以通过在 apoc.conf 中设置以下属性来启用从文件系统上的任何位置读取文件

apoc.conf
apoc.import.file.use_neo4j_config=false

Neo4j 现在将能够从文件系统上的任何位置读取，因此在设置此属性之前请务必确认这是您的意图。

使用示例

导入简单 GraphML 文件

simple.graphml 文件包含来自 GraphML primer 的图表示。

apoc.import.graphml.simple diagram
simple.graphml
<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns
     http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
  <graph id="G" edgedefault="undirected">
    <node id="n0"/>
    <node id="n1"/>
    <node id="n2"/>
    <node id="n3"/>
    <node id="n4"/>
    <node id="n5"/>
    <node id="n6"/>
    <node id="n7"/>
    <node id="n8"/>
    <node id="n9"/>
    <node id="n10"/>
    <edge source="n0" target="n2"/>
    <edge source="n1" target="n2"/>
    <edge source="n2" target="n3"/>
    <edge source="n3" target="n5"/>
    <edge source="n3" target="n4"/>
    <edge source="n4" target="n6"/>
    <edge source="n6" target="n5"/>
    <edge source="n5" target="n7"/>
    <edge source="n6" target="n8"/>
    <edge source="n8" target="n7"/>
    <edge source="n8" target="n9"/>
    <edge source="n8" target="n10"/>
  </graph>
</graphml>
以下基于 simple.graphml 导入图
CALL apoc.import.graphml("http://graphml.graphdrawing.org/primer/simple.graphml", {})

如果我们运行此查询，将看到以下输出

结果
file source format nodes relationships properties time rows batchSize batches done data

"http://graphml.graphdrawing.org/primer/simple.graphml"

"file"

"graphml"

11

12

0

618

0

-1

0

TRUE

NULL

我们也可以将 simple.graphml 复制到 Neo4j 的 import 目录中，然后从那里导入文件。

然后我们可以通过以下方式运行导入过程

以下基于 simple.graphml 导入图
CALL apoc.import.graphml("file://simple.graphml", {})

下面的 Neo4j Browser 可视化显示了导入的图

apoc.import.graphml.simple
图 1. 简单图可视化

导入由导出 GraphML 存储过程创建的 GraphML 文件

movies.graphml 包含 Neo4j 电影图的一个子集，由 导出 GraphML 存储过程 生成。

movies.graphml
<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<key id="born" for="node" attr.name="born"/>
<key id="name" for="node" attr.name="name"/>
<key id="tagline" for="node" attr.name="tagline"/>
<key id="label" for="node" attr.name="label"/>
<key id="title" for="node" attr.name="title"/>
<key id="released" for="node" attr.name="released"/>
<key id="roles" for="edge" attr.name="roles"/>
<key id="label" for="edge" attr.name="label"/>
<graph id="G" edgedefault="directed">
<node id="n188" labels=":Movie"><data key="labels">:Movie</data><data key="title">The Matrix</data><data key="tagline">Welcome to the Real World</data><data key="released">1999</data></node>
<node id="n189" labels=":Person"><data key="labels">:Person</data><data key="born">1964</data><data key="name">Keanu Reeves</data></node>
<node id="n190" labels=":Person"><data key="labels">:Person</data><data key="born">1967</data><data key="name">Carrie-Anne Moss</data></node>
<node id="n191" labels=":Person"><data key="labels">:Person</data><data key="born">1961</data><data key="name">Laurence Fishburne</data></node>
<node id="n192" labels=":Person"><data key="labels">:Person</data><data key="born">1960</data><data key="name">Hugo Weaving</data></node>
<node id="n193" labels=":Person"><data key="labels">:Person</data><data key="born">1967</data><data key="name">Lilly Wachowski</data></node>
<node id="n194" labels=":Person"><data key="labels">:Person</data><data key="born">1965</data><data key="name">Lana Wachowski</data></node>
<node id="n195" labels=":Person"><data key="labels">:Person</data><data key="born">1952</data><data key="name">Joel Silver</data></node>
<edge id="e267" source="n189" target="n188" label="ACTED_IN"><data key="label">ACTED_IN</data><data key="roles">["Neo"]</data></edge>
<edge id="e268" source="n190" target="n188" label="ACTED_IN"><data key="label">ACTED_IN</data><data key="roles">["Trinity"]</data></edge>
<edge id="e269" source="n191" target="n188" label="ACTED_IN"><data key="label">ACTED_IN</data><data key="roles">["Morpheus"]</data></edge>
<edge id="e270" source="n192" target="n188" label="ACTED_IN"><data key="label">ACTED_IN</data><data key="roles">["Agent Smith"]</data></edge>
<edge id="e271" source="n193" target="n188" label="DIRECTED"><data key="label">DIRECTED</data></edge>
<edge id="e272" source="n194" target="n188" label="DIRECTED"><data key="label">DIRECTED</data></edge>
<edge id="e273" source="n195" target="n188" label="PRODUCED"><data key="label">PRODUCED</data></edge>
</graph>
</graphml>
以下基于 movies.graphml 导入图
CALL apoc.import.graphml("movies.graphml", {})

