导出为 CSV

导出 CSV 的过程将数据导出为 Python 和 R 生态系统中数据科学库更支持的格式。我们也可以将数据导出为 JSON 格式，以便导入其他工具或用于查询结果的通用共享。本节描述的过程支持导出到文件或作为流（stream）输出。

对于 apoc.export.csv.all、apoc.export.csv.data 和 apoc.export.csv.graph，节点和关系的属性按字母顺序排列，并使用以下结构：

_id,_labels,<list_nodes_properties_naturally_sorted>,_start,_end,_type,<list_rel_properties_naturally_sorted>.

对于一个包含节点属性 age, city, kids, male, name 和 street，以及关系属性 bar 和 foo 的图，我们将得到以下结构：

_id,_labels,age,city,kids,male,name,street,_start,_end,_type,bar,foo

导出的标签按字母顺序排列。labels() 函数的输出不是排序的，请将其与 apoc.coll.sort() 结合使用。

请注意，为了执行正确的 Point 序列化，不建议导出坐标为 x,y 和 crs: 'wgs-84' 的点，例如 point({x: 56.7, y: 12.78, crs: 'wgs-84'})。否则，该点将被导出为经度和纬度（以及高度），而不是 x 和 y（以及 z）。

可用过程

下表描述了可用的过程：

限定名称类型

限定名称	类型
apoc.export.csv.all `apoc.export.csv.all(file STRING, config MAP<STRING, ANY>)` - 将整个数据库导出到提供的 CSV 文件中。	`过程`
apoc.export.csv.data `apoc.export.csv.data(nodes LIST<NODE>, rels LIST<RELATIONSHIP>, file STRING, config MAP<STRING, ANY>)` - 将给定的 `NODE` 和 `RELATIONSHIP` 值导出到提供的 CSV 文件中。	`过程`
apoc.export.csv.graph `apoc.export.csv.graph(graph MAP<STRING, ANY>, file STRING, config MAP<STRING, ANY>)` - 将给定的图导出到提供的 CSV 文件中。	`过程`
apoc.export.csv.query `apoc.export.csv.query(query STRING, file STRING, config MAP<STRING, ANY>)` - 将运行给定 Cypher 查询的结果导出到提供的 CSV 文件中。	`过程`

apoc.export.csv.all
apoc.export.csv.all(file STRING, config MAP<STRING, ANY>) - 将整个数据库导出到提供的 CSV 文件中。

过程

apoc.export.csv.data
apoc.export.csv.data(nodes LIST<NODE>, rels LIST<RELATIONSHIP>, file STRING, config MAP<STRING, ANY>) - 将给定的 NODE 和 RELATIONSHIP 值导出到提供的 CSV 文件中。

过程

apoc.export.csv.graph
apoc.export.csv.graph(graph MAP<STRING, ANY>, file STRING, config MAP<STRING, ANY>) - 将给定的图导出到提供的 CSV 文件中。

过程

apoc.export.csv.query
apoc.export.csv.query(query STRING, file STRING, config MAP<STRING, ANY>) - 将运行给定 Cypher 查询的结果导出到提供的 CSV 文件中。

过程

导出到文件

默认情况下，导出到文件系统是被禁用的。我们可以通过在 apoc.conf 中设置以下属性来启用它：

apoc.conf

apoc.export.file.enabled=true

有关访问 apoc.conf 的更多信息，请参阅配置选项章节。

如果我们尝试在未先设置此属性的情况下使用任何导出过程，我们将收到以下错误消息：

Failed to invoke procedure: Caused by: java.lang.RuntimeException: Export to files not enabled, please set apoc.export.file.enabled=true in your apoc.conf. Otherwise, if you are running in a cloud environment without filesystem access, use the {stream:true} config and null as a 'file' parameter to stream the export back to your client.