如果我们运行此查询，将看到以下输出

结果
file source format nodes relationships properties time rows batchSize batches done data

"movies.graphml"

"file"

"graphml"

8

7

36

23

0

-1

0

TRUE

NULL

我们可以运行以下查询来查看导入的图

MATCH p=()-->()
RETURN p
结果
p

({name: "Laurence Fishburne", born: "1961", labels: ":Person"})-[:ACTED_IN {roles: "[\"Morpheus\"]", label: "ACTED_IN"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", labels: ":Movie"})

({name: "Carrie-Anne Moss", born: "1967", labels: ":Person"})-[:ACTED_IN {roles: "[\"Trinity\"]", label: "ACTED_IN"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", la bels: ":Movie"})

({name: "Lana Wachowski", born: "1965", labels: ":Person"})-[:DIRECTED {label: "DIRECTED"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", labels: ":Movie"})

({name: "Joel Silver", born: "1952", labels: ":Person"})-[:PRODUCED {label: "PRODUCED"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", labels: ":Movie"})

({name: "Lilly Wachowski", born: "1967", labels: ":Person"})-[:DIRECTED {label: "DIRECTED"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", labels: ":Movie"})

({name: "Keanu Reeves", born: "1964", labels: ":Person"})-[:ACTED_IN {roles: "[\"Neo\"]", label: "ACTED_IN"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", labels: ": Movie"})

({name: "Hugo Weaving", born: "1960", labels: ":Person"})-[:ACTED_IN {roles: "[\"Agent Smith\"]", label: "ACTED_IN"}]→({tagline: "Welcome to the Real World", title: "The Matrix", released: "1999", la bels: ":Movie"})

GraphML 文件中定义的标签已添加到每个节点的 labels 属性中，而不是作为节点标签添加。我们可以将配置属性 readLabels: true 设置为导入原生标签

以下基于 movies.graphml 导入图并存储节点标签
CALL apoc.import.graphml("movies.graphml", {readLabels: true})
结果
file source format nodes relationships properties time rows batchSize batches done data

"movies.graphml"

"file"

"graphml"

8

7

21

23

0

-1

0

TRUE

NULL

现在让我们重新运行查询以查看导入的图

MATCH p=()-->()
RETURN;
结果
p

(:Person {name: "Lilly Wachowski", born: "1967"})-[:DIRECTED]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

(:Person {name: "Carrie-Anne Moss", born: "1967"})-[:ACTED_IN {roles: "[\"Trinity\"]"}]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

(:Person {name: "Hugo Weaving", born: "1960"})-[:ACTED_IN {roles: "[\"Agent Smith\"]"}]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

(:Person {name: "Laurence Fishburne", born: "1961"})-[:ACTED_IN {roles: "[\"Morpheus\"]"}]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

(:Person {name: "Keanu Reeves", born: "1964"})-[:ACTED_IN {roles: "[\"Neo\"]"}]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

(:Person {name: "Joel Silver", born: "1952"})-[:PRODUCED]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

(:Person {name: "Lana Wachowski", born: "1965"})-[:DIRECTED]→(:Movie {tagline: "Welcome to the Real World", title: "The Matrix", released: "1999"})

二进制文件

您还可以从二进制 byte[]（未压缩）或压缩文件（允许的压缩算法有：GZIP, BZIP2, DEFLATE, BLOCK_LZ4, FRAMED_SNAPPY）导入文件。

CALL apoc.import.graphml(`binaryGzipByteArray`,  {compression: 'GZIP'})

或

CALL apoc.import.graphml(`binaryFileNotCompressed`,  {compression: 'NONE'})

例如，这与 apoc.util.compress 函数配合使用效果很好

WITH apoc.util.compress('<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<graph id="G" edgedefault="directed">
<node id="n0"> <data key="labels">:FOO</data><data key="name">foo</data> </node>
<node id="n1"> <data key="labels">:BAR</data><data key="name">bar</data> <data key="kids">[a,b,c]</data> </node>
<edge id="e0" source="n0" target="n1"> <data key="label">:EDGE_LABEL</data> <data key="name">foo</data> </edge>
</graph>
</graphml>', {compression: 'DEFLATE'}) as xmlCompressed
CALL apoc.import.graphml(xmlCompressed,  {compression: 'DEFLATE'})
YIELD source, format, nodes, relationships, properties
RETURN source, format, nodes, relationships, properties
结果
source format nodes relationships properties

"binary"

"graphml"

2

1

7

往返分离的 GraphML 文件

使用此数据集

CREATE (f:Foo:Foo2:Foo0 {name:'foo', born:Date('2018-10-10'), place:point({ longitude: 56.7, latitude: 12.78, height: 100 })})-[:KNOWS]->(b:Bar {name:'bar',age:42, place:point({ longitude: 56.7, latitude: 12.78})});
CREATE (:Foo {name: 'zzz'})-[:KNOWS]->(:Bar {age: 0});
CREATE (:Foo {name: 'aaa'})-[:KNOWS {id: 1}]->(:Bar {age: 666});

我们可以执行这 3 个导出查询

// Foo nodes
call apoc.export.graphml.query('MATCH (start:Foo)-[:KNOWS]->(:Bar) RETURN start', 'queryNodesFoo.graphml', {useTypes: true});

// Bar nodes
call apoc.export.graphml.query('MATCH (:Foo)-[:KNOWS]->(end:Bar) RETURN end', 'queryNodesBar.graphml', {useTypes: true});

// KNOWS rels
MATCH (:Foo)-[rel:KNOWS]->(:Bar)
WITH collect(rel) as rels
call apoc.export.graphml.data([], rels, 'queryRelationship.graphml', {useTypes: true})
YIELD nodes, relationships RETURN nodes, relationships;