导出文件被写入 import 目录，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。如果我们尝试写入绝对路径（例如 /tmp/filename），我们将收到类似于以下内容的错误消息：

Failed to invoke procedure: Caused by: java.io.FileNotFoundException: /path/to/neo4j/import/tmp/fileName (No such file or directory)

我们可以通过在 apoc.conf 中设置以下属性来允许写入文件系统上的任何位置：

apoc.conf

apoc.import.file.use_neo4j_config=false

Neo4j 现在将能够写入文件系统上的任何位置，因此在设置此属性之前，请确保这是您的意图。

导出流

如果我们不想导出到文件，可以通过将文件名设置为 null 并提供 stream:true 配置，将结果流式传输回 data 列。

示例

本节包含展示如何使用导出到 CSV 过程的示例。这些示例基于电影数据集，可以通过运行以下 Cypher 查询来导入：

CREATE (TheMatrix:Movie {title:'The Matrix', released:1999, tagline:'Welcome to the Real World'})
CREATE (Keanu:Person {name:'Keanu Reeves', born:1964})
CREATE (Carrie:Person {name:'Carrie-Anne Moss', born:1967})
CREATE (Laurence:Person {name:'Laurence Fishburne', born:1961})
CREATE (Hugo:Person {name:'Hugo Weaving', born:1960})
CREATE (LillyW:Person {name:'Lilly Wachowski', born:1967})
CREATE (LanaW:Person {name:'Lana Wachowski', born:1965})
CREATE (JoelS:Person {name:'Joel Silver', born:1952})
CREATE
(Keanu)-[:ACTED_IN {roles:['Neo']}]->(TheMatrix),
(Carrie)-[:ACTED_IN {roles:['Trinity']}]->(TheMatrix),
(Laurence)-[:ACTED_IN {roles:['Morpheus']}]->(TheMatrix),
(Hugo)-[:ACTED_IN {roles:['Agent Smith']}]->(TheMatrix),
(LillyW)-[:DIRECTED]->(TheMatrix),
(LanaW)-[:DIRECTED]->(TheMatrix),
(JoelS)-[:PRODUCED]->(TheMatrix);

下方的 Neo4j Browser 可视化显示了导入的图

将整个数据库导出为 CSV

apoc.export.csv.all 过程将整个数据库导出到 CSV 文件或作为流输出。

以下查询将整个数据库导出到文件 movies.csv：

CALL apoc.export.csv.all("movies.csv", {})

表 1. 结果
file	source	format	节点	relationships	属性	time	rows	batchSize	batches	done	data
"movies.csv"	"database: nodes(8), rels(7)"	"csv"	8	7	21	39	15	20000	1	TRUE	NULL

movies.csv 的内容如下所示：

movies.csv

"_id","_labels","born","name","released","tagline","title","_start","_end","_type","roles"
"188",":Movie","","","1999","Welcome to the Real World","The Matrix",,,,
"189",":Person","1964","Keanu Reeves","","","",,,,
"190",":Person","1967","Carrie-Anne Moss","","","",,,,
"191",":Person","1961","Laurence Fishburne","","","",,,,
"192",":Person","1960","Hugo Weaving","","","",,,,
"193",":Person","1967","Lilly Wachowski","","","",,,,
"194",":Person","1965","Lana Wachowski","","","",,,,
"195",":Person","1952","Joel Silver","","","",,,,
,,,,,,,"189","188","ACTED_IN","[""Neo""]"
,,,,,,,"190","188","ACTED_IN","[""Trinity""]"
,,,,,,,"191","188","ACTED_IN","[""Morpheus""]"
,,,,,,,"192","188","ACTED_IN","[""Agent Smith""]"
,,,,,,,"193","188","DIRECTED",""
,,,,,,,"194","188","DIRECTED",""
,,,,,,,"195","188","PRODUCED",""

以下查询在 data 列中返回整个数据库的流：

CALL apoc.export.csv.all(null, {stream:true})
YIELD file, nodes, relationships, properties, data
RETURN file, nodes, relationships, properties, data

表 2. 结果
file	节点	relationships	属性	data
`NULL`	`8`	`7`	`21`	"\"_id\",\"_labels\",\"born\",\"name\",\"released\",\"tagline\",\"title\",\"_start\",\"_end\",\"_type\",\"roles\" \"188\",\":Movie\",\"\",\"\",\"1999\",\"Welcome to the Real World\",\"The Matrix\",,,, \"189\",\":Person\",\"1964\",\"Keanu Reeves\",\"\",\"\",\"\",,,, \"190\",\":Person\",\"1967\",\"Carrie-Anne Moss\",\"\",\"\",\"\",,,, \"191\",\":Person\",\"1961\",\"Laurence Fishburne\",\"\",\"\",\"\",,,, \"192\",\":Person\",\"1960\",\"Hugo Weaving\",\"\",\"\",\"\",,,, \"193\",\":Person\",\"1967\",\"Lilly Wachowski\",\"\",\"\",\"\",,,, \"194\",\":Person\",\"1965\",\"Lana Wachowski\",\"\",\"\",\"\",,,, \"195\",\":Person\",\"1952\",\"Joel Silver\",\"\",\"\",\"\",,,, ,,,,,,,\"189\",\"188\",\"ACTED_IN\",\"[\"\"Neo\"\"]\" ,,,,,,,\"190\",\"188\",\"ACTED_IN\",\"[\"\"Trinity\"\"]\" ,,,,,,,\"191\",\"188\",\"ACTED_IN\",\"[\"\"Morpheus\"\"]\" ,,,,,,,\"192\",\"188\",\"ACTED_IN\",\"[\"\"Agent Smith\"\"]\" ,,,,,,,\"193\",\"188\",\"DIRECTED\",\"\" ,,,,,,,\"194\",\"188\",\"DIRECTED\",\"\" ,,,,,,,\"195\",\"188\",\"PRODUCED\",\"\" "

将指定的节点和关系导出为 CSV

apoc.export.csv.data 过程将指定的节点和关系导出到 CSV 文件或作为流输出。

以下查询将所有带有 :Person 标签且 name 属性以 L 开头的节点导出到文件 movies-l.csv：

MATCH (person:Person)
WHERE person.name STARTS WITH "L"
WITH collect(person) AS people
CALL apoc.export.csv.data(people, [], "movies-l.csv", {})
YIELD file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data
RETURN file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data

表 3. 结果
file	source	format	节点	relationships	属性	time	rows	batchSize	batches	done	data
"movies-l.csv"	"data: nodes(3), rels(0)"	"csv"	3	0	6	2	3	20000	1	TRUE	NULL

movies-l.csv 的内容如下所示：

"_id","_labels","born","name","_start","_end","_type"
"191",":Person","1961","Laurence Fishburne",,,
"193",":Person","1967","Lilly Wachowski",,,
"194",":Person","1965","Lana Wachowski",,,

以下查询将所有 ACTED_IN 关系以及该关系两侧带有 Person 和 Movie 标签的节点导出到文件 movies-actedIn.csv：

MATCH (person:Person)-[actedIn:ACTED_IN]->(movie:Movie)
WITH collect(DISTINCT person) AS people, collect(DISTINCT movie) AS movies, collect(actedIn) AS actedInRels
CALL apoc.export.csv.data(people + movies, actedInRels, "movies-actedIn.csv", {})
YIELD file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data
RETURN file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data

表 4. 结果
file	source	format	节点	relationships	属性	time	rows	batchSize	batches	done	data
"movies-actedIn.csv"	"data: nodes(5), rels(4)"	"csv"	5	4	15	2	9	20000	1	TRUE	NULL

movies-actedIn.csv 的内容如下所示：

"_id","_labels","born","name","released","tagline","title","_start","_end","_type","roles"
"189",":Person","1964","Keanu Reeves","","","",,,,
"190",":Person","1967","Carrie-Anne Moss","","","",,,,
"191",":Person","1961","Laurence Fishburne","","","",,,,
"192",":Person","1960","Hugo Weaving","","","",,,,
"188",":Movie","","","1999","Welcome to the Real World","The Matrix",,,,
,,,,,,,"189","188","ACTED_IN","[""Neo""]"
,,,,,,,"190","188","ACTED_IN","[""Trinity""]"
,,,,,,,"191","188","ACTED_IN","[""Morpheus""]"
,,,,,,,"192","188","ACTED_IN","[""Agent Smith""]"

以下查询在 data 列中返回所有 ACTED_IN 关系以及该关系两侧带有 Person 和 Movie 标签的节点的流：

MATCH (person:Person)-[actedIn:ACTED_IN]->(movie:Movie)
WITH collect(DISTINCT person) AS people, collect(DISTINCT movie) AS movies, collect(actedIn) AS actedInRels
CALL apoc.export.csv.data(people + movies, actedInRels, null, {stream: true})
YIELD file, nodes, relationships, properties, data
RETURN file, nodes, relationships, properties, data