在这种情况下，我们将有以下 3 个文件：.queryNodesFoo.graphml

<?xml version='1.0' encoding='UTF-8'?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<key id="born" for="node" attr.name="born" attr.type="string"/>
<key id="name" for="node" attr.name="name" attr.type="string"/>
<key id="place" for="node" attr.name="place" attr.type="string"/>
<key id="labels" for="node" attr.name="labels" attr.type="string"/>
<graph id="G" edgedefault="directed">
<node id="n0" labels=":Foo:Foo0:Foo2"><data key="labels">:Foo:Foo0:Foo2</data><data key="born">2018-10-10</data><data key="name">foo</data><data key="place">{"crs":"wgs-84-3d","latitude":12.78,"longitude":56.7,"height":100.0}</data></node>
<node id="n3" labels=":Foo"><data key="labels">:Foo</data><data key="name">zzz</data></node>
<node id="n5" labels=":Foo"><data key="labels">:Foo</data><data key="name">aaa</data></node>
</graph>
</graphml>
queryNodesBar.graphml
<?xml version='1.0' encoding='UTF-8'?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<key id="name" for="node" attr.name="name" attr.type="string"/>
<key id="place" for="node" attr.name="place" attr.type="string"/>
<key id="age" for="node" attr.name="age" attr.type="long"/>
<key id="labels" for="node" attr.name="labels" attr.type="string"/>
<graph id="G" edgedefault="directed">
<node id="n1" labels=":Bar"><data key="labels">:Bar</data><data key="name">bar</data><data key="age">42</data><data key="place">{"crs":"wgs-84","latitude":12.78,"longitude":56.7,"height":null}</data></node>
<node id="n4" labels=":Bar"><data key="labels">:Bar</data><data key="age">0</data></node>
<node id="n6" labels=":Bar"><data key="labels">:Bar</data><data key="age">666</data></node>
</graph>
</graphml>
queryRelationship.graphml
<?xml version='1.0' encoding='UTF-8'?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<key id="label" for="edge" attr.name="label" attr.type="string"/>
<key id="id" for="edge" attr.name="id" attr.type="long"/>
<graph id="G" edgedefault="directed">
<edge id="e0" source="n0" target="n1" label="KNOWS"><data key="label">KNOWS</data></edge>
<edge id="e1" source="n3" target="n4" label="KNOWS"><data key="label">KNOWS</data></edge>
<edge id="e2" source="n5" target="n6" label="KNOWS"><data key="label">KNOWS</data><data key="id">1</data></edge>
</graph>
</graphml>

因此，我们可以通过这种方式在另一个数据库中导入，以使用这些查询重新创建原始数据集

CALL apoc.import.graphml('queryNodesFoo.graphml', {readLabels: true, storeNodeIds: true});
CALL apoc.import.graphml('queryNodesBar.graphml', {readLabels: true, storeNodeIds: true});
CALL apoc.import.graphml('queryRelationship.graphml', {readLabels: true, source: {label: 'Foo'}, target: {label: 'Bar'}});

请注意，我们必须先执行节点导入，并且我们使用 useTypes: true 将节点标签的 id 属性作为属性导入，并使用 readLabels 为节点填充标签。

使用自定义属性键

否则，我们可以利用自定义属性并避免以这种方式导入 id 属性（通过 useTypes:true）（与之前相同的数据集和节点导出查询）

// KNOWS rels
MATCH (:Foo)-[rel:KNOWS]->(:Bar)
WITH collect(rel) as rels
call apoc.export.graphml.data([], rels, 'queryRelationship.graphml',
  {useTypes: true, source: {id: 'name'}, label: {id: 'age'}})
YIELD nodes, relationships RETURN nodes, relationships;

强烈建议使用唯一性约束来确保唯一性，因此在这种情况下，对于标签 Foo 和属性 name，以及对于标签 Bar 和属性 age

以上查询生成此关系文件

queryRelationship.graphml
<?xml version='1.0' encoding='UTF-8'?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
<key id="label" for="edge" attr.name="label" attr.type="string"/>
<key id="id" for="edge" attr.name="id" attr.type="long"/>
<graph id="G" edgedefault="directed">
<edge id="e0" source="foo" sourceType="string" target="42" targetType="long" label="KNOWS"><data key="label">KNOWS</data></edge>
<edge id="e1" source="zzz" sourceType="string" target="0" targetType="long" label="KNOWS"><data key="label">KNOWS</data></edge>
<edge id="e2" source="aaa" sourceType="string" target="666" targetType="long" label="KNOWS"><data key="label">KNOWS</data><data key="id">1</data></edge>
</graph>
</graphml>

最后，我们可以使用与上述相同的 id（name 和 age）导入文件

CALL apoc.import.graphml('queryNodesFoo.graphml', {readLabels: true});
CALL apoc.import.graphml('queryNodesBar.graphml', {readLabels: true});
CALL apoc.import.graphml('queryRelationship.graphml',
  {readLabels: true, source: {label: 'Foo', id: 'name'}, target: {label: 'Bar', id: 'age'}});
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