表 5. 结果
file	节点	relationships	属性	data
`NULL`	`5`	`4`	`15`	"\"_id\",\"_labels\",\"born\",\"name\",\"released\",\"tagline\",\"title\",\"_start\",\"_end\",\"_type\",\"roles\" \"190\",\":Person\",\"1967\",\"Carrie-Anne Moss\",\"\",\"\",\"\",,,, \"189\",\":Person\",\"1964\",\"Keanu Reeves\",\"\",\"\",\"\",,,, \"191\",\":Person\",\"1961\",\"Laurence Fishburne\",\"\",\"\",\"\",,,, \"192\",\":Person\",\"1960\",\"Hugo Weaving\",\"\",\"\",\"\",,,, \"188\",\":Movie\",\"\",\"\",\"1999\",\"Welcome to the Real World\",\"The Matrix\",,,, ,,,,,,,\"189\",\"188\",\"ACTED_IN\",\"[\"\"Neo\"\"]\" ,,,,,,,\"190\",\"188\",\"ACTED_IN\",\"[\"\"Trinity\"\"]\" ,,,,,,,\"191\",\"188\",\"ACTED_IN\",\"[\"\"Morpheus\"\"]\" ,,,,,,,\"192\",\"188\",\"ACTED_IN\",\"[\"\"Agent Smith\"\"]\" "

将 Cypher 查询结果导出为 CSV

apoc.export.csv.query 过程将 Cypher 查询的结果导出到 CSV 文件或作为流输出。

以下查询将所有 DIRECTED 关系以及该关系两侧带有 Person 和 Movie 标签的节点导出到文件 movies-directed.csv：

WITH "MATCH path = (person:Person)-[:DIRECTED]->(movie)
      RETURN person.name AS name, person.born AS born,
             movie.title AS title, movie.tagline AS tagline, movie.released AS released" AS query
CALL apoc.export.csv.query(query, "movies-directed.csv", {})
YIELD file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data
RETURN file, source, format, nodes, relationships, properties, time, rows, batchSize, batches, done, data;

表 6. 结果
file	source	format	节点	relationships	属性	time	rows	batchSize	batches	done	data
"movies-directed.csv"	"statement: cols(5)"	"csv"	0	0	10	3	2	20000	1	TRUE	NULL

movies-directed.csv 的内容如下所示：

"name","born","role","title","tagline","released"
"Lilly Wachowski","1967","","The Matrix","Welcome to the Real World","1999"
"Lana Wachowski","1965","","The Matrix","Welcome to the Real World","1999"

以下查询返回所有 DIRECTED 关系以及该关系两侧带有 Person 和 Movie 标签的节点的流：

WITH "MATCH path = (person:Person)-[:DIRECTED]->(movie)
      RETURN person.name AS name, person.born AS born,
             movie.title AS title, movie.tagline AS tagline, movie.released AS released" AS query
CALL apoc.export.csv.query(query, null, {stream: true})
YIELD file, nodes, relationships, properties, data
RETURN file, nodes, relationships, properties, data;

表 7. 结果
file	节点	relationships	属性	data
`NULL`	`0`	`0`	`10`	"\"name\",\"born\",\"title\",\"tagline\",\"released\" \"Lilly Wachowski\",\"1967\",\"The Matrix\",\"Welcome to the Real World\",\"1999\" \"Lana Wachowski\",\"1965\",\"The Matrix\",\"Welcome to the Real World\",\"1999\" "

您还可以压缩要导出的文件。请点击此处获取更多信息

当启用 bulkImport 配置时，它会创建一个可用于 Neo4j 批量导入的文件列表。

此配置仅可与 apoc.export.csv.all 和 apoc.export.csv.graph 一起使用。

所有创建的文件命名如下：

节点文件由输入文件的名称加上 .nodes.[LABEL_NAME].csv 组成。
关系文件由输入文件的名称加上 .relationships.[TYPE_NAME].csv 组成。

如果节点或关系有多个标签/类型，它将为每个标签/类型创建一个文件。

配置参数

该过程支持以下配置参数

表 8. 配置选项
参数	默认	description（描述）
batchSize	20000	批处理大小。
delim	","	CSV 文件的分隔符字符。
arrayDelim	";"	用于数组的分隔符字符（用于批量导入）。
quotes	'always'	用于 CSV 的引用字符，可能的值为： `none`：不添加任何引用。 `always`：在所有值周围添加引用。 `ifNeeded`：仅在必要时对字符串应用引用。
differentiateNulls	false	在空字符串和 null 值之间创建区分。其行为受 `quotes` 配置值的影响： `none`：空字符串和 null 不加引号。 `ifNeeded` && `differentiateNulls`：空字符串用 `""` 引用，null 值留空。 `ifNeeded` && !`differentiateNulls`：空字符串和 null 值留空。 `always` && `differentiateNulls`：空字符串用 `""` 引用，null 值留空。 `always` && !`differentiateNulls`：空字符串和 null 值都用 `""` 引用。
useTypes	false	将类型添加到文件头中。
bulkImport	true	为 Neo4j Admin 导入创建文件。
timeoutSeconds	100	查询在超时前应运行的最大秒数。
separateHeader	false	创建两个文件：一个用于头部，一个用于数据。
streamStatements	false	通过配置 `batchSize` 配置，跨多个行批处理结果。
stream	false	等同于 `streamStatements` 配置。

引用配置示例

可以使用不同的引用策略将图导出到 CSV 文件。

以下查询是在包含一个节点的图上执行的：

CREATE (:Quote {name: 'foo,bar,baz', array:["a","b","c"], other: 123})

不带引用导出

CALL apoc.export.csv.all("fileNoQuote.csv", {quotes: 'none'})

返回以下 CSV 文件：

fileNoQuote.csv

_id,_labels,array,name,other,_start,_end,_type
5,:Quote,["a","b","c"],foo,bar,baz,123,,,

带引用导出

CALL apoc.export.csv.all("fileAlwaysQuote.csv", {quotes: 'always'})

返回以下 CSV 文件：

fileAlwaysQuote.csv

"_id","_labels","array","name","other","_start","_end","_type"
"5",":Quote","[""a"",""b"",""c""]","foo,bar,baz","123",,,

必要时带引用导出

CALL apoc.export.csv.all("fileIfNeededQuote.csv", {quotes: 'ifNeeded'})

返回以下 CSV 文件：

fileIfNeededQuote.csv

_id,_labels,array,name,other,_start,_end,_type
5,:Quote,"[""a"",""b"",""c""]","foo,bar,baz",123,,,

区分 null 值配置示例

默认情况下，空字符串和 null 值被视为相同，但可以使用 differentiateNulls 配置项更改此行为。

以下查询是在包含两个节点的图上执行的：

CREATE (:Quote {value1: "Hello", value2: ""})
CREATE (:Quote {value1: "I have a \"null\" value", value2: null})

带引用并区分 null 值导出

CALL apoc.export.csv.all("fileAlwaysQuote.csv", {quotes: 'always', differentiateNulls: true})

返回以下 CSV 文件：

fileAlwaysQuote.csv

"_id","_labels","value1","value2","_start","_end","_type"
"0",":Quote","Hello","",,,
"1",":Quote","I have a ""null"" value",,,,

value2 的空字符串值由引号 "" 表示，而 null 值则留空。

必要时带引用并区分 null 值导出

CALL apoc.export.csv.all("fileIfNeededQuote.csv", {quotes: 'ifNeeded', differentiateNulls: true})

返回以下 CSV 文件：

fileIfNeededQuote.csv

_id,_labels,value1,value2,_start,_end,_type
0,:Quote,Hello,"",,,
1,:Quote,"I have a ""null"" value",,,,

字符串 Hello 未加引号，因为它不包含任何特殊字符。字符串 I have a "null" value 被加了引号，因为它包含特殊字符。空字符串被加了引号以区别于 null 值。null 值为空。

不带引用导出

当不带引用导出时，null 和空字符串将始终显示为不带引用，无论 differentiateNulls 设置为什么。

CALL apoc.export.csv.all("fileNoQuote.csv", {quotes: 'none', differentiateNulls: true})

返回以下 CSV 文件：

fileNoQuote.csv

_id,_labels,value1,value2,_start,_end,_type
0,:Quote,Hello,,,,
1,:Quote,I have a "null" value,,,